Positive Semidefinite Generalized Diffusion Tensor Imaging via Quadratic Semidefinite Programming

来源 :International Conference on the spectral theory of the tenso | 被引量 : 0次 | 上传用户：cnanjr

【摘要】

：

　　Keeping the positive definiteness of a diffusion tensor is important in magnetic resonance imaging (MRI) because it reflects the phenomenon of water molecul

【作者】

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Wenyu Sun

【机构】

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NanjingNormalUniversity

【出处】

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International Conference on the spectral theory of the tenso

【发表日期】

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2012年5期

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　　Keeping the positive definiteness of a diffusion tensor is important in magnetic resonance imaging (MRI) because it reflects the phenomenon of water molecular diffusion in complicated biological tissues environment.To preserve this property,we represent it as an explicit positive semidefinite (PSD) matrix constraint and some linear matrix equalities.The objective function is the regularized linear least squares fitting for the log-linearized Stejskal-Tanner equation.The regularization term is the nuclear norm of the PSD matrix.

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Positive Semidefinite Generalized Diffusion Tensor Imaging via Quadratic Semidefinite Programming

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