The images obtained by large aperture static imaging spectrometer (LASIS) are two dimensional images which contain interference information. The acquisition of different places’ interferogram needs to pushbroom the whole field of view. Because of the instability of the pushbroom platform, the original LASIS image registration is required, and the interferogram after registration is no longer consistent with equal interval interference. The spectral information will be severely distorted while a fast Fourier transform (FFT) is used for the direct extraction of the interferogram. In view of the above problems, this paper introduces a method based on phase correlation, and proposes an adaptive fast interpolation algorithm. Experimental results show that the proposed method can recover the spectral information well when the registration accuracy is sufficient.
Acousto-optic tunable filter (AOTF) is a novel device for spectrometer. The electronic tunability qualifies it with the
most compelling advantages of higher wavelength scan rate over the conventional spectrometers that are mechanically
tuned, and the feature of large angular aperture makes the AOTF particularly suitable in imaging applications. In this
research, an AOTF-based near-infrared imaging spectrometer was developed. The spectrometer consists of a TeO2
AOTF module, a near-infrared imaging lens assembly, an AOTF controller, an InGaAs array detector, an image
acquisition card, and a PC. A precisely designed optical wedge is placed at the emergent surface of the AOTF to deal
with the inherent dispersion of the TeO2 that may degrade the spatial resolution. The direct digital synthesizer (DDS)
techniques and the phase locked loop (PLL) techniques are combined for radio frequency (RF) signal synthesis. The
PLL is driven by the DDS to take advantage of both their merits of high frequency resolution, high frequency scan rate
and strong spurious signals resistance capability. All the functions relating to wavelength scan, image acquisition,
processing, storge and display are controlled by the PC. Calibration results indicate that the spectral range is 898~1670
nm, the spectral resolution is 6.8 nm(@1064 nm), the wavelength separation between frames in the spectral image
assembly is 1.0 nm, and the processing time of a single image is less than 1 ms if a TV camera with 640×512 detector is
incorporated. A prototype device was assembled to test the capability of differentiating samples with similar
appearances, and satisfactory results were achieved. By this device, the chemical compositions and the distribution
information can be obtained simultaneously. This system has the most advantages of no moving parts, fast wavelength
scan and strong vibration resistance. The proposed imaging spectrometer has a significant application prospect in the
area of identification of camouflaged target from complex backgrounds. In addition, only the objective lens and its
accessories are required to be replaced for its use in microscopic spectral imaging system, which may be popularized to
a large number of other possible applications.
We have been developing a computer-aided diagnosis (CAD) system for automatically recognizing cervical cancer cells from Papanicolaou smear. Considering that pathological changes of cervix can be indicated by the abnormity of the nucleus of intermediate cell, the key task of this system is to find the intermediate cells and segment the nucleus precisely. This paper presents a novel approach for automatic segmentation of microscopic cervical cell images using multispectral imaging techniques. In order to capture images at different wavelengths, a Liquid Crystal Tunable Filter (LCTF) device is used to provide wavelength selection from 400nm to 720nm with an increment of 10nm. Considering the spectral variances of background, nucleus and cytoplasm, background is extracted firstly from the microscopic images by calculating pixel intensity variance at 470nm, 530nm, 570nm, 580nm and 650nm. Then superficial cells are extracted apart from intermediate cells easily at 530nm 650nm because of the different pixel intensity distribution of the two kinds of cells at these two wavelengths. To segment the nucleus from intermediate cells, we adopt two procedures. Firstly, the nuclei are roughly segmented apart by using an iterative maximum deviation between-cluster algorithm. Secondly, a novel rigorous algorithm based on active contour model is adopted to achieve more exact nuclei segmentation. Using the method proposed in this paper, we did experiments on over 300 cervical smears, and the results show that this method is more robust and precise.
