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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 direction field on cortical surface conveys important information. Diffusion of direction field, which aims to smooth noise and meanwhile preserve major geometric structures and inherent discontinuity in the direction field, is useful for cortical surface analysis. In this paper, we propose a novel method for tangential direction field diffusion on cortical surface, which is formulated as an energy...
Due to complexity and irregulation of each encephalic tissue boundary, three-dimensional (3D) reconstruction for MRI image has been a hot area. Support vector machine (SVM) based on statistical learning theory is mainly utilized in classification and regression. One Class SVM (OCSVM) was originally proposed for solving some special classification problems. In this paper, OCSVM, which tries to find...
Reconstruction of the geometric central surface of the human cerebral cortex is an important means to study the structure and function of the brain cortex. In this paper, we propose a novel method based on an elastic deformable transform vector field to drive a deformable model for the reconstruction of the central surface of the brain cortex. In addition, simulated brain cortexes are generated to...
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