Based on Pennes equation, the influences of the intensity and the impulse frequency of laser acupuncture on the point tissues' blood flow perfusion rate are discussed. We find that the blood perfusion rate of point tissue increases with the intensity of laser acupuncture increasing. After impulse laser acupuncture the point tissue blood perfusion rate increase little, but after continuum laser acupuncture the point tissues blood perfusion rate increase much.

Ulcerative colitis (UC) is an inflammatory destructive disease of the large intestine occurred usually in the rectum and lower part of the colon as well as the entire colon. In this paper, the influence of IL-1α and IL-4 on the experimental ulcerative colitis by light emitting diode ( LED ) (λ: 632.8nm; power: 4.0mw) applied to colon directly were studied. Making 30 rats into 3 groups: LED curative group, model group, normal control group. There were 10 rats of each group. We used glacial acetic acid (5%) and trinitro-benzene-sulfonic acid (TNBS) (1%) intra-anally to replicate the rat model of ulcerative colitis. After a week treatment with administrating LED rectal irradiation to curative group, 30mm each time, once per day, the histopathological studies in colonic tissue were performed, and the expression and distribution of IL-lα and IL-4 in colonic tissues were investigated by immunohistochemical staining. The extent of the Colonic tissue injury in LED curative group was not as significant as that in the model group. Compared with model group, the content of MDA in LED curative group was reductived and the activity of SOD was increased significantly, and the expression and distribution of IL-lα in LED curative group was depressed significantly, however the expression and distribution of IL-4 in LED curative group was increased obviously. This results show that the LED rectal irradiation can protect colonic mucosa from the experimental ulcerative colitis in rats, and suggest that the effects may be related to the photobiomodulation and immunomodulation of LED.

We describe a new method for evaluating the viscoelastical characterization of biological tissue by photoacoustic technique in this paper. The amplitude attenuation curse of the tissue photoacoustic signals (the stress waves) induced by Q-YAG laser provides necessary data for us to work out the decay time of the stress waves. According to the theory of viscoelasticity, the decay time is equal to the tissue viscosity-elasticity ratio. The result we get from measuring gelatin shows the viscosity-elasticity ratio of Kelvin-Voigt model tissue obtained by photoacoustic measurement almostly equals that by conventional rheometer. The agreement is almost 97%. Furthermore, we firstly apply the method to measure the tissue viscosity-elasiicity ratio of Maxwell model. From the theorical analysis and the experimental result, we can conclude that the method can be applied to any model tissue, because it is only related with its acoustic impedance, having nothing to do with tissue state. In short, photoacoustic measurement is real-time, noninvasive and highly sensitive and repetitive. Based on the virtues mentioned above, it can be widely applied to biology and medicine.

In the research of non-invasive concentration blood measurement, the scattering behavior of the tissue may leads to significant differences in the ideal Lambert Beer's law. In this paper, Monte Carlo method is used to analyses the blood tissue's influence to the Dynamic Spectrum proposed by Professor LI Gang. The Dynamic Spectrum evaluating only the pulsatile part of the entire optical signal, this approach is rather independent of individual or time changes in scattering or absorption characteristics of the tissue. In this paper, Monte Carlo method is used to analyses the scattering behavior of the blood, the influence of the scattering behavior of the skin tissue to the scattering behavior of the blood. and their influence to the Dynamic Spectrum. The pulsatile part ofthe spectrum was modeled by performing simulations of photon migration through the tissue for the diastolic and systolic states. With the simulation of the Monte Carlo method. the diffuse reflectance and transmittance of the model was calculated, analyzed and compared. The scattering behavior must be considered in the measurement of Dynamic Spectrum to get the high precision measurement. The error caused by the transmittance is greater than the error caused by the diffuse reflectance. The thickness of the Epidermis can influence the nonlinearity of the transmittance, and influence the value of the diffuse reflectance. The thickness of the tissue can influence the scattering behavior of the tissue.

The polarization properties of light backscattered from the Intralipid suspensions are investigated for different input polarized light. The Stokes vector of the diffuse backscattered light exiting the sample is measured by use of CCD experimental setup. The backscattering intensity and the degree of polarization are calculated from each Stokes vector. Especially, the emphasis is on the influence of linearly polarized light with different input azimuth angle, the circularly polarized light with the different rotary direction on the backscattering intensity and the degree of polarization of the turbid media. Furthermore, both the relations of the backscattering intensity with the media concentration and the degree of polarization with the media concentration for different input polarization state, different input azimuth angle are presented. These experimental results have shown that the degree of polarization and the intensity of light backscattered from a turbid media are sensitive to the input polarization state and the media concentration.

Near-IR radiation is often utilized to detect the properties in tissues. If the diffusion equation can be applied to analyze and determine optical properties of superficial biological tissue, the pathological changes occurring in vivo will be understood and thus the noninvasive measurement can be realized. Up to now, a semi-infinite medium photon migration model and a two-layered turbid medium model are applied widely. On the basis of diffusion equation, the photon diffusion through a three-layered matching medium was analyzed and the Green's function in the steady state solved by employing the extrapolated boundary condition. With the results, it is found the solution of two-layered media is the simplified form of three-layered matching turbid media.

Near-IR radiation has great potential in medical diagnosis and therapy because of the non-invasive nature of light and the selectively poisonous effect to tumors of photodynarnic treatment. Therefore, Near-IR light propagation in highly scattering biological tissue must be understudied for basic research and clinical application of biomedical optics. A tissue is multi-layered mismatched medium, but many investigators only study the diffusion equation of matched medium. they take the tissue as the same refractive index. In order to understand the light transport in tissue, We analyze the diffusion of photons three-layered mismatched medium and set up the solution of Green's function in frequency domain, we employ the extrapolated boundary condition to set up a solution of the diffusion equation. At the same time, we utilize the diffuse equation to calculate the phase in different situation

During numerical simulation of laser and tissue thermal interaction, the light fluence rate distribution should be formularized and constituted to the source term in the heat transfer equation. Usually the solution of light irradiative transport equation is given in extreme conditions such as full absorption (Lambert-Beer Law), full scattering (Lubelka-Munk theory), most scattering (Diffusion Approximation) et al. But in specific conditions, these solutions will induce different errors. The usually used Monte Carlo simulation (MCS) is more universal and exact but has difficulty to deal with dynamic parameter and fast simulation. Its area partition pattern has limits when applying FEM (finite element method) to solve the bio-heat transfer partial differential coefficient equation. Laser heat source plots of above methods showed much difference with MCS. In order to solve this problem, through analyzing different optical actions such as reflection, scattering and absorption on the laser induced heat generation in bio-tissue, a new attempt was made out which combined the modified beam broaden model and the diffusion approximation model. First the scattering coefficient was replaced by reduced scattering coefficient in the beam broaden model, which is more reasonable when scattering was treated as anisotropic scattering. Secondly the attenuation coefficient was replaced by effective attenuation coefficient in scattering dominating turbid bio-tissue. The computation results of the modified method were compared with Monte Carlo simulation and showed the model provided reasonable predictions of heat source term distribution than past methods. Such a research is useful for explaining the physical characteristics of heat source in the heat transfer equation, establishing effective photo-thermal model, and providing theory contrast for related laser medicine experiments.

To describe the complex nonlinear process of laser tissue interactions during laser-induced interstitial thermotherapy (LITT), a two-dimensional mathematical model considering the dynamic changes in the physical tissue properties was developed. A modified Monte Carlo method was developed to simulate photon transport in tissue with a non-uniform optical property field, the finite volume method was used to numerically solve the Pennes bioheat equation to calculate the temperature distribution and the Arrhenius equation was used to predict the thennal damage extent. A temperature control heating method was also incorporated into present model to simulate the LITT clinical treatment to increase thermal damage volume and avoid evaporation and carbonization. The numerical results showed that the dynamic changes in the optical properties, the thermal properties and the blood perfusion rate significanfly affected the damage volume accumulation in tissue and should be included in munerical simulations of the LITT treatment.

A Monte Carlo algorithm to simulate the propagation of polarized light was used and the backscattered Mueller matrices were calculated for various scattering and absorption coefficients and layered structures. Results show that scattering produce a spatial re-distribution of light, while absorption only causes a uniform decrease in intensity. The major contribution to backscattered Mueller matrix comes from weakly scattered photons. As scattering enhances the majority of these photons exit from around the centre. result in image intensity increase around the centre and decrease at the edge. For absorption strengthen only uniform intensity weakening was observed. Both can be easily differentiated by Mueller matrix distribution patterns. A two-layer niodel with thin surface layer was also calculated, Mueller matrix represent disparate alternant rule for upper and lower layer, which suggest possibilities for discriminating subtle epidennal structure. All these results together indicate that discriminate optical properties in turbid media using backscattered Mueller matrix is feasible.

Ultrasound-modulated optical tomography is a promising and noninvasive method for biomedical imaging. The advantage of this technology is its combination of optical contrast and ultrasonic resolution. In order to reconstruct the tissue imaging effectively and reliably, the propagation of the light modulated by ultrasound in the tissue should be understood extensively. In our opinion, there are three light transport processes in tissue as follows: Firstly, the incident light goes from the surface to the focused region. If the distance, tagged as Iis long enough (Z>>mfp, mean free path). the light transport obeys diffuse theory. Secondly, the diffuse light can be modulated in the focused region at Z due to the light-sound interaction. Finally, the modulation light from the Z can be regarded as a spot light source which emits the ballistic or snake photons to reach the surface and so as to be collected by a detector outside of tissue in the third process. the propagation of the diffused light modulated by ultrasound play an important role in particularly because it reflects some information about the optical and ultrasonic properties of tissue. Based on the Monte Carlo simulation, the relations to the modulation light intensity and its modulation depth contributed by the tissue thickness, optical properties, etc. are figured out and supported by an equivalent experiment and at an extended condition also agree with the diffuse theory.

The doughnut beams with charges of 1 to 3 are generated by one and stacking two and three Liquid crystal(LC) spiral phase plates with cell gaps of 7 μm respectively. Theoretically, any charge number can be obtained by the stacking method. High efficiency and flexibility are the advantages of generating doughnut beams by stacking liquid crystal spiral phase plates. The interference of doughnut beam generated by LC spiral phase plate and plane wave has been studied. The numerical simulation results agree with the experiment.

Some work had been done in this paper to study the role of the fluence rate of the illuminating light in the photodynamic therapy (PDT), which focused on the influence of light fluence rate on the microvasculature damage, the cell killing and the photodynamic reaction impetus. The microvasculature damage was studied through observing the values of RBC's column diameter during the process of the HpD mediated PDT. It was found that less microvasculature damage was induced by 75 mW/cm² illumination than that by 150 mW/cm², indicating that under 75mW/cm² illumination tumor oxygen can be better preserved than 150 mW/cm². The cell killing experiment was performed in vitro and designed in the manner that cell killing rate was only influenced by photobleaching. Higher cell killing rate caused by 75 mW/cm illumination indicated that lower fluence rate light could enhance the light absorbency and decrease the bleaching of photosensitizer. So the cell-killing rate under low fluence rate was enhanced through the oxygen preservation and photobleaching decreasing.

