We attempt to develop a systematic scheme through adopting high-pass filtering (HPF) to well resolve value-preserved images such as medical images. Our approach is derived from the Poisson maximum a posteriori superresolution algorithm employing the HP filters, where four filters are considered such as two low-pass-filter-combination based filters, wavelet filter, and negative-oriented Laplacian HP filter. The proposed approach is incorporated into the procedure of finite-element-method (FEM)-based image reconstruction for diffuse optical tomography in the direct current domain, posterior to each iteration without altering the original FEM modeling. This approach is justified with various HPF for different cases that breast-like phantoms embedded with two or three inclusions that imitate tumors are employed to examine the resolution performances under certain extreme conditions. The proposed approach to enhancing image resolution is evaluated for all tested cases. A qualitative investigation of reconstruction performance for each case is presented. Following this, we define a set of measures on the quantitative evaluation for a range of resolutions including separation, size, contrast, and location, thereby providing a comparable evaluation to the visual quality. The most satisfactory result is obtained by using the wavelet HP filter, and it successfully justifies our proposed scheme.
Near-infrared diffuse optical tomography (NIR DOT) for noninvasive tissue monitoring have been developed for nearly
two decades. The NIR imaging, however, suffers from low resolution due to the diffusive nature of the scattered light;
there are compelling reasons for merging high-resolution structural information from other imaging modalities with the
functional information attainable with NIR DOT. In this article, slight variation of the inclusion (tumor) in low contrast
of optical properties is estimated and investigated. We present that an initial study of using a structural <i>a priori</i>knowledge in NIR tomography where absorption image reconstruction of the tested phantom is well defined with the aid
of a structural a priori knowledge obtained from other imaging modalities. This is advantageous compared to either
modality alone. As well, the reconstructed optical absorption coefficient is achieved more accurate near to be exact
value with incorporating the empirical updating information being proportional to the off-boundary distance but not size
of inclusion against the background. Numerical simulation is demonstrated on varied sizes, locations and contrast of the
inclusion. With the comparison between with or without <i>a priori </i>and empirical updating information, it is found that the
reconstructed optical properties are more accurate than the near-infrared imaging alone.
Diffuse optical tomography (DOT) is in an attempt to image the interior of human tissues. However, the NIR imaging
suffers from low resolution due to the diffusive nature of the scattered light, which results into poor reconstructed image
quality. Thus, the effort to improve the image quality remains in progress. The numerical simulation using high-pass
filtering incorporated into the finite-element-based diffusion equation to reconstruct tomographic images of optical
properties was performed where results reveal that several inclusions (tumors) can be well defined separately, thereby
demonstrating the ability to highly resolve the image of interest with the optimal high-pass filtering process.
The study aims at developing a near infrared (NIR) tomography imaging system using a single rotating source/detector scanning device, which will be working for diffuse optical tomography (DOT) on medical applications. Some influential factors in terms of the design of this scanning device and test phantoms are investigated such as the temporal stability, air-absorption, container influence, and radiance normalization, etc. Then, a heterogeneous microsphere phantom with an off-center inclusion is investigated. It is observed that the radiance deviation between the heterogeneous and the homogenous is shifting with the inclusion position accordingly. Through the previously-mentioned system calibration, the back projection method as widely applied in the computed tomography (CT) technique is used to reconstruct optical images which indicate the distribution of optical property of the test phantom.
In the research, the pseudo-model technique is proposed and implemented to simulate biological tissues under the framework of investigating near infrared (NIR) light propagating in diffusive media. The same optical characteristics inhere in the corresponding pseudo-models as in real tissues, where pseudo-models are constructed by using various volume densities of Intralipid. The pseudo-model technique proposed in the study has following advantages:
1.For the NIR tomography imaging system, the output signal from the real tissue may be too weak to be detected beyond the ability of current technologies. Thus, the pseudo-model is a viable alternative to cope with the limitation of the system in the measurement of real tissues.
2.Once the pseudo-model of a real tissue is decided, its optical properties can be investigated thoroughly. In addition, the initial estimates for the reconstruction of NIR optical property images can be selected adequately, and the image reconstruction algorithm can be modified accordingly with the information acquired from the pseudo-model.
In the experiment, a pseudo-model of the background with an inclusion is performed for real tissues of pork inserted by a bone. It is observed that 1 % v.d. and 3 % v.d. of Intralipids can replace the pork and the bone, respectively, and the characteristics of the pseudo-model proposed here are consistent with those of the real tissues. As part of conclusion, the use of the pseudo-model technique is a promising approach to mimicking real tissues, especially for some parts of human body unable to be detected effectively.
Diffuse optical tomography (DOT) using diffuse light, red or near-infrared (NIR) light, is in an attempt to image the interior of human tissues such as breasts, arms, etc. In the current design of our NIR tomography imaging system, the system uses a single rotating source/detector scanning device associated with an image reconstruction scheme. The device can dramatically save source- and detection-fiber-bundles, and offer promising measured radiance reflecting the optical properties of the test phantoms. Both source and detector can rotate on command with any pre-defined angles controlled by the computer. Additionally, an image reconstruction algorithm applied to the tomography scanning device in the DC domain is also implemented. The ability and performance of this image reconstruction algorithm are discussed and presented. Results reveal that inclusion (tumor) positions can be well defined and the spatial resolution is beyond 1:16, inclusion to background.
The research aims at developing an NIR tomography system using a single rotating source/detector scanning device associated with an image reconstruction scheme. Several simulation results concerning the phantom with one, two or three targets are presented. Additionally, the developed system is validated by a hemoglobin phantom inserted by another different volume density one.