From Compressed-Sensing to Deep Learning MR: Comparative Biventricular Cardiac Function Analysis in a Patient Cohort.

Abstract

Authors

• Xianghu Yan
  Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
• Yi Luo
  Electrical and Computer Engineering Department, Bioengineering Department, University of California, Los Angeles, CA 90095 USA, and also with the California NanoSystems Institute, University of California, Los Angeles, CA 90095 USA.
• Xiao Chen
• Eric Z Chen
  United Imaging Intelligence, Cambridge, Massachusetts, USA.
• Qi Liu
  National Institute of Traditional Chinese Medicine Constitution and Preventive Medicine, Beijing University of Chinese Medicine, Beijing, China.
• Lixian Zou
  Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, Guangdong, China.
• Yuwei Bao
  Department of Computer Science and Engineering, University of Michigan, Ann Arbor, 48109, MI, USA.
• Lu Huang
  School of Food Science and Technology, Dalian Polytechnic University, National Engineering Research Center of Seafood, Dalian 116034, PR China.
• Liming Xia
  From the Department of Radiology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, the Netherlands (Q.T., E.H.M.P., D.P.S., A.d.R., H.J.L., R.J.v.d.G.); Department of Electrical Engineering, Fudan University, Shanghai, China (W.Y., Y.W.); Multidisciplinary Cardiovascular Research Centre & Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, England (P.G., S.P.); Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (L.H., L.X.); and Departments of Cardiology (M.S.) and Radiology (J.T.), Institute for Clinical and Experimental Medicine, Prague, Czech Republic.

Keywords

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