In this paper, we have constructed an integrative fast photoacoustic (PA) imaging system for fast photoacoustic imaging, which includes a fiber, ultrasonic coupling medium, and a multi-element linear transducer array (MLTA). The PA signals were received by the MLTA in a reflection mode arid collected by a computer, reconstructed by limited-field filtered back projection algorithm. The PA images of different depth of phantom and animal blood vessels of different diameters were obtained. The lateral resolution of the system was 0.2mm. It would provide a new approach to tissue functional images in vivo and may have potentials in developing into an appliance for clinic diagnosis of disease.

Optoacoustic tomography can be applied into medical imaging, which can detect the light absorption distribution of target hidden inside scattering media. When a short laser pulse illuminates the optical turbid media, such as biological tissue, the media will generate ultrasound pulses, which is linearly proportional to the optical absorption of the media. The acoustic pressure distribution can be imaged with an acoustic lens. Similar to an optically imaging system, the optoacoustic signals from a plane in tissue require the same delay time to reach a detecting plane. While the optoacoustic signals from different planes in media require different delay time to reach an image plane. A BOXCAR was used to go on with the same delay-time, and a 64-element linear transducer array was one-dimensional scanned on an imaging plane, and thus the acoustic pressure distribution was acquired. The signals were recorded and reconstructed by a computer. By scanning the sampling gate of BOXCAR, the optoacoustic images of different planes in media could be obtained. The experimental result indicates that the system is able to obtain optoacoustic tomography images of targets hidden optical turbid media, and the reconstructed images agree well with the original samples. The results show that the lateral resolution is about 5mm and the axial resolution is about 1.5mm.

Photoacoustic tomography is a potential and noninvasive medical imaging technology. It combines the advantages of pure optic imaging and pure ultrasound imaging. We have explored photoacoustic imaging with different filters, such as RL, SL, Modi-SL arid Kwoh-Reed, which take important roles on reconstructed images. The results of simulations and experiments show that the filter of Kwoh-Reed can restrain noise effectively and improve the contrast of images compares with the filters of RL, SL, ModiSL in the presence of strong noise. A Q-switched Nd:YAG laser operating at 532nm was used as light source. The laser had a pulse width of 7ns and a repetition frequency of 30Hz. A needle PVDF hydrophone with diameter of I mm was used to detect photoacoustic signals.

This paper presents a novel model of photoacoustic tomography with an ultrasonic probe beam. A strict theory describes the nonlinear interaction between photoacoustic wave and ultrasonic probe beam. When a pulse laser irradiates on biological tissues, the laser energy will be absorbed by the identity molecule of the tissues, and be converted into heat. Subsequently, the thermal expansion of the instantaneously heated tissues induces photoacoustic waves. So the density, temperature and compressibility of the absorption area will be changed. A focus ultrasonic probe beam with a single frequency passes through the irradiated area, the changes of the properties of the irradiated medium will be coupled with the ultrasonic probe beam, which will propagate through the medium with minimal distortion and can be detected at the surface of the medium. The PA signal in situ can be obtained by demodulating the detected ultrasonic beam. It will take out much more information from the interaction area, which can reflect not only the intrinsic optical properties but also the mechanical and acoustical properties of the tissue. In our experimentation, a Q-switched Nd: YAG pulse laser operated at 1064nm was employed to generate photoacoustic signal, the frequency of ultrasonic probe beam is l0M. By demodulating the detected ultrasonic beam, we obtained very high quality tomography images. So it will provide a new promising method for tumour detection and noninvasion function imaging.

The major approach to photoacoustic imaging is the filtered back projection (FBP) algorithm, which is based on direct Fourier inversion. But the reconstruction with the FBP needs sufficient views to all points in the "detection region", it requires a quite long time to get enough data, which restricts the application in the medical field. In this paper, the limited-view photoacoustic imaging based on algebraic reconstruction techniques (ART) has been studied. A Q-switched Nd: YAG laser operating at 1064 nm was used as light source. The laser had a pulse width of 6ns and a repetition frequency of 20Hz. A needle PVDF hydrophone with diameter of 1mm was used to detect photoacoustic signals. Under the same condition, the simulations and experiments demonstrated that ART works well for limited-view data in photoacoustic imaging, and ART can improve the resolution and contrast of reconstruction images compared with the FBP algorithm.

In this paper, Influences of the acoustic path difference on photoacoustic (PA) images caused by mismatch of ultrasonic velocities were studied. We first proposed using the concentration-adjustable glycerite as an ultrasonic transmitting medium. By switching a appropriate concentration of the glycerite, it can make the velocities of the PA signals keep constant between transmitting medium and biological tissues, and avoid the acoustic path difference (APD) in image reconstruction. The experiments demonstrate that the acoustic path difference influences the imaging qualities badly: especially, the spatial resolution of PA image is extremely reduced. After matching ultrasonic velocity by glycerite the contrast of the reconstructed image is improved greatly and the background artifacts are reduced obviously. The spatial resolution of the reconstructed image is improved from 0.5mm to 0.15mm. It has great practical significance for applying photoacoustic tomography to noninvasive clinic diagnosis of cancer.

We developed a fast microwave-induced thermoacoustic tomography system based on a 320-element phase-controlled linear transducer array. A 1.2GHz microwave generator transmits microwave with pulse duration of 0.5 us and an incident energy density of 0.45 mJ/cm². Compared to single transducer collection, the system with multi-element linear transducer array can eliminate the mechanical rotation of the transducer, so can effectively reduce the image blurring and improve the image resolution. Using phase-controlled technique to collect thermoacoustic signals, the data need not be averaged because of the high signal-to-noise ratio, resulting in the total data acquisition time of less than 5 s. The system thus provide a rapid and reliable approach to thermoacoustic imaging. which can potentially be developed as a powerful diagnostic tool for early-stage breast caners.

Thermal imager can transfer difference of temperature to difference of electric signal level, so can be application to medical treatment such as estimation of blood flow speed and vessel 1ocation^[1], assess pain^[2] and so on. With the technology of un-cooled focal plane array (UFPA) is grown up more and more, some simple medical function can be completed with un-cooled thermal imager, for example, quick warning for fever heat with SARS. It is required that performance of imaging is stabilization and spatial and temperature resolution is high enough. In all performance parameters, noise equivalent temperature difference (NETD) is often used as the criterion of universal performance. 320 x 240 α-Si micro-bolometer UFPA has been applied widely presently for its steady performance and sensitive responsibility. In this paper, NETD of UFPA and the relation between NETD and temperature are researched. several vital parameters that can affect NETD are listed and an universal formula is presented. Last, the images from the kind of thermal imager are analyzed based on the purpose of detection persons with fever heat. An applied thermal image intensification method is introduced.

The overview of the Spectral Optical Coherence Tomography an alternative method to more popular Time domain modality is given. Examples from medical practice utilizing high resolution, ultra fast SOCT device are presented.

We developed a full-field OCT system using thermal light as the low-coherence light source. The whole system is combined with a commercial fluorescent microscope. A compact Linnik interferometnc adapter is designed as reference arm. Due to the broad spectral width of the thermal light, a sub micrometer axial resolution can be achieved for OCT imaging. As the acquisition rate of CCD is fast enough, real time OCT imaging can be achieved. The whole system is compact and robust, very suitable for biomedical applications.

This research work is part of research of plant image based modeling, which is a main research area in virtual plant. To modeling the plant, the first step is to make model for leafs. And to modeling leafs, the first step is to acquire its nervure structure. So, this thesis dissertate a plant leaf nervure structure acquiring system base on MS3100 3CCD image processing. By the 3CCD image system, three channel data (green, red and near-infrared) images were gotten. The image data were transferred to a host computer and were stored as files in TIFF format. With further image processing, we can get a relatively more clear vision of plant nervure image. By means of non-contact measuring method, main geometrical characteristic parameters of plant nervure can be acquired in image or grid format. This process includes the technologies such as imaging pre-processing, image binary-conversion, boundary encoding and so on. The second part is to establish the vector structure of the leaf nervure. The establishment of tree structure of the plant leaf nervure is mainly discussed. At last plant leaf nervure in vector format based on the multi-spectrum images gotten from 3CCD camera can be acquired.

The photoacoustic (PA) effect refers to the generation of acoustic waves by the modulated optical radiation. A novel tissue imaging technique, photoacoustic imaging is using the acoustic waves made in the PA effect to reconstruct the sample. It whose characteristic is combining the advantages of pure optical imaging and pure ultrasound imaging can map the high contrast and high spatial resolution tissue image. The PA imaging reconstmction algorithm performing the signal filtering operation first and then to reduce the signal data to the image, has the important influence on the quality of the image made by the experiment of PA. With the laser appearance in 1960s, the PA imaging technique made great advance and the reconstruction algorithm gains quick development. The prevalent PA reconstruction algorithms include Kruger's 3D inverse Radon transform, Frenz's Fourier transform, Lihong Wang's method based on the analytic solution. Nowadays, PA imaging technique develops to the real-time PA image. So to choose a suitable fast algorithm is significant to the PA imaging system's application. We will review the current PA imaging reconstruction algorithm and compare them in the aspect of the tissue imaging spatial resolution and so on.

Photo-acoustic tomography(PAT) is a new ultrasound-mediated biomedical imaging technology which combines the advantages of high optical contrast and high ultrasonic resolution. In theory, PAT can image object embedded several centimeters under the surface of sample with the resolution of tens of microns. In this paper, several representative image reconstruction algorithms are discussed. Because the PA signal is wide band signal, it is hard to get the whole frequency spectrum due to the tremendous calculation needed. Therefore, the most applicable reconstruction algorithms are all performed in time domain such as "delay-and-sum" and "back projection". The current research methods have been focused on optical detecting and piezoelectric detecting. The optical method has the advantage of high spatial sensitivity due to the short wavelength of the probe laser beam. PA signal detecting using piezoelectric sensor has two main modes i.e. using unfocused transducer or transducer array or using focused transducer array or linear transducer array. When a focused transducer array is used, the "delay-and-sum" method is often used for image reconstruction. The advantage of the method is that its data acquisition time can be reduced to several minutes or even several seconds by employing the phase control linear scan technique. The future development in PAT research and its potential clinic application is also presented.

Spectral OCT (SOCT), with high acquisition speed and high dynamic range, has been implemented by many research groups in the world. However, SOCT image inherently has virtual image, including auto-correlation noise and mirror image. The existence of the virtual image may deteriorate the quality of the image. In order to eliminate those virtual images, some methods have been demonstrated effective, such as differential SOCT and complex SOCT. In this paper, a novel method is proposed i.e. three-phase shifting method. The pathlength of the reference arm is changed for certain distance by PZT controller. Three phase shifted coherence spectra are recorded for A-line. The reconstruction algorithm can eliminate both auto-correlation noise and minor image, thus improve the signal-to-noise ratio of the SOCT image. Furthermore, this method is also able to amplify the measuring range of SOCT by a factor of 2. An intact porcine cornea tissue in vitro is further used to show the potential of this method for high-resolution biological imaging.