Counting of different classes of white blood cells in bone marrow smears can give pathologists valuable information regarding various cancers. But it is tedious to manually locate, identify, and count these classes of cells, even by skilled hands. This paper presents a novel approach for automatic detection of White Blood Cells in bone marrow microscopic images. Different from traditional color imaging method, we use multispectral imaging techniques for image acquisition. The combination of conventional digital imaging with spectroscopy can provide us with additional useful spectral information in common pathological samples. With our spectral calibration method, device-independent images can be acquired, which is almost impossible in conventional color imaging method. A novel segmentation algorithm using spectral operation is presented in this paper. Experiments show that the segmentation is robust, precise, with low computational cost and insensitive to smear staining and illumination condition. Once the nuclei and cytoplasm have been segmented, more than a hundred of features are extracted under the direction of a pathologist, including shape features, textural features and spectral ratio features. In pattern recognition, a maximum likelihood classifier (MLC) is implemented in a hierarchical tree. The classification results are also discussed. This paper is focused on image acquisition and segmentation.
Cervical cancer is the second most common cancer among women worldwide. Early detection of cervical cancer is very important for successful treatment and increasing survival. Papanicolaou test is the most popular and effective screening test for cervical cancer, but it is highly subjective and skilled-labor intensive. We report a multispectral imaging microscopic system for Papanicolaou smear analysis for early detection of cervical cancer. Different from traditional color imaging method, we use multispectral imaging techniques for image acquisition, which can simultaneously record spectral and spatial information of a sample. A liquid crystal tunable filter (LCTF) is coupled in the light microscope for fast wavelength selection and a two-dimensional cooled charge-coupled device (CCD) for image capture. In this paper, the multispectral image acquisition method is introduced, including exposure control and spectral calibration, which makes the images not so dependent on imaging devices. In the image segmentation process, an effective algorithm using spectral ratio method is applied for cell nuclei detection. This segmentation method can easily detect the nuclei and diminish the influence of the cytoplasm overlap. Results show that our segmentation is more robust and precise than conventional color imaging method which is heavily dependant on sample staining and illumination conditions while with high speed. Once the nuclei have been segmented, cell features including morphological and textural features are measured. A genetic algorithm is used for feature selection and a support vector machine(SVM)is used for training and classification. This paper is focused on image acquisition and segmentation.
This paper describes a novel multispectral imaging microscope that can simultaneously record both spectral and spatial information of a sample, which can take advantage of spatial image processing and spectroscopic analysis techniques. A Liquid Crystal Tunable Filter device is used for fast wavelength selection and a cooled two-dimensional monochrome CCD for image detection. In order to acquire images that are not so dependent on imaging devices, a clever CCD exposure time control and a software based spectral and spatial calibration process is performed to diminish the influence of illumination, optic ununiformity, CCD’s spectral response curve and optic throughput property. A set of multispectral image processing and analysis software package is developed, which covers not only general image processing and analysis functions, and also provides powerful analysis tools for multispectral image data, including multispectral image acquisition, illumination and system response calibration, spectral analysis and etc. The combination of spatial and spectral analysis makes it an ideal tool for the applications to biomedicine. In this paper, two applications in biomedicine are also presented. One is medical image segmentation. Using multispectral imaging techniques, a mass of experiments on both marrow bone and cervical cell images showed that our segmentation results are highly satisfactory while with low computational cost. Another is biological imaging spectroscopic analysis in the study of pollen grains in rice. The results showed that the transmittance analysis of multispectral pollen images can accurately identify the pollen abortion stage of male-sterile rice, and can easily distinguish a variety of male sterile cytoplasm.
This paper describes a novel multispectral imaging microscope and its applications in the study of pollen grains in rice. The Imaging instruments can simultaneously record both spectral and spatial information of a sample, which is helpful to study the chemical states and physical properties of the sample by taking advantage of spatial image processing and spectroscopic analysis techniques. A LCTF (liquid crystal tunable filter) device is used for fast wavelength selection in the range of 400nm to 720nm and a cooled two-dimensional monochrome CCD for image detection. In this paper, the image acquisition process, spatial and spectral calibration and spectral imaging analysis methods are detailed. And also a novel method using this multispectral imaging microscope to observe rice pollen grains is reported here. The multispectral images were systematically processed and analyzed by the software. The results illustrated that the transmittance analysis of multispectral pollen images can accurately identify the pollen abortion stage of male-sterile rice, and can easily distinguish a variety of male sterile cytoplasm. Compared with cytological and histochemical methods reported previously, the method reported here has demonstrated to be more efficient and reliable in the study of chemical states and physical properties in plant cells.