Convolutional Sparse Coding for Compressed Sensing CT Reconstruction

Over the past few years, dictionary learning (DL)-based methods have been successfully used in various image reconstruction problems. However, the traditional DL-based computed tomography (CT) reconstruction methods are patch-based and ignore the consistency of pixels in overlapped patches. In addit...

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Veröffentlicht in:	IEEE transactions on medical imaging Jg. 38; H. 11; S. 2607 - 2619
Hauptverfasser:	Bao, Peng, Sun, Huaiqiang, Wang, Zhangyang, Zhang, Yi, Xia, Wenjun, Yang, Kang, Chen, Weiyan, Chen, Mianyi, Xi, Yan, Niu, Shanzhou, Zhou, Jiliu, Zhang, He
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.11.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Coding Compressed sensing compressed sensing CT reconstruction Computed tomography Computer simulation Convolutional codes convolutional sparse coding Dictionaries Image coding Image processing Image reconstruction Medical imaging Objective function Signal processing
ISSN:	0278-0062, 1558-254X, 1558-254X
Online-Zugang:	Volltext
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