Noninvasive photoacoustic tomography (PAT) is a novel technique with great potential in biomedical image applications for it combines the merits and most compelling features of light and sound, and has the advantages of providing high contrast and high resolution images in moderate depth below the surface. When the image depth is on the scale of centimeter, the millimeter-scale resolution images still can be obtained. Thus it is a powerful tool for the early-stage breast cancer sensing. In this paper, photoacoustic tomography is studied by using the simulation method. The results show that: (1) the contrast of image increases linearly with respect to the number of measurement position (NMP); (2) the contrast increases exponentially with respect to noise-to-signal ratio.

Polarization sensitive optical coherence tomography (PS-OCT) is a new non-contact and non-invasive method for measuring the change of birefringence in biological tissues caused by pathological changes of body. It has great potential in imaging the structural properties of turbid biological media because the polarization state of light backscattered from biological tissues is influenced by the birefringence of fibrous structures. The arrangement is based on a Michelson interferometer with use of quarter-wave plates and polarimeter. Through the detection of light backscattered from biological tissues and reflected from a reference mirror, the optical phase delay between orthogonal polarization compositions propagating in the birefringence media can be measured. PS-OCT is a powerful tool for research of tendon, dentin, lesions, which have strong polarization effective. We in this paper describe the experimental scheme and its mathematical representation, along with the theory of PS-OCT imaging. Besides, we introduce a fiber-based PS-OCT system for measuring the tissue birefringence.

We have built up two sets of THz generation and detection system. One uses the photoconductor antenna as the THz emitter, which can generate a stronger THz electromagnetic radiation. Its spectral range is relative narrow 0.1 - 1.1 THz, so it is suitable to the application of THz imaging. Another uses a femto-second laser pulse to excite semiconductor surface and generates the broadband THz radiation with the spectral range between 0.2 THz and 3.0 THz, which is suitable for the study on THz time resolved spectroscopy. Both of the THz setups utilize the detection technology of free-space electro-optic sampling, and realize the experimental function of low noise, high sensitivity high signal-to-noise ratio and very large of dynamical range. The signal-to-noise ratio of our system achieve at above 600. The dynamical range is 10⁴. Therefore, our setup provides a strong experimental basis for THz spectroscopy and imaging, and is ready to study on the application of THz optics, THz chemistry, material science, biology and medicine.

Crosstalk between changes in concentration of oxy-and deoxy-haemoglobin calculated by modified Lambert-Beer law in near-infrared topography is theoretically investigated. The change in intensity detected with source-detector pairs on the scalp caused by global or focal ahsorption change in the brain is predicted by Monte Carlo simulation. The topographic images of changes in oxy- and deoxy-haemoglobin are obtained from the changes in intensity detected with source-detector pairs on the scalp. The crosstalk depends on the relative position of the focal absorption change to source-detector pairs. The crosstalk is minimised when the focal absorption change is located below a measurement point that is the midpoint between a source and a detector.

Since x-ray was discovered and applied to the imaging technology, the x-ray imaging techniques have experienced several improvements, from film-screen, x-ray image intensifier, CR to DR. To store and transmit the image information conveniently, the digital imaging is necessary for the imaging techniques in medicine and biology. Usually as the intensifying screen technique as for concerned, to get the digital image signals, the CCD was lens coupled directly to the screen, but which suffers from a loss of x-ray signal and resulted in the poor x-ray image perfonnance. Therefore, to improve the image performance, we joined the brightness intensifier, which, was named the Low Light Level (LLL) image intensifier in military affairs, between the intensifying screen and the CCD and designed the novel x-ray imaging system. This design method improved the image performance of the whole system thus decreased the x-ray dose. Comparison between two systems with and without the brightness intensifier was given in detail in this paper. Moreover, the main noise source of the image produced by the novel system was analyzed, and in this paper, the original images produced by the novel x-ray imaging system and the processed images were given respectively. It was clear that the image performance was satisfied and the x-ray imaging system can be used in security checking and many other nondestructive checking fields.

Near Infrared Spectroscopy (NIRS) has been widely used to access the brain functional activity non-invasively. A portable, multi-channel, continuous-wave (CW) NIR topography instrument we designed to measure the concentration changes of each hemoglobin species and map cerebral cortex functional activation. The probe of instrument consists of 4 LEDs operating at three-wavelength (735 nm & 805 nm & 850 nm) surrounded with 10 photodiodes mounted on a flexible PCB with the interoptode distance up to 2.88cm. On the basis of the modified Beer-Lambert law, the ratios of optical density changes in a ftilly oxygenated and deoxygenated state are determined by varying blood volume and hemoglobin oxygenation state in model experiment. The average ratios are 0.56. 1.74 and 0.45. Additionally, study on the phantoms is carried out to investigate the penetration depth (13 mm) of the sensor array.

This paper describes a digital rat alias of sectional anatomy made by milling. Two healthy Sprague-Dawley (SD) rat weighing 160-180 g were used for the generation of this atlas. The rats were depilated completely, then euthanized by Co₂. One was via vascular perfusion, the other was directly frozen at -85 °C over 24 hour. After that, the frozen specimens were transferred into iron molds for embedding. A 3% gelatin solution colored blue was used to fill the molds and then frozen at -85 °C for one or two days. The frozen specimen-blocks were subsequently sectioned on the cryosection-milling machine in a plane oriented approximately transverse to the long axis of the body. The surface of specimen-blocks were imaged by a scanner and digitalized into 4,600 x2,580 x 24 bit array through a computer. Finally 9,475 sectional images (arterial vessel were not perfused) and 1,646 sectional images (arterial vessel were perfused) were captured, which made the volume of the digital atlas up to 369.35 Gbyte. This digital rat atlas is aimed at the whole rat and the rat arterial vessels are also presented. We have reconstructed this atlas. The information from the two-dimensional (2-D) images of serial sections and three-dimensional (3-D) surface model all shows that the digital rat atlas we constructed is high quality. This work lays the foundation for a deeper study of digital rat.

Recently optical techniques have been applied to the biomedical areas such as diagnostics, imaging etc. However, light scattering in biological tissues can dramatically degrade the imaging contrast and reduce the probe depth. Polarization based measurement have shown its advantages in overcoming such drawbacks. In this work, we achieved a contrast enhancement in subsurface optical imaging by changing the incident polarization states between linear and circular polarizations. Contrasts of the comb like metal target submerged in Intralipid solutions are measured quantitatively as functions of the Intralipid concentration and the submersion depths. Different behaviors in contrast for linear and circular polarizations are compared. Contributions to the background of circular polarization degree images by backscattering, snake and diffusive photons are examined.

The internal quality of tomato such as acidity and sugar content is important to its taste thus influences the market. The objective of this paper was to demonstrate the feasibility of using a near-infrared spectroscopy (NIRS) to investigate the relationship between sugar content and acidity of tomato and absorption spectra. The N1RS reflectance of nondestructive tomatoes was measured with a Visible/NJR spectrophotometer in 325-1075 nm range. The sugar content and acidity of tomato were obtained with a handhold sugar content meter and a PH meter. The reflectance data set was recorded and analyzed with some mathematic methods. The PLS (Partial least squares) calibration method was developed for converting the NIRS reflectance of tomato into the data which determined the acidity value. BP (Back propagation) neural network was used to set up the relationship between the NIRS reflectance of tomato and sugar content. The acidity values were detected with an accuracy of 9O% and the sugar contents determined by the BP network were also very close to the measurements (coefficient of correlation r²=0.8764). NW spectra analysis would be very useful in the nondestructive internal quality inspecting of tomato.

An immunochromatographic assay (ICA) system for quantitative determination of analyte in sample is described in this paper. The designed system not only quantitatively detect target analytes in sample but also enhance detection precision in immunochromatographic assay technique.

Extracting light that has maintained its original polarization state can be used to improve the image resolution in imaging or localize the volume probed in spectroscopy. This paper describes polarization dependent instrumentation and modelling methods used in the imaging and spectroscopy of scattering media. The use of integrated optical sensors in imaging the polarization difference signal is also demonstrated.

Spectral imaging of the retina shows great promise for the early detection of retinal disease through retinal screening programs. Implementation of such a program will require instrumentation capable of efficiently recording the requisite spectral data cube. We report on the development of two candidate approaches: one employs a traditional liquid crystal tunable filter to filter the illumination source and enable the spectral data cube to be assembled from mutually coregistered narrow-band images recorded in time sequence: the second employs, IRIS, a novel image replicating imaging spectrometer to record a two-dimensional spectral data cube in a single snapshot.

We present a multi-dimensional TCSPC technique that simultaneously records the photon distribution over the time in the fluorescence decay, the wavelength, and the coordinates of a two-dimensional scan or the time since the start of the experiment. We demonstrate the application of the technique to diffuse optical tomography, single-point autofluorescence measurements of skin, and multi-spectra autofluorescence lifetime imaging of tissue.

Equine articular cartilage has been imaged using both polarization-sensitive optical coherence tomography (PS-OCT) and non-linear microscopy. PS-OCT has been used to spatially map the birefringence in the cartilage and we have found that in the vicinity of the lesion the images display a characteristic disruption in the regular birefringence bands shown by normal cartilage. We also note that significant (e.g. x2) variations in the apparent birefringence of samples taken from young (18 month) animals that otherwise appear visually homogeneous are found over spatial scales of a few millimeters. We have also imaged the cartilage using non-linear microscopy and compare the scans taken with second harmonic generation (SHG) light and the two photon fluorescence (TPF) light. SHG images collected using 800 nm excitation reveals the spatial distribution of collagen fibers, whilst TPF images clearly shows the distribution of intracellular and pericellular fluorophores.

Our recent DOT experiments on human lower legs and forearms are presented using the time-resolved measuring system and image reconstruction algorithm based on the modified generalized pulse spectrum technique. It was shown that the the spatial resolution and quantitativeness of the resultant images, including, was rather poor, and the interior blood vessels invisible in the absorption images. To clarify this issue, the influences of target contrast and size on the image reconstruction were investigated with simulated data. We have found that the quantitativeness of the reconstructed optical properties was prone to be spoiled by the small size ratio and high contrast of the interior targets to the background and the incompleteness of information embedded in the featured data-types, evidently answers for the degradation of the image quality. It was shown in a further simulative investigation that the image quality could be substantially improved by making full use of the time-resolved data.

Infrared and visual images are the two formats of a same image that to be identified in the gate control system. The infrared image is the reflection of the facial temperature feature, and the interferential signals such as the light can be removed in the image manipulation. The combination of the infrared image and the visual image increase the accuracy in the identification system. The mathematic arithmetic of the image manipulation for the facial features identification is suitable for both formats. The method of the identification is the pixels comparison. A facial image inputted from the video collection device is converted into an array of pixels in the identification system. The pixels that contain parts of the whole facial features are compared with those in an image database. Each of the infrared image and the visual image is calculated accordingly. In terms of the accordant degree of the two calculation results, the system can judge that whether the face belongs to a person in the database or not. Accordingly, the output signal can control the gate open or not.

