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It is more difficult to remove the noise and keep the edge information in the same time in the brain MR image than the ordinary image since the boundaries of encephalic tissue are highly complicated. As one kind of the multi-scale and multi-directional geometrical analysis method, the Contourlet Transform (CT) is an optimal representation of the contour and texture information in an image and overcomes...
In the brain MR images, the boundary of each encephalic tissue is highly irregular. Traditional 3-D reconstruction algorithms are challenged. Owing to its powerful capacity in solving nonlinearity problems, the sphere-shaped support vector machines (SSSVMs) is applied in the 3-D reconstruction. Selecting parameters for SSSVM and the kernel function, however, is a complicated issue. Appropriate parameters...
The Infrared images have been applied in clinical diagnoses, but the images are noisy and blurred. Therefore the smooth processing that can keep edges is needed. Traditional smoothing methods have the common defect that they smooth not only the noise region but also the edges. AMSS (affine morphological scale space) algorithm can be used to better save the edge information, it has the Partial Differential...
The infrared imaging technique can be used to image the temperature distribution of the body. It's hopeful to be applied to the diagnosis and prediction of many diseases. Image processing is necessary to enhance the original infrared images because of the blurring. In this paper, the image enhancement technique based on the Retinex theory is studied. The algorithms such as Frackle-McCann algorithm,...
MITK supports an extensive set of image processing and volume rendering functionality, and it is a very convenient tool. 3-D reconstruction of the liver is performed by MITK under VC++ 6.0 platform. Compared with 3-D reconstruction results by Amira, good surface image of liver could be obtained by MITK. The 3-D reconstruction image of liver can be used for finite element analysis and temperature field...
Denoising is an important step for image processing. One of the most important characteristics of MRI (MRI) is the complicated changes of gray level. For MRI, preservation of useful information is more important than simple improvement of Signal-Noise Ratio (SNR). Traditional filtering algorithms are not fit for MRI. Adaptive Template Filtering Method (ATFM) can dynamically match the best template...
Intelligent Optimization Algorithm (IOA) mainly includes Immune Algorithm (IA) and Genetic Algorithm (GA). One of the most important characteristics of MRI is the complicated changes of gray level. Traditional filtering algorithms are not fit for MRI. Adaptive Template Filtering Method (ATFM) is an appropriate denoising method for MRI. However, selecting threshold for ATFM is a complicated problem...
Denoising is an important step for image processing. One of the most important characteristics of MRI (MRI) is the complicated changes of gray level. For MRI, preservation of useful information is more important than simple improvement of Signal-Noise Ratio (SNR). Traditional filtering algorithms are not fit for MRI. Adaptive Template Filtering Method (ATFM) can dynamically match the best template...
Intelligent Optimization Algorithm (IOA) mainly includes Immune Algorithm (IA) and Genetic Algorithm (GA). One of the most important characteristics of MRI is the complicated changes of gray level. Traditional filtering algorithms are not fit for MRI. Adaptive Template Filtering Method (ATFM) is an appropriate denoising method for MRI. However, selecting threshold for ATFM is a complicated problem...
Electrical impedance tomography (EIT) is a noninvasive technique that permits estimation of resistivity within a subject by reconstructing from boundary measurements. The head electrical properties based on EIT technology have been studied by many authors and in most of this work the realistic head model has been considered without contact impedance between the electrodes and the scalp. It is interesting...
Support vector machine (SVM) can be seen as a new machine learning way which is based on the idea of VC dimensions and the principle of structural risk minimization rather than empirical risk minimization. SVM can be used for classification and regression. Support vector regression (SVR) is a very important branch of Support vector machine. Partial differential equations (PDEs) have been successfully...
The modified Newton-Raphson (MNR) method is used to solve the inverse resistivity problem in this paper. Using Tikhonov regularization method, comparisons among the L-curve method, the zero-crossing (ZC) method and the generalized cross validation (GCV) method are carried out for determining the regularization parameters of MNR method. By these criterions the appropriate regularization parameters...
Electrical impedance tomography (EIT) is a noninvasive technique to estimate the conductivity distribution inside the object. In EIT, driving currents are injected through the object and voltages are measured at the electrodes on the surface. Algorithms to estimate the conductivity distribution from the measured voltages are called reconstruction algorithms. Image reconstruction is a nonlinear inverse...
Three EIT approaches for static imaging of head are investigated in this paper. The modified Newton-Raphson (MNR) method and the differential evolution (DE) algorithm are applied to the impedance reconstruction of 2D section of head based on real head model. Comparisons are carried out on the results obtained using simulated data, and a DE-MNR combination method is proposed, which demonstrated high...
Electrical impedance tomography (EIT) is a newly developed technique by which impedance measurements from the surface of an object are reconstructed into impedance image. But in the initial stage, the EIT problem is regarded as the two-dimensional EIT problem, which ignores too much important information and makes it can't give the exact spatial information of the place where the impedance has changed...
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