文章基本信息

标题：An SCADTV Nonconvex Regularization Approach for Magnetic Resonance Imaging
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作者：Zhijun Luo ; Zhibin Zhu ; Benxin Zhang 等
期刊名称：IAENG International Journal of Computer Science
印刷版ISSN：1819-656X
电子版ISSN：1819-9224
出版年度：2021
卷号：48
期号：4
语种：English
出版社：IAENG - International Association of Engineers
摘要：In this paper, we propose a non-convex regularization magnetic resonance imaging (MRI) reconstruction model via the smoothly clipped absolute deviation (SCAD) penalty function, which can effectively improve the fitting performance and prevent systematic underestimation compared with the classical total variation (TV) regularization. Then, we choose the alternating direction method of multipliers (ADMM) algorithm to solve the non-convex regularization model. The experiment results show that the efficiency of the proposed model and algorithm in comparison with some other typical methods.
关键词：MRI reconstruction;TV regularization;SCAD penalty function;ADMM