We report the implementation of compound imaging with backward second harnionic generation (SHG) and two-photon excitation fluorescence (TPEF) in a standard confocal microscope. Various biological tissues, including skin, muscle and ocular tissues (e.g. cornea. iris, choroid, and sclera) have been investigated with different sample preparation methods (fresh, fixation). The results show that collagen-rich ocular tissues, like cornea, iris, choroids, and sclera can produce strong SHG signals. In sclera, there are not only plenty of collagen, but also various endogenous fluorophores. The organization of collagen fibers in sclera is clearly distinguishable from its SHG images viewed transversely and horizontally respectively. We also find that fixation of the sample with formaldehyde has reduced the intensity of SHG intensity by almost 5O%. As the SHG and TPEF can provide complementary information about collagen and fluorophores rich biological tissues, compound imaging of SHG and TPEF presented in this study is believed to have potential applications in biomedicine and clinical diagnosis.

The direct problem of noninvasive optical biomedical diagnostics based on laser probing is considered. Light propagation in tissue is described by the radiative transfer equation. A grid algorithm using an analytical representation of the non-scattered radiation and a semi-analytical method for calculating the single scattered radiation intensity is presented. The direct solution of the radiative transfer equation is compared with the experimental data, Monte-Carlo simulation results and the diffusion approximation solution. The proposed algorithm has advantages in terms of accuracy and lower calculation time.

This paper discusses the principle and implementation method of Ray-casting volume rendering algorithm. In order to enhance the image quality and speed of alternate operation, we improve the grads formula in Ray-casting volume rendering algorithm and compound method of the sampling points.

In this paper, we present a new image segmentation algorithm based on the concept of two-dimensional Renyi's entropy along with statistical variance from the assumed data sets of object and the background to produce the appropriate threshold. So the statistic infonnation, or relative spatial distribution, or co-occurrence, of pixel grey levels, was taken into account. Experimental results show that the method we proposed performed better than one-dimensional and two-dimensional entropy-based methods with lower segmentation errors, and a reduction in the amount of noise present in the resultant images. This method can be extended to any other entropy segmentation method based on two-dimensional gray histogram and may also be useful for pattern recognition and image sequence analysis. Especially when the gray value of the object and the background overlap greatly or there is big noises in the image, the segmentation result can be drastically improved.

An increasing number of medical imagery is created directly in digital form. Such as Clinical image Archiving and Communication Systems (PACS), as well as telemedicine networks require the storage and transmission of this huge amount of medical image data. Efficient compression of these data is crucial. Several lossless and lossy techniques for the compression of the data have been proposed. Lossless techniques allow exact reconstruction of the original imagery, while lossy techniques aim to achieve high compression ratios by allowing some acceptable degradation in the image. Lossless compression does not degrade the image, thus facilitating accurate diagnosis, of course at the expense of higher bit rates, i.e. lower compression ratios. Various methods both for lossy (irreversible) and lossless (reversible) image compression are proposed in the literature. The recent advances in the lossy compression techniques include different methods such as vector quantization. Wavelet coding, neural networks, and fractal coding. Although these methods can achieve high compression ratios (of the order 50:1, or even more), they do not allow reconstructing exactly the original version of the input data. Lossless compression techniques permit the perfect reconstruction of the original image, but the achievable compression ratios are only of the order 2:1, up to 4:1. In our paper, we use a kind of lifting scheme to generate truly loss-less non-linear integer-to-integer wavelet transforms. At the same time, we exploit the coding algorithm producing an embedded code has the property that the bits in the bit stream are generated in order of importance, so that all the low rate codes are included at the beginning of the bit stream. Typically, the encoding process stops when the target bit rate is met. Similarly, the decoder can interrupt the decoding process at any point in the bit stream, and still reconstruct the image. Therefore, a compression scheme generating an embedded code can start sending over the network the coarser version of the image first, and continues with the progressive transmission of the refinement details. Experimental results show that our method can get a perfect performance in compression ratio and reconstructive image.

Wavelets have been widely used in signal and image processing for the past 20 years. In this paper, we present an overview of the various methods of the wavelet transform in medical image fusion. Using wavelet transform, we presented a general image fusion scheme involves decomposition of the input images, calculation of the wavelet transform modulus, fusion strategy, and reconstruction for new fusion image. Next we provide a survey of recent wavelet developments in medical image fusion. In each case, we provide the reader with some general background information and a brief explanation of how the methods work.

In this paper, we propose a new Wavelet-domain Hidden Markov Model (WHMM) for image denoising, which can exploit the local statistics and also capture intra-scale dependencies of the wavelet coefficients. Firstly, a Gaussian Mixture Field (GMF) on the wavelet transform is developed. In the GMF, we assume each wavelet coefficient follows a local Gaussian Mixture Model (GMM) which is determined by its own neighborhood. The GMF contains rich local statistics of wavelet coefficients, which can be further combined with the contextual WHMM (CWHMM) to capture inter-scale or intra-scale dependencies. Based on our numerous simulation results, we find that the combination of the GMF and the inter-scale CWHMIM performs better than the combination of the GMF and the intra-scale CWHMM. We also notice that there is no significant benefit to consider both the inter-scale and intra-scale dependencies together in the GMF. Therefore, for the simplification of implementation, we consider the combination of the GMF and the intra-scale CWIHMM and name the novel model Gaussian Mixture Field Wavelet-domain Hidden Markov Model (GMFWWVIIM) in this work. The newly proposed GMFWHMM allows more accurate image modeling with improved denoising performance at the low computational complexity. Finally, the novel model is applied to medical image denoising with interesting results.

In many applications of image processing, the observed image can be considered as a convolution of the original image and the point spread function (PSF) of the observation instruments. The operation to obtain the original image from the observed image is called deconvolution. We have more interests in the case named blind deconvolution that the PSF is not known in advance. Based on kurtosis extrema, we develop an algorithm of blind deconvolution. Several experiments on the micrograph and astronomy images demonstrate its feasibility. This is a universal image blind deconvolution method, and can be applied to many image blind deconvolution areas.

Level set methods provide powerful numerical techniques for analyzing and solving interface evolution problems based on partial differential equations. Level sets display interesting elastic behaviors and can handle topological changes. Although level set methods have many advantages, they still often face difficult challenges such as poor image contrast, noise, and missing or diffuse boundaries. The robust level set method of this paper is based on the anisotropic diffusion method. The fast marching method provides a fast implementation for level set methods, the anisotropic diffusion is allowed to better control the amount of smoothing effect and this process can get both noise smoothing and edge enhancement at the same time. Experimental results indicate that the method can greatly reduce the noise without distorting the image and made the level set methods more robust and accurate.

This paper describes a new neural network model that performs color image segmentation in an unsupervised manner. The new scheme is called enhancing learning algorithm on the radial basis function neural network (ERBF). First, ERBF employs a dynamic nearest neighbor-clustering algorithm to set its front two layers: the input layer and the hidden layer. Second, ERBF network introduces the Hebb rule to train the hidden layer and divide the hidden neurons center vectors into two meaningful groups: one group members are the target color-clustering centers; the other group members are the background color-clustering centers. Finally, the ERBF output layer is trained by the competitive algorithm and outputs different values with different input values so as to divide the target region from the image. The present model avoids the trouble in deciding the hidden nodes number beforehand and needs only to be trained twice. This new color image segmentation scheme has been implemented and tested on medical color images. The results shown that the new segmentation scheme is proved to be an effective segmentation algorithm.

Selective application of herbicide to weeds at an earlier stage in crop growth is an important aspect of site-specific management of field crops. For approaches more adaptive in developing the on-line weed detecting application, more researchers involves in studies on image processing techniques for intensive computation and feature extraction tasks to identify the weeds from the other crops and soil background. This paper investigated the potentiality of applying the digital images acquired by the MegaPlus^TM MS3100 3-CCD camera to segment the background soil from the plants in question and further recognize weeds from the crops using the Matlab script language. The image of the near-infrared waveband (center 800 nm; width 65 nm) was selected principally for segmenting soil and identifying the cottons from the thistles was achieved based on their respective relative area (pixel amount) in the whole image. The results show adequate recognition that the pixel proportion of soil, cotton leaves and thistle leaves were 78.24%(-0.20% deviation), 16.66% (+ 2.71% SD) and 4.68% (-4.19% SD). However, problems still exists by separating and allocating single plants for their clustering in the images. The information in the images acquired via the other two channels, i.e., the green and the red bands, need to be extracted to help the crop/weed discrimination. More optical specimens should be acquired for calibration and validation to establish the weed-detection model that could be effectively applied in fields.

This paper presents a methodology for high resolution image classification and segmentation. The size and information volume of the images, taken by a high resolution digital camera, will be tens to hundreds times as the ones taken by an ordinary CCD camera. In order to speed up the image segmentation process of the large images, we classify the images first by using a low resolution image, then, segment them by a fast segmentation algorithm. The algorithm is studied mainly based on multi-resolution technique and the fusion of edge detection result and similarity segmentation result. By using this methodology, the whole image segmentation process time is reduced by tens' times than traditional segmentation methods, and the accuracy of the image segmentation is not decreased.

This paper presents the utilization of laser data for image processing and analysis, especially for image segmentation. Recently a number of researchers tried different ways to make fusion of the two types of segmentation algorithms, and make processing procedure more complicated, but the detection results still cannot be guaranteed. As an alternative, when images are taken by a laser scanner, the laser image data will be very useful for overcoming the above problem. To analyze the form and shape of an object on a laser image, edge based segmentation tecimique is applied for the main contour detection of an object. In the detection, the extra information of the laser data (third dimensional information) for image segmentation algorithms is used, and the testing results are satisfactory.

2-D electrophoresis gel images can be used for identifying and characterizing many forms of a particular protein encoded by a single gene. Conventional approaches to gel analysis require the three steps: (1) Spot detection on each gel; (2) Spot matching between gels; and (3) Spot quantification and comparison. Many researchers and developers attempt to automate all steps as much as possible, but errors in the detection and matching stages are common. In order to carry out gel image analysis, one first needs to accurately detect and measure the protein spots in a gel image. This paper presents the algorithms for automatically delineating gel spots. The fusion of two types of segmentation algorithms was implemented. One is edge (discontinuity) based type, and the other is region based type. The primary integration of the two types of image segmentation algorithms have been tested too, the test results clearly show that the integrated algorithm can automatically delineate gel spots not only on a simple image and also on a complex image, and it is much better that either only edge based algorithm or only region based algorithm. Based on the testing and analysis results, the fusion of edge information and region information for gel image segmentation is good for this kind of images.

The paper proposes an antetype matching algorithm in Fourier Transform domain (AMFT), which is robust against geometrical changes in time domain. We present several methods to eliminate the geometry interferences induced by the limited changes of objects, such as shift, amplitude, scale, rotation and their combination in time domain: (1) Using the Time-shifting property of Fourier Transform. To eliminate the time shifting of signal, (2) normalizing the disturbance out of signal intensity with auto-correlativity operation, (3). The scale factor in time-domain being transformed to time shifting with semi-logarithm operation, (4) constructing a energy distribution function to keep the correlation between the antetype and a target and eliminate the interference induced by rotating the larget. The experimental results show that the geometrical changes of targets can efficiently be rid of during matching processes with a constant prototype using this algorithm.

