An Adaptive Directional Haar Framelet-Based Reconstruction Algorithm for Parallel Magnetic Resonance Imaging
Publication in refereed journal

香港中文大學研究人員

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摘要Parallel magnetic resonance imaging (pMRI) is a technique to accelerate the magnetic resonance imaging process. The problem of reconstructing an image from the collected pMRI data is ill-posed. Regularization is needed to make the problem well-posed. In this paper, we first construct a two-dimensional tight framelet system whose filters have the same support as the orthogonal Haar filters and are able to detect edges of an image in the horizontal, vertical, and +/- 45 degrees directions. This system is referred to as directional Haar framelet (DHF). We then propose a pMRI reconstruction model whose regularization term is formed by the DHF. This model is solved by a fast proximal algorithm with low computational complexity. The regularization parameters are updated adaptively and determined automatically during the iteration of the algorithm. Numerical experiments for in-silico and in-vivo data sets are provided to demonstrate the superiority of the DHF-based model and the efficiency of our proposed algorithm for pMRI reconstruction.
著者Yan-Ran Li, Raymond H. Chan, Lixin Shen, Yung-Chin Hsu, Wen-Yih Isaac Tseng
期刊名稱SIAM Journal on Imaging Sciences
出版年份2016
月份2
日期1
卷號9
期次2
出版社SIAM PUBLICATIONS
出版地United Kingdom
頁次794 - 821
國際標準期刊號1936-4954
語言英式英語
關鍵詞parallel MRI, Haar wavelet system, proximity operator, total variation, tight frame
Web of Science 學科類別Computer Science, Artificial Intelligence;Computer Science, Software Engineering;Mathematics, Applied;Imaging Science & Photographic Technology;Computer Science;Mathematics;Imaging Science & Photographic Technology

上次更新時間 2020-11-10 於 00:38