Equilibrated Zeroth-Order Unrolled Deep Network for Parallel MR Imaging-Reference-Cited by-同舟云学术

Equilibrated Zeroth-Order Unrolled Deep Network for Parallel MR Imaging

Published:2023-12 Issue:12 Volume:42 Page:3540-3554
ISSN:0278-0062
Container-title:IEEE Transactions on Medical Imaging
language:
Short-container-title:IEEE Trans. Med. Imaging

Author:

Cui Zhuo-Xu¹^ORCID,Jia Sen²,Cheng Jing²^ORCID,Zhu Qingyong¹^ORCID,Liu Yuanyuan³^ORCID,Zhao Kankan¹,Ke Ziwen⁴^ORCID,Huang Wenqi⁵,Wang Haifeng²^ORCID,Zhu Yanjie²^ORCID,Ying Leslie⁶^ORCID,Liang Dong¹^ORCID

Affiliation:

1. Research Center for Medical AI, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

2. Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

3. National Innovation Center for Advanced Medical Devices, Shenzhen, China

4. Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China

5. Institutes of Radiology and Artificial Intelligence and Informatics in Medicine, Technical University of Munich, Munich, Germany

6. Department of Biomedical Engineering and the Department of Electrical Engineering, The State University of New York, Buffalo, NY, USA

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Natural Science Foundation of Guangdong Province, China

Shenzhen Outstanding Talents Training Fund;

Shenzhen Key Laboratory of Ultrasound Imaging and Therapy

Shenzhen Peacock Plan Team Program

Innovation and Technology Commission of the Government of Hong Kong SAR

Strategic Priority Research Program of Chinese Academy of Sciences

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Radiological and Ultrasound Technology,Software

Link

http://xplorestaging.ieee.org/ielx7/42/10336247/10177777.pdf?arnumber=10177777

Reference53 articles.

1. Deep low-Rank plus sparse network for dynamic MR imaging

2. Deep Magnetic Resonance Image Reconstruction: Inverse Problems Meet Neural Networks

3. Learned Low-Rank Priors in Dynamic MR Imaging

4. Learning Data Consistency and its Application to Dynamic MR Imaging

5. A Mathematical Introduction to Compressive Sensing

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