Medical imaging has started to take advantage of digital technology, opening the way for advanced medical imaging and teleradiology. Medical images, however, require large amounts of memory. At over 1 million bytes per image, a typical hospital needs a staggering amount of memory storage (over one trillion bytes per year), and transmitting an image over a network (even the promised superhighway) could take minutes--too slow for interactive teleradiology. This calls for image compression to reduce significantly the amount of data needed to represent an image. Several compression techniques with different compression ratio have been developed. However, the lossless techniques, which allow for perfect reconstruction of the original images, yield modest compression ratio, while the techniques that yield higher compression ratio are lossy, that is, the original image is reconstructed only approximately. Medical imaging poses the great challenge of having compression algorithms that are lossless (for diagnostic and legal reasons) and yet have high compression ratio for reduced storage and transmission time. To meet this challenge, we are developing and studying some compression schemes, which are either strictly lossless or diagnostically lossless, taking advantage of the peculiarities of medical images and of the medical practice. In order to increase the Signal to Noise Ratio (SNR) by exploitation of correlations within the source signal, a method of combining differential pulse code modulation (DPCM) is presented.

It is difficult to get high compression ratio and good reconstructed image by conventional methods; we give a new method of compression on medical image. It is to decompose and reconstruct the medical image by wavelet packet. Before the construction the image, use neural network in place of other coding method to code the coefficients in the wavelet packet domain. By using the Kohonen's neural network algorithm, not only for its vector quantization feature, but also for its topological property. This property allows an increase of about 80% for the compression rate. Compared to the JPEG standard, this compression scheme shows better performances (in terms of PSNR) for compression rates higher than 30. This method can get big compression ratio and perfect PSNR. Results show that the image can be compressed greatly and the original image can be recovered well. In addition, the approach can be realized easily by hardware.

This paper presents that (1) to apply image processing technique into lung tissue information recognition, the key and hardest task is to auto-detecting lung tissue details on the X-ray images; and (2) the newly developed ridge detection algorithm is very powerful for detecting lung tissue, it has been tested not only for regular lung tissue images and also for irregular lung tissue images. The algorithm has been compared to some traditional image segmentation algorithms. All the test results show that it works satisfactory for lung tissue images.

To recognize the characteristics of coiony images, an important step is to segment colony images (delineate colonies). Therefore, an algorithm based on kernel spatial FCM (fuzzy c-means) is studied for colony images, presented in this paper. When conventional fuzzy c-means clustering algorithm is used to segment colony images, spatial information is not considered, and Euclidean distance calculation in such an algorithm is not robust. In this paper, we consider the spatial information when colony images are deal with, by using MCF. By using Mercer kernel functions, image pixels are mapped from the original space into a higher dimensional feature space. We can perform c-means clustering efficiently in the feature space for the kernel functions, which can induce robust distance measures while the computational complexity is low. We conduct some experiments on colony images by using the new algorithm. The results show that the studied algorithm is suitable and robust for colony images segmentation.

This research aimed to identify weeds from crops in early stage in the field operation by using image-processing technology. As 3CCD images offer greater binary value difference between weed and crop section than ordinary digital images taken by common cameras. It has 3 channels (green, red, ifred) which takes a snap-photo of the same area, and the three images can be composed into one image, which facilitates the segmentation of different areas. By the application of image-processing toolkit on MATLAB, the different areas in the image can be segmented clearly. As edge detection technique is the first and very important step in image processing, The different result of different processing method was compared. Especially, by using the wavelet packet transform toolkit on MATLAB, An image was preprocessed and then the edge was extracted, and getting more clearly cut image of edge. The segmentation methods include operations as erosion, dilation and other algorithms to preprocess the images. It is of great importance to segment different areas in digital images in field real time, so as to be applied in precision farming, to saving energy and herbicide and many other materials. At present time Large scale software as MATLAB on PC was used, but the computation can be reduced and integrated into a small embed system, which means that the application of this technique in agricultural engineering is feasible and of great economical value.

Optical Coherence Tomography (OCT) has been developed for more than one decade. With the optimum of system configuration such as light source, the imaging elements, the imaging quality has been improved to a higher level. However, many ideal assumptions including dispersion cancellation. in the study of OCT system have become inapplicable. Actually, dispersion, can lead to a wavelength dependent phase distortion in sample arm, and finally result in a degrading in image resolution. Therefore, many dispersion compensation methods have been presented by researchers to correct the distorted image. In this paper, the principle of dispersion in OCT imaging system is discussed, and we demonstrate how it affects image quality. Then, with respect to the compensation methods as our knowledge, we classify them into hardware compensation and software compensation and present the detailed procedures and their characteristics, respectively. At last, a detailed discussion has been made to conclude that novel algorithms which can perform higher order compensation with depth variant are necessary and uniform evaluating criteria as well.

Medical image processing has been investigated for more than three decades. It is clear that medical imaging will still play a very dominant role in clinical research as well as in the daily routine practice in the coming decade. For a number of reasons the images obtained by the medical instruments itself, such as CT, MRI are insufficient for the efficient performance of a surgical intervention and various image processing techniques are necessary in order to make the most important features more easily visible. Owing to its rapidly increasing popularity over last few decades, the wavelet transform has become quite a standard tool in numerous image research and application domains. Wavelet thresholding has been a popular technique for image denoising. The basic principle of wavelet thresholding is to identify and zero out wavelet coefficients of a signal which are likely to contain mostly noise. By preserving the most significant coefficients, wavelet thresholding preserves important highpass features of a signal such as discontinuities. Here we used this technology in medicine image denoising and resulted in quite satisfying result. The goal of the medical image denoising in a broad sense is the research, implementation, and validation of image processing approaches. Research is carried out among others medical application areas.

The basidiomycetes Thelephora ganbajun Zang and Termitomyces albuminosus (Berk.) Heim are two of the most favorite edible mushrooms in Yunnan Province, Southwest of China. In this paper, Fourier transform infrared speciroseopy (FTIR) was used to characterize the fruiting bodies of the two wild growing edible mushrooms. The results show that each mushroom has its characteristic infrared spectrum, in which the major peaks are attributed to proteins and polysaccharides. The spectra indicate that the poiysaccharides of the two mushrooms contain, both. α- and β-glycosidic linkage. A characteristic band of Thelephora ganbajun is an obvious band at about 1763 cm^-1, which indicates that the mushroom contain oil. Differences are observed in the spectra of different parts of the fruiting body of Termitomyces albuminosus. According to the differences of the characteristic spectra peaks and absorbance ratios, the different parts of mushroom can be discriminated. The results suggest that the different species of mushrooms might be identified by the vibrational spectral features of the different parts of the fruiting bodies of mushrooms.

Amanita is one of cosmopolitan genera of basidiomycetes. This genus contains some of the most poisonous toadstools, as well as several species of the most favorite edible mushrooms. In this paper, Fourier transform infrared spectroscopy was used for obtaining vibrational spectra of the fruiting bodies of wild growing Amanita mushrooms. The results show that the mushrooms exhibit characteristic spectra, whose strong absorption bands appear at about 1655, 1076, and 1040 cm^-1. The vibrational spectra indicate that the main compositions of the Amanita mushrooms are proteins and polysaccharides. The observed spectral differences might be used to discriminate different species of Amanita. It is showed that FTIR spectroscopic method is a valuable tool for rapid and nondestructive identification of Amanita mushrooms.

In this paper, some key techniques on development of on-line MR urine analyzing system based on AOTF (Acousto - Optics Tunable Filter) are introduced. Problems about designing the optical system including collimation of incident light and working distance (the shortest distance for separating incident light and diffracted light) are analyzed and researched. DDS (Direct Digital Synthesizer) controlled by microprocessor is used to realize the wavelength scan. The experiment results show that this MR urine analyzing system based on. AOTF has 10000 - 4000cm^-1 wavelength range and O.3ms wavelength transfer rate. Compare with the conventional Fourier Transform NIP. spectrophotometer for analyzing multi-components in urine, this system features low cost, small volume and on-line measurement function. Unscrambler software (multivariate statistical software by CAMO Inc. Norway) is selected as the software for processing the data. This system can realize on line quantitative analysis of protein, urea and creatinine in urine.

The purpose of present study is to determine and compare the optical properties of normal human pulmonary artery tissue in vitro at 650, 680, 710, 740, 780 nm wavelengths of Ti:Sapphire laser. The optical parameters of tissue samples were determined using a double integrating sphere set-up. The inverse Adding-doubling method was used to determine the optical properties from the measurements. The results of measurement showed that the absorption coefficients for pulmonary arteries increase with increase of laser wavelength, the maximum absorption coefficient is 0.277 mm^-1 at 780 nm, and the minimum absorption coefficient is 0.160 mm^-1 at 650nm, and the reduced scattering coefficients for pulmonary arteries increase with decrease of laser wavelength, the maximum reduced scattering coefficient is 48.8 mm^-1 at 650 urn, and the minimum reduced scattering coefficient is 13.3 mm^-1 at 780 nm. The optical penetration depths for pulmonary arteries increase with increase of laser wavelength, the maximum optical penetration depth is 0.298 mm at 780 nm, and the minimum optical penetration depth is 0.206 mm at 650 nm. The backscattered reflectances for normal human pulmonary arteries increase with decrease of laser wavelength, the maximum backscattered reflectance is 0.794 at 650 nm, and the minimum backscattered reflectance is 0.561 at 780 nm.

Noninvasive determination of tissue optical properties is essential for clinical applications in medical diagnostics and therapeutics. In recent years, several methods were successfully introduced to deduce the optical properties of semi-infinite tissue model from spatially resolved (SR) diffuse reflectance. However, biological tissue is in fact not homogeneous and usually exhibits a complicated layered structure. The previous methods are not always efficient for the layered-structure tissue model. In this paper, we introduced a new method to determine the optical properties of the two-layer medium from the steady-state spatially resolved diffuse reflectance, which is based on the theory of support vector machine (SVM). The method was validated using the Monte Carlo algorithm generated reflectance from a two-layer model that consists of a 5mm thick top layer and a semi-infinite bottom layer. The training and predicting time of SVM are 20s and 5s respectively. The predictive errors of the proposed method were less than 2% for the top-layer optical properties and less than 4% for the bottom-layer optical properties, showing that the SVM method has a higher accuracy and a shorter training time comparing with other methods. The principle to deal with regression estimation problems with SVis briefly introduced firstly. Then, the phantom experiment set and the results are described. In the end, some limitations and strategies are also discussed.

A new approach for discrimination of varieties of yogurt by means of VisINTR-spectroscopy was present in this paper. Firstly, through the principal component analysis (PCA) of spectroscopy curves of 5 typical kinds of yogurt, the clustering of yogurt varieties was processed. The analysis results showed that the cumulate reliabilities of PC1 and PC2 (the first two principle components) were more than 98.956%, and the cumulate reliabilities from PC1 to PC7 (the first seven principle components) was 99.97%. Secondly, a discrimination model of Artificial Neural Network (ANN-BP) was set up. The first seven principles components of the samples were applied as ANN-BP inputs, and the value of type of yogurt were applied as outputs, then the three-layer ANN-BP model was build. In this model, every variety yogurt includes 27 samples, the total number of sample is 135, and the rest 25 samples were used as prediction set. The results showed the distinguishing rate of the five yogurt varieties was 100%. It presented that this model was reliable and practicable. So a new approach for the rapid and lossless discrimination of varieties of yogurt was put forward.

