Joint sparsity and fidelity regularization for segmentation-driven CT image preprocessing

Abstract

In this paper, we propose a novel segmentation-driven computed tomography (CT) image preprocessing approach. The proposed approach, namely, joint sparsity and fidelity regularization (JSFR) model can be regarded as a generalized total variation (TV) denoising model or a generalized sparse representation denoising model by adding an additional gradient… (More)
DOI: 10.1007/s11432-015-5375-x

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