Deep learning with domain adaptation for accelerated projection-reconstruction MR-Reference-Cited by-同舟云学术

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Deep learning with domain adaptation for accelerated projection-reconstruction MR

Published:2018-02-04 Issue:3 Volume:80 Page:1189-1205
ISSN:0740-3194
Container-title:Magnetic Resonance in Medicine
language:en
Short-container-title:Magn. Reson. Med

Author:

Han Yoseob¹,Yoo Jaejun¹,Kim Hak Hee²,Shin Hee Jung²,Sung Kyunghyun³,Ye Jong Chul¹

Affiliation:

1. Department of Bio and Brain Engineering; Korea Advanced Institute of Science & Technology (KAIST); Daejeon Republic of Korea

2. Department of Radiology; Research Institute of Radiology, Asan Medical Center, College of Medicine, University of Ulsan; Seoul Republic of Korea

3. Department of Radiological Sciences; University of California Los Angeles; Los Angeles California

Funder

National Institute of Biomedical Imaging and Bioengineering

National Research Foundation of Korea

NIH Blueprint Initiative for Neuroscience Research

National Institutes of Health

Publisher

Wiley

Subject

Radiology, Nuclear Medicine and imaging

Reference47 articles.

1. Reduction of flow artifacts in NMR diffusion imaging using view-angle tilted line-integral projection reconstruction;Jung;Magn Reson Med.,1991

2. Use of a projection reconstruction method to decrease motion sensitivity in diffusion-weighted MRI;Gmitro;Magn Reson Med.,1993

3. MR coronary vessel wall imaging: Comparison between radial and spiral k-space sampling;Katoh;J Magn Reson Imaging.,2006

4. Analysis and comparison of motion-correction techniques in diffusion-weighted imaging;Trouard;J Magn Reson Imaging.,1996

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