In order to reduce the interference of the individual discrepancy in the noninvasive measurement of blood composition, a new MR spectroscopy- dynamic spectroscopy is put forward and a new near infrared spectrometer is developed for the dynamic spectroscopy. Experiments indicated that the dynamic spectroscopy can reduce the interference of individual discrepancy well.

This work is aim to present a new approach for discrimination of varieties of tea by means of infrared spectroscopy (NIRS) (325-1075nm). The relationship has been established between the reflectance spectra and tea varieties. The data set consists of a total of 150 samples of tea. First, the spectra data was analyzed with principal component analysis. It appeared to provide the reasonable clustering of the varieties of tea. PCA compressed thousands of spectral data into a small quantity of principal components and described the body of spectra the scores of the first 6 principal components computed by PCA had been applied as inputs to a back propagation neural network with one hidden layer. 125 samples of five varieties were selected randomly, which were used to build BP-ANN model. This model had been used to predict the varieties of 25 unknown samples; the residual error for the calibration samples is 1.267 x 10^-4. The recognition rate of 100% was achieved. This model is reliable and practicable. So this paper put forward a new method to the fast discrimination of varieties of tea.

A fast measurement of pH of yogurt using Vis/NIR-spectroscopy techniques was established in order to measuring the acidity of yogurt rapidly. 27 samples selected separately from five different brands of yogurt were measured by Vis/NIR-spectroscopy. The pH of yogurt on positions scanned by spectrum was measured by a pH meter. The mathematical model between pH and Vis/NIR spectral measurements was established and developed based on partial least squares (PLS) by using Unscramble V9.2. Then 25 unknown samples from 5 different brands were predicted based on the mathematical model. The result shows that The correlation coefficient of pH based on PLS model is more than 0.890, and standard error of calibration (SEC) is 0.037, standard error of prediction (SEP) is 0.043. Through predicting the pH of 25 samples of yogurt from 5 different brands, the correlation coefficient between predictive value and measured value of those samples is more than 0918. The results show the good to excellent prediction performances. The Vis/NIR spectroscopy technique had a significant greater accuracy for determining the value of pH. It was concluded that the VisINIRS measurement technique can be used to measure pH of yogurt fast and accurately, and a new method for the measurement of pH of yogurt was established.

In order to measuring the sugar content of yogurt rapidly, a fast measurement of sugar content of yogurt using Vis/NIR-spectroscopy techniques was established. 25 samples selected separately from five different brands of yogurt were measured by Vis/NIR-spectroscopy. The sugar content of yogurt on positions scanned by spectrum were measured by a sugar content meter. The mathematical model between sugar content and Vis/NIR spectral measurements was established and developed based on partial least squares (PLS). The correlation coefficient of sugar content based on PLS model is more than 0.894, and standard error of calibration (SEC) is 0.356, standard error of prediction (SEP) is 0.389. Through predicting the sugar content quantitatively of 35 samples of yogurt from 5 different brands, the correlation coefficient between predictive value and measured value of those samples is more than 0.934. The results show the good to excellent prediction performance. The Vis/NIR spectroscopy technique had significantly greater accuracy for determining the sugar content. It was concluded that the Vis/NIRS measurement technique seems reliable to assess the fast measurement of sugar content of yogurt, and a new method for the measurement of sugar content of yogurt was established.

A new noninvasive measurement of oxygen contents in hepatic tissues using near-infrared technique according to physiological characteristics is proposed. The procedure can be divided into three categories. First a quantitative formula is introduced to measure oxygen contents in hepatic tissues based on the relationship between absorption coefficient and typical wavelengths, where 760nm and 850nm infrared wavebands are utilized in this paper. Second, many characteristics such as waveforms of oxygen contents in hepatic tissues, cross correlation of blood-oxygen and power spectrum of oxygen contents, are analyzed detailedly with regard to different symptoms in hepatic tissues. Finally, a conclusion can be drawn that waveforms of oxygen contents, cross correlation and power spectrum are three main features, which can well depict the symptoms of hepatic tissues. The proposed method is applied to examine 143 people, including 40 normal people and 103 patients with different symptoms in hepatic tissues. The false probability is 8.3% and the missing probability is 13.7% under specified criterion. The clinical experiments show that our proposed method is simple but effective and can be used to routine examinations or intensive care units for liverish patients.

Near infrared (NIR) diffuse reflection spectroscopy has been an effective way to perform quantitative analysis without the requirement of sample pretreatnient. In this paper, NIR Fourier transform infrared (FTIR) spectroscopy has been introduced to probe spectral features of traditional Chinese medicine Danshen. Infrared fingerprint spectra of Danshen can be established. Influence of differentiation of spectrum is also discussed. After pretreatment and derivation on the spectral data, methods of principal analysis (PCA), soft independent modeling of class analogy (SIMCA) and Artificial Neural Network (ANN) are combined to sort the geographical origins of 53 samples by local modeling. The result show that, as a basis of the other two methods, PCA is a more efficient one for identifying the geographical origins of Danshen. Combining SIMCA with PCA, an effective model is built to analyze the data after normalization and differentiation, the correct identification rate reaches above 90%. Then 36 samples are chosen as training set while other 17 samples being verifying set. Using ANN-based Back Propagation method, after proper training of BP network, the origins of Danshen are completely classified. Therefore, combined with advanced mathematical analysis, NIR diffuse spectroscopy can be a novel and rapid way to accurately evaluate the origin of Chinese medicine, and also to accelerate the modernization process of Chinese drugs.

In this paper, to find the quantitative errors of aqueous glucose induced by the temperature change at every wave point ranging from 1200 to 1700 nm, the calibration curve is calculated and shown. During the measurement the temperature varies from 30°C to 40°C, at a 2°C interval, and aqueous glucose concentration ranges from 100 mg/dL to 500 mg/dL, at a interval of 100 mg/dL. The absorption of aqueous glucose decreases with the increasing of temperature, also the absorbance decreases. In addition, only 1°C change in the temperature induces about -7xlO^-3and -4x10^-3 errors in the absorbance of the aqueous glucose at the wavelength of 1550 and 1610 nm respectively. To decrease or even eliminate the error caused by the temperature, two methods are put up in this paper.

A new method for discrimination of apple varieties by means of infrared spectroscopy (NIRS) was developed. First, the characteristic spectra of apple were got through principal component analysis (PCA), the analysis suggested that the cumulative reliabilities of PC (principal component)1 and PC2 was more than 98%. The 2-dimensions plot was drawn with the scores of the first and the second principal components; it appeared to provide the best clustering of the vaneties of apple. PCA compressed thousands of spectral data into several variables that described the body of spectra; the several variables were applied as inputs to a back propagation neural network with one hidden layer. 75 samples with three varieties were selected randomly, then they were used to build BP-ANN model. This model had been used to predict the varieties of 15 unknown samples; the recognition rate of 100% was achieved. This model is reliable and practicable. So this paper could offer a new approach to the fast discrimination of apple varieties methods.

Near infrared reflectance spectroscopy offers the potential for rapid and cost-effective soil analysis. Unfortunately, their prediction model is valid to their sampling pretreatment and the experiment proceedings, and this is believed to be due to the influence of the physical properties of the soil sample and the geometric conditions of the sampling accessory. The objective of this study was to evaluate the influence of the container to soil spectra in a given distance and angle of the spectra detector, and their ability to soil water content prediction. Six petri dishes with different diameters and heights (d12.5cm, h2.2cm; d14.7cm, h2.9cm; d15.7cm, h2.8cm; dl0.4cm, h1.7cm; d9.3cm, hl.5cm; d9.7cm, hl.9cm) were applied for the analysis. A total of 106 soil samples were obtained in Zhejiang, Hangzhou and their spectral features and the water content were analyzed. Principal component analysis (PCA) - artificial neural network (ANN) was used to build prediction models with a calibration data set of 81 randomly chosen samples. The remaining 25 soil samples were used to valithte the prediction model. Accurate water content prediction was obtained when the diameter of the soil container was 12.5 cm with r = 0.91. The results were consistent with the geometric analysis.

The spectral analysis technique based on the spectral reflected property to identify object make the real time inspection of crop nutrition and fast diagnoses come true. Compared with the conventional means of crop nutrition fast diagnoses, the information acquired by spectral analysis technique is faster and save both time and labor, it is the basic technique adopted in the precision agriculture which needs to do research on variable fertilization and irrigation. Using spectral analysis technique to process crop nutrition real time inspection and fast diagnoses is always the popular research in remote sensing in agriculture. In this paper, in order to find a simple, quick and untouched method to check the level of nitrogen in canola, the spectral reflectance and SPAD values of the canola leaves of eight regions were measured by an ASD Field Spec(R) and SPAD 502 chlorophyll meter. Experiment was made on the leaves taken from live canola, and the relationship between spectral reflectivity and chlorophyll concentration was analyzed. 32 groups of the chlorophyll concentration data and the reflected spectra data corresponding to them were acquired, also the correlation between red edge inflexion point position and chlorophyll concentration was analyzed, and the coefficient of 0.986 was got. The mathematic model between the first derivative of absorption spectra and chlorophyll concentration was established, and the coefficient of 0.873 was got. Therefore it indicated more that it is possible to use the hyper-spectroscopy remote sensing to explore the chlorophyll concentration of canola in ration.

The objective of this research was to analyze NIR spectroscopy potential to estimate COD in livestock wastewater. A total of 20 wastewater samples were taken from the Animal Institution of Zhejiang Agricultural Science Organization. We selected two kinds of containers with the sizes of l000mL and 2000mL for samples, because of the high absorption peaks in the near-infrared region (350-11OOnm) around 635nm. 14 samples spectra were used during the calibration and cross-validation stage. Five samples spectra were used to predict COD concentration in wastewater. NW spectra and constituents were related using partial least square (PLS) technique. The r² between measured and predicted values of COD of wastewater with l000mL and 2000mL, 0.9895 and 0.9985, as well as SEP showed table l, 22 and 32, respectively, demonstrated that NIR method have potential to predict COD in wastewater. While SEP and SEC is high, because the magnitude of COD value in livestock wastewater is high. In other words, higher magnitudes will result in high standard error values. However, the result also shows that NIR could be a good tool to be combined with environmental monitoring of water quality.

Visible/Near Infrared Speciroscopy (Vis/NIR) appears as a prominent technique for nondestructive fruit quality assessment. This research work was focused in to evaluate the use of Vis/NIRS in measuring the quality characteristics of intact Fuji apple (from Shanxi of China), and the relationship was established between nondestructive Vis/NIR spectral measurement and the soluble solids content of apple. Intact apple fruit were measured by reflectance Vis/NIR in 325-1075 nm range. The data set as the logarithms of the reflectance reciprocal (absorbance (logl/R)) was analyzed in order to build the best calibration model for this characteristic, using some spectral pretreatments and multivariate calibration techniques such as partial least square regression (PLS). The models for the SSC (r =0.862), standard error of prediction (SEP) 0.907 with a bias of 0.599; shown the reasonable prediction performance. The Vis/NIR spectroscopy technique had significantly accuracy for detennining the SSC. It was concluded that the Vis/NIRS measurement technique seems reliable to assess the soluble solids content of apple non-destructively.

