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In this paper, we investigate the classification of masses with texture features. We propose an improved level set method to find the boundary of a mass, based on the initial contour provided by radiologists. After the boundary of a mass is found, texture features from Gray Level Co-occurrence Matrix (GLCM) are extracted from the surrounding area of the boundary of the mass. The extracted texture...
The finite element method (FEM) geometry modeling of realistic head volume conductor plays an important role in FEM-based EEG/MEG forward and inverse problems. In this paper, a tetrahedron mesh generation method was developed for finite element modeling of human head. By using this method, a finite element model of human head is obtained from segmented medical images, and tested in application to...
The finite element (FE) modeling of a realistic head is a key issue for the finite element analysis of brain electromagnetic field. In the present study, we have developed a new method to generate subject specific FE head models based on their magnetic resonance (MR) and computer tomography (CT) imaging data. The present approach consists of three parts: segmentation of MR and CT images, co-registration...
Noise reduction is an important image processing method which has wide applications in different fields. The key to noise reduction is to reduce the noise without deteriorating the important features in the images. Anisotropic diffusion filter is one of the methods which satisfy this need and draws much attention from researchers in the past. However, traditional anisotropic diffusion filter has many...
Electron tomography is a method for three-dimensional reconstruction of a specimen, based on its electron microscopical projections which are produced by tilting the specimen in the microscope about a fixed axis. After determining a common coordinate frame, a tomogram is computed by weighted backprojection. Higher resolution can be obtained by applying a contrast transfer function (CTF) correction...
The FEM geometry modeling of realistic head is a key issue for the research on FEM-based EEG/MEG. In this paper, a methodology is developed to construct this kind of model. By using this method, a five -layer realistic head FEM model is obtained, and with its application in FEM-based EEG, a satisfying result shows the reliability of the model
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