Robust dynamic myocardial perfusion CT deconvolution using adaptive-weighted tensor total variation regularization

Changfei Gong; Dong Zeng; Zhaoying Bian; Jing Huang; Xinyu Zhang; Hua Zhang; Lijun Lu; Qianjin Feng; Zhengrong Liang; Jianhua Ma

doi:10.1117/12.2217351

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30 March 2016 Robust dynamic myocardial perfusion CT deconvolution using adaptive-weighted tensor total variation regularization

Changfei Gong, Dong Zeng, Zhaoying Bian, Jing Huang, Xinyu Zhang, Hua Zhang, Lijun Lu, Qianjin Feng, Zhengrong Liang, Jianhua Ma

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Proceedings Volume 9783, Medical Imaging 2016: Physics of Medical Imaging; 97833D (2016) https://doi.org/10.1117/12.2217351
Event: SPIE Medical Imaging, 2016, San Diego, California, United States

Abstract

Dynamic myocardial perfusion computed tomography (MPCT) is a promising technique for diagnosis and risk stratification of coronary artery disease by assessing the myocardial perfusion hemodynamic maps (MPHM). Meanwhile, the repeated scanning of the same region results in a relatively large radiation dose to patients potentially. In this work, we present a robust MPCT deconvolution algorithm with adaptive-weighted tensor total variation regularization to estimate residue function accurately under the low-dose context, which is termed `MPD-AwTTV'. More specifically, the AwTTV regularization takes into account the anisotropic edge property of the MPCT images compared with the conventional total variation (TV) regularization, which can mitigate the drawbacks of TV regularization. Subsequently, an effective iterative algorithm was adopted to minimize the associative objective function. Experimental results on a modified XCAT phantom demonstrated that the present MPD-AwTTV algorithm outperforms and is superior to other existing deconvolution algorithms in terms of noise-induced artifacts suppression, edge details preservation and accurate MPHM estimation.

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Changfei Gong, Dong Zeng, Zhaoying Bian, Jing Huang, Xinyu Zhang, Hua Zhang, Lijun Lu, Qianjin Feng, Zhengrong Liang, and Jianhua Ma "Robust dynamic myocardial perfusion CT deconvolution using adaptive-weighted tensor total variation regularization", Proc. SPIE 9783, Medical Imaging 2016: Physics of Medical Imaging, 97833D (30 March 2016); https://doi.org/10.1117/12.2217351

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