A new method for discrimination of varieties of Chinese bayberry by means of infrared spectroscopy (NIRS) (325-1075nm) was developed. A relation has been established between the reflectance spectra and Chinese bayberry varieties. The dataset consist of a total of 69 samples of Chinese bayberry. First, the data was analyzed with principal component analysis. It appeared to provide the best clustering of the varieties of Chinese bayberry. PCA compressed thousands of spectral data into a small quantity of principal components and described the body of spectra; the scores of the first 20 principal components computed by PCA had been applied as inputs to a back propagation neural network with one hidden layer. 69 samples contained three varieties were selected randomly, then they were used to build BP-ANN model. This model had been used to predict the varieties of 15 unknown samples; the residual error for the calibration samples is 1.508458 x 10^-6. The recognition rate of 100% was achieved. The result achieved by using PCA-BP method is much better than the results achieved by only using the PCA method. This model is reliable and practicable. So this paper could offer a new approach to the fast discrimination ofvarieties of Chinese bayberry.

In this research, the potential of using the Visible/Near Infrared Spectroscopy (Vis/NIRS) was investigated for measuring the acidity of Chinese bayberry (Myrica rubra Sieb.et Zucc. ), and the relationship is established between nondestructive Vis/NIR spectral measurement and the major physiological property of Chinese bayberry. Intact Chinese bayberry fruit were measured by reflectance Vis/NIR in 325-1075 nm range. The data set as the logarithms of the reflectance reciprocal (absorbance (loglIR)) was analyzed in order to build the best calibration model for this characteristic, using some spectral pretreatments and multivariate calibration techniques such as partial least square regression (PLS). The models for the pH (r=0.963), standard error ofprediction (SEP) 0.21 with a bias of 0.138; shown the excellent prediction performance. The Vis/NIR spectroscopy technique had significantly greater accuracy for determining the pH. It was concluded that the Vis/NIRS measurement technique seems reliable to assess the quality attribute of Chinese bayberry nondestructively.

In this research, the potential ofusing the Visible/Near Infrared Spectroscopy (VisINIRS) was investigated for measuring the reducing sugar of Fuji apple (from Shanxi of China), and the relationship was established between nondestructive Vis/NIR spectral measurement and the reducing sugar of apple. Intact apple fruit were measured by reflectance Vis/NIR in 325-1075 nm range. The data set as the logarithms of the reflectance reciprocal (absorbance (logl/R)) was analyzed in order to build the best calibration model for this characteristic, using some spectral pretreatments and multivariate calibration techniques such as partial least square regression (PLS). The models for the reducing sugar (r=0.915), standard error of prediction (SEP) 0.562 with a bias of 0.054; shown the excellent prediction performance. The Vis/NIR spectroscopy technique had significantly greater accuracy for determining the reducing sugar. It was concluded that by using the Vis/NIRS measurement technique, in the spectral range (325-1075 nm), it is possible to assess the reducing sugar content of apple.

This research is to use spectroscopy data to determine the producing area of sampled waxberries. which are very similar in sizes and textures and color. and also very similar in taste. So, it is hard to tell where is the producing area of the given waxberry. In this research, 30 samples were chosen from each of the 4 kinds of waxberries. The producing areas are XianJu CiXi Nmghai and Lishui all in Zhejiang province. Firstly, spectroscopy were taken down by ASD FieldSpec (Handheld type, its spectrum is between 325-1075nm resolution is 3.5nm), and then its acidity measured by PH meter and sugar content by saccharin-meter. The following data process shows that the spectroscopy can record the whole information of one sample. By using wavelet transform and PCA analysis. the sampled waxberry producing area were recognized with higher correction than using the two chemical indices. acidity and sugar content index. In the 30 samples. 100 were used to build model, and let other 20 to forecast. less than 3 samples were forecasted wrongly. The PCA statistics told us that the relativity between the acidity and sugar index vector to the PCA vector extracted from the spectroscopy is greater than 0.84. Due to the large standard variance in one sampled set. the using of chemical indices to classify is not satisfying. This research demonstrates that the different producing areas of waxberry have evident differences in spectroscopy, though it is hard to tell them out by using hand or mouth.

The traditional uniform herbicide application often results in an over chemical residues on soil, crop plants and agriculture produce, which have imperiled the environment and food security. Near-infrared reflectance spectroscopy (NIRS) offers a promising means for weed detection and site-specific herbicide application. In laboratory, a total of 90 samples (30 for each species) of the detached leaves of two weeds, i.e., threeseeded mercury (Acalypha australis L.) and fourleafed duckweed (Marsilea quadrfolia L.), and one crop soybean (Glycine max) was investigated for NIRS on 325- 1075 nm using a field spectroradiometer. 20 absorbance samples of each species after pretreatment were exported and the lacked Y variables were assigned independent values for partial least squares (PLS) analysis. During the combined principle component analysis (PCA) on 400-1000 nm, the PC1 and PC2 could together explain over 91% of the total variance and detect the three plant species with 98.3% accuracy. The full-cross validation results of PLS, i.e., standard error of prediction (SEP) 0.247, correlation coefficient (r) 0.954 and root mean square error of prediction (RMSEP) 0.245, indicated an optimum model for weed identification. By predicting the remaining 10 samples of each species in the PLS model, the results with deviation presented a 100% crop/weed detection rate. Thus, it could be concluded that PLS was an available alternative of for qualitative weed discrimination on NTRS.

The use of optical techniques to identify and quantify atmospheric pollutants has been focused within the past two decades. Fourier Transform Infrared (FTIR) spectroscopy has proven to be a powerful tool for multi-component analysis of air quality monitoring. The technique has been used for gaseous samples by extractive sampling as well as in the open-path configuration. The present contribution has described the application of FTIR to analyze gaseous pollutants in ambient air in detail. The study for the detection limits of the interested gas, the design of the multipass White mirror system, and the experimental results are described. The White cell is employed to increase the absorbance relative to noise in the absorbance spectrum by increasing the path length without proportional loss of signal. A classical least squares (CLS) fit is used to match the scaled standards or previously measured absorption profiles to those of the observed spectrum in the specified spectral analysis regions for simultaneous quantification of the compounds of interest, plus several other ambient air constituents. The regions were chosen carefully to provide optimum detection of the compounds of interest with minimum interference by other compounds. Specially, spectrum subtraction and differential absorption concepts are introduced into FTIR data analysis. The optimal window for CO, S0₂, NO₂, NO and CO₂ would be the region at 2250-2020 cm^-1, 1230-1070 cm^-1, 2940-2840 cm^-1, 1965-1775 cm^-1, and around 668.24 cm^-1 respectively. Deviations from traditional measured results for all approaches are in 10%.

Technology for fluorescence spectral imaging of microscopic has made significant strides advantages in the past several years. These advances have led to the enhanced choice of suitable diagnosis bases. Of course, fluorescence imaging can facilitate the study of disease at the molecular level in vivo. And this type of optical imaging has enabled real-time research to track cell movement, cell growth and other cell functions. With the addition of spectral imaging, fluorescence spectral imaging could complete a so-called 4-dimension imaging for the object. The investigator can obtain either the color imaging information or the information beyond it. The combination of both of them could show the relative completeness message. For evolution of software tools to deal with the resulting high-dimensionality datasets, it is necessary to find some effective and comparative reliable datasets analytical methods. In this paper, it also describes some quantitative fluorescence in tissue and addresses further applications of fluorescence spectral imaging. It includes MSE (Minimum Squared Error), PCA (Principal Components Analysis), ICA (Independent Component Analysis), FEA (Finite-Element Analysis), wavelet theory and their applications. They are useful in intact animals for disease detection, screening, diagnosis, treatment evaluation and drug development.

Apoptosis is an evolutionary conserved cellular process that plays an important role during development, but it is also involved in tissue homeostasis and in many diseases. To study the characteristics of suicide gene system of the herpes simplex virus thymidine kinase (HSV-tk) gene in tumor cells and explore the apoptosis phenomena in this system and its effect on the human adenoid cystic carcinoma line ACC-M cell, we detected apoptosis of CD3- (ECFP-CRS-DsRed) and TK-GFP-expressing ACC-M (ACC-M-TK-GFP-CD3) cells induced by acyclovir (ACV) using fluorescence resonance energy transfer (FRET) technique. CD3 is a FRET-based indicator for activity of caspase-3, which is composed of an enhanced cyan fluorescent protein, a caspase-3 sensitive linker, and a red fluorescent protein from Discosoma with efficient maturation property. FRET from ECFP to DsRed could be detected in normal ACC-M-TK-GFP-CD3 cells, and the FRET efficient was remarkably decreased and then disappeared during the cells apoptosis induced by ACV. It was due to the activated caspase-3 cleaved the CD3 fusion protein. In this study, the results suggested that the AVC-induced apoptosis of ACC-M-TK-GFP-CD3 cells was through caspase-3 pathway.

Combination of fluorescence spectral and temporal resolutions can improve the sensitivity and specificity of biomedical diagnostics. In this paper, we present the development of a time resolved two-photon excited fluorescence spectroscopy system that consists of a Ti: Sapphire femtosecond laser, a fluorescence microscope objective, a prism spectrophotometer and a high repetition rate picosecond streak camera. The streak camera and the time-resolved fluorescence spectroscopy system. have been calibrated with an F-P etalon and a spectral line lamp respectively. Validation experiment of the system is also performed on two standard fluorescent dyes (Rhodamine 6G and Coumarin 314), and the results agree well with those reported in the literatures. Preliminary experimental results on autofluorescence spectra and lifetimes of freshly picked leaves and in vivo human skin are also presented, which demonstrates the potential applications of this system in tissue discrimination and clinical diagnostics.

In this study, a novel method for the direct detection of GMP without amplified by the general method of PCR is firstly presented and proved by experiments. In our method, fluorescence correlation spectroscopy, cleaving nucleic acid by restriction endonuclease and two nucleic acid probe hybridization techniques are combined to distinguish the caulifiower mosaic virus (CaMV) 35S promoter and determine whether samples contain genetically modified components. The detection principle is as follows: firstly two restriction endonucleases FOKI and BsrDlare used to cleave the genomic DNA and the 169bp fragments of CaMV 35S promoter are retrieved; secondly, two nucleic acid probes labeled by Rhodamine Green and y5 dyes respectively hybridize with cleaved 169bp fragments of CaMV 35S promoter; thirdly, the hybridization products simultaneously with two dye-labeled probes are detected by fluorescence cross-correlation spectroscopy and GMP is distinguished. As the detection and analysis by FCS can be performed at the level of single molecule, there is no need for any type of amplification. Genetically modified tobaccos are measured by this method. The results indicate this method can detect CaMV 35S promoter of GMP exactly and the sensitivity can be down to 3.47X10^-10M. Because no any type of amplification is involved, this method can avoid the non-specffic amplification and false-positive problems of PCR, Due to its high-sensitivity, simplicity, reliability and little need for sample amounts, this method promises to be a highly effective detection method for GMP.

Photosynthetic apparatus is susceptible to environmental stress. Light-induced delayed fluorescence (DF) in plant is an intrinsic label of the efficiency of charge separation at P680 in photosystem II (PS II). In this investigation, we have developed a biosensor that can accurately inspect acid rain pollution by means of DF in vivo. Compared with traditional methods, the proposed technique can continuously monitor environmental changes, making fast, real-time and noninvasive inspection possible. The biosensor is an all-weather measuring instrument; it has its own illumination power and utilizes intrinsic DF as the measurement marker. With soybean (Glycine max (L.) Merr.) seedling as a testing model, which is sensitive to acid rain pollution, the relationship that delayed fluorescence properties and capability of photosynthetic apparatus after being affected by simulated acid rain with different pH value was studied. The current investigation has revealed that the changes of delayed fluorescence (equation available in paper) can probably characterize the pollution degree of simulated acid rain, Inspecting the changes in DF characteristics (φ_i) of plant leaf in vivo may be a new approach for the detection of acid rain pollution and its impact on the ecosystem.

We demonstrate a new fluorescence resonance energy transfer (FRET) based approach to determine the donor-acceptor distributions and apply it to two model molecular systems: double stranded DNA labeled with Hoechst 33258 and FAM, and perylene randomly surrounded by cobalt ions in a bulk solution. The approach makes some generic assumptions regarding the FRET kinetics, but no a priori assumptions regarding the distribution function.

The desire to image with sub micron resolution at ever increasing depths into living samples is providing optical physicists with the latest in a long line of challenges presented by life science researchers. The advent of confocal, and subsequently multiphoton microscopy, has opened up exciting new possibilities but simultaneously posed new challenges. As one images ever more deeply into the sample, the optical properties of the tissue distort the image significantly lowering the resolution and, in the case of multiphoton imaging in particular, decreasing the fluorescence yield as the excitation volume rises. The recent use of active optical elements has shown a way forward in restoring high contrast high resolution images at depth. However, significant issues on the actual shape required on such an element are as yet unresolved. We report on two recent advances in this area. The first is the use of a range of optimisation algorithms to restore the optical point spread function and hence improve the image quality at depth. The second is a radically new approach incorporating two active elements, a slow spatial light modulator and a fast deformable mirror, to actively lock up the system. We report on the latest advances in active image compensation where conections at over 5OOmicrons into the sample have been made using a combination of deformable mirrors and spatial light modulators.

Confocal laser scanning microscopy (CLSM) has rapidly become an essential tool in the life sciences laboratory, enabling high-resolution and minimally intrusive optical sectioning of fluorescent samples. Most commercially available CLSM systems employ a gas laser, e.g. a Kr/Ar laser, to provide the excitation radiation. However, such lasers have several shortcomings, including the maintenance requirements, short lifetimes and high noise levels. To overcome these limitations, a light source for CLSM that is based on supercontinuum generation in photonic crystal fiber has been developed. This source provides the necessary wavelength range required to excite the widest possible variety of fluorophores. A novel method of extracting the desired wavelengths from the supercontinuum source using a digital micro-mirror device (DMD) is also described.

We have developed a novel method for imaging the fluorescence intensity and anisotropy by two-photon fluorescence microscopy and tested its capability in biological application. This method is applied to model sample including FITC and FITC-CD44 antibody solution and also FITC-CD44 stained cells. The fluorescence anisotropy (FA) of FITC-CD44ab solution is higher than the FITC solution with the same concentration. The fluorescence in cell sample has even higher FA than in solution because the rotation diffusion is restrained in membrane. The method is employed to study the effect of berberine a kind of Chinese medicine, on tumor metastasis. The results indicated that tumor cell membrane fluidity is decreasing with increasing the concentration of berberine in culture medium.

In this study, P300 that induced by visual stimuli was examined with simultaneous EEG/fMRI. For the purpose of combine the best temporary resolution with the best special resolution together to estimate the brain function, event-related analysis contributed to this methodological trial. A 64 channel MRT-compatible MR EEG amplifier (BrainAmp: made of Brain Production GmbH, Gennany) was used in the measurement simultaneously with fMRI scanning. The reference channel is between Fz, Cz and Pz. Sampling rate of raw EEG was 5 kHz, and the MRT noise reduction was performed. EEG recording synchronized with MRI scan by our original stimulus system, and an oddball paradigm (four-oriented Landolt Ring presentation) was performed in the official manner. After P300 segmentation, the timing of P300 was exported to event-related analysis of fMRI data with SPM99 software. In single subject study, the significant activations appear in the left superior frontal, Broca's area and on both sides of the parietal lobule when P300 occurred. It is suggest that P300 may be an integration carried out by top-down signal from frontal to the parietal lobule, which regulates an Attention-Logical Judgment process. Compared with other current methods, the event related analysis by simultaneous EEG/IMRI is excellent in the point that can describe the cognitive process with reality unifying further temporary and spatial information. It is expected that examination and demonstration of the obtained result will supply with the promotion of this powerful methods.

Multifocal multiphoton microscopy (MMM) is a more efficient and powerful method for three-dimensional (3-D) fluorescence imaging with reduced acquisition time compared with conventional confocal and two-photon excitation fluorescence microscopy. We present a novel multifocal two-photon excitation fluorescence sampling imaging technique that is based on a specially designed streak camera and combines fluorescence lifetime and spectrum resolutions. A proof-of-principle experiment is performed on a standard fluorescent dye solution (Rhodamine 6G in ethanol), Time- and spectrum-resolved sampled fluorescence image of Rhodamine 6G is obtained in a snapshot. The reconstructed two-dimensional (2-D) fluorescence image of a prepared plant slide is also obtained by moving the sample laterally. The capability of this system capable of performing simultaneous 2-D measurements of temporal and spectral information has many potential applications, e.g., multi-well imaging and spectrally resolved multifocal multiphoton fluorescence lifetime imaging etc.

Raman spectroscopy combines the fingerprinting advantage of mid-JR spectroscopy with the ease of use and remote, non-invasive capability of near-JR spectroscopy. Now, Raman spectroscopy is fast becoming a perfect technique of analysis in raw material identification, verification, process control in biological, chemical and industrial fields, because Raman spectra are a fingerprint for the molecular species present in a specimen and can be used for both qualitative identification and quantitative determination. This paper introduces that low-resolution Raman spectroscopy (LRRS) satisfies the need for a highly useful, low-cost spectroscopic approach to both qualitative and quantitative analyses. First the principles and methods of analyses were introduced, especially quantitative analyses based on ratio method, and then several applications were described, which were representatives of qualitative and quantitative analyses. Secondly, these experimental results were discussed and analyzed in detail. The results show that the Raman spectroscopy technology is flexible, affordable and easily adapted to on-site and in situ analysis.

The characterization of species in aqueous solutions has presented a challenge to analytical and physical chemist, because the JR absorption of the aqueous solvent is so intense that it becomes difficult to observe the solute in the water by JR absorption. In contrast, Raman spectrum of the solute is unaffected by the water, so the weak scattering of water makes the technique well suited to aqueous samples, and the Raman spectrum exhibits well-defined bands corresponding to fundamental modes of vibration. In addition, Raman spectroscopy has some inherent advantages in aqueous solution analysis, because the spectral features of signals from different species are much more distinct, and it provides characteristic signatures for samples, such as blood, protein and cholesterol. All the advantages make Raman spectroscopy be a potential alternative for the study of aqueous solutions. Now, Raman spectroscopy has been applied to studying samples in aqueous solutions, blood serum, intracellular protein levels. Now, industrial wasted water contains many organic contaminants, and it is necessary to determine and monitor these contaminants. The paper first introduces Raman spectroscopy, and then describes its applications to determining the components in aqueous solutions, analyzes and assignes the Raman spectra of o-dichlorobenzene, o-xylene, m-xyiene and p-xylene in detail. The experimental results demonstrate that Raman spectroscopy is a particularly powerful technique for aqueous solutions analyses.

By means of Artificial Neural Network and Back-Propagation algorithm, the multi-component of azo-dyes can be qualitatively and quantitatively analyzed simultaneously, though their Raman spectra are overlapped. This article designed a Back-Propagation algorithm network to analyze the multi-component of azo-dyes (Sudan I and Sudan III). In conclusion, by using the Artificial Neural Network and Raman spectrum can be a good choice for resolving multi-component.

Light-induced autofluorescence spectra of nasopharyngeal carcinoma and normal tissue in vitro were compared to that of known endogenous fluorophores to explore the possible causes of tissue autofluorescence and to further determine the optimal excitation wavelengths for optical biopsy in vivo. Nasopharyngeal carcinoma and normal tissues were obtained from the suspected patients during pathological biopsy. A FL/FS92O combined TCSPC spectrofluonmeter and a lifetime spectrometer system was used for autofluorescence spectra measurement. Fluorescence excitation wavelengths varying from 260 to 480 nm were used to induce tissue autofluorescence, and the corresponding fluorescence emission spectra were recorded from a range starting 20 nm above the excitation wavelength and extending to 700 nm. The autofluorescence excitation-emission pairs of nasopharyngeal carcinoma and nonnal tissues occur at 300-330, 340-460 and 450-520 nm, and the optimal diagnostic excitation wavelengths for detection of nasopharyngeal carcinoma were 340 and 450 nm. The results abtained in this study could be treated as a reference for the development of optical biopsy system for nasopharyngeal carcinoma.

The absorption spectra of two illicit drugs, methylenedioxyamphetarnine (MDA) and methamphetamine (MA), within and without two conventional envelopes are studied using terahertz time-domain spectroscopy technique. The characteristic absorption spectra of MDA and MA are obtained in the range of 0.2 THz to 2.5 THz. MDA has an obvious absorption peak at 1.41 THz while MA has obvious absorption peaks at 1.23 THz, 1.67 THz, 1.84 THz and 2.43 THz. We find that the absorption peaks of MDA and MA within the envelopes are almost the same as those without the envelopes respectively although the two envelopes have some different absorption in THz waveband. This result indicates that the type of illicit drugs in envelopes can be determined by identifying their characteristic absorption peaks, and THz time-domain spectroscopy is one of the most powerful candidates for illicit drugs inspection.

The optical characteristics of both the reduced and oxidized glutathione molecules in the range of O.2-2.5 THz have been investigated by the terahertz time-domain spectroscopy (THz-TDS) technology. The characteristic spectrum and optical parameter are obtained at the room temperature in nitrogen condition. The result shows that different samples have different absorption features. For the reduced glutathione, the absorption peaks centered at 0.85, 1.20, 1.52, 1.64, and 2.5 THz. While for the oxidized glutathione no obvious absorption peaks were found. The average refractive indices of two pure different glutathione samples (reduced and oxidized) are 1.77 and 1.89 respectively. The experimental results of two samples are compared and analyzed in this paper. This work has demonstrated significantly that THz-TDS can be used to identify two kinds of glutathione molecules, and can further be used to study other biological molecules in biological and biomedical engineering.

This paper reports the theoretical and experimental vibrational spectra of the histidine in the frequency range between 0~ 10.0 and 0.2~2.8 THz (FIR) respectively. Seven absorption peaks have been calculated out by using the semi-empirical theory and PM3 algorithm. The characteristic absorption peaks are attributed to torsional vibration modes of the molecule based on the semi-empirical theory. Three experimental peaks obtained from terahertz time-domain spectroscopy (THz-TDS) are comparable with the first three calculated peaks and these results mutually validated both approaches, although other four theoretical peaks between 2.8~10.0 THz remain to be tested in future.