Deep Learning-based Image Enhancement Techniques for Fast MRI in Neuroimaging-Reference-Cited by-同舟云学术

Deep Learning-based Image Enhancement Techniques for Fast MRI in Neuroimaging

Published:2024 Issue:3 Volume:23 Page:341-351
ISSN:1347-3182
Container-title:Magnetic Resonance in Medical Sciences
language:en
Short-container-title:MRMS

Author:

Yoo Roh-Eul¹²,Choi Seung Hong¹²³⁴

Affiliation:

1. Department of Radiology, National Cancer Center, Goyang-si, Republic of Korea

2. Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea

3. Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea

4. Center for Nanoparticle Research, Institute for Basic Science (IBS), Seoul, Republic of Korea

Funder

AIRS Medical Inc.

National Research Foundation of Korea

Institute for Basic Science

Samsung Research Funding & Incubation Center of Samsung Electronics

SNUH Research Fund

Publisher

Japanese Society for Magnetic Resonance in Medicine

Link

https://www.jstage.jst.go.jp/article/mrms/23/3/23_rev.2023-0153/_pdf

Reference53 articles.

1. 1. Andre JB, Bresnahan BW, Mossa-Basha M, et al. Toward quantifying the prevalence, severity, and cost associated with patient motion during clinical MR examinations. J Am Coll Radiol 2015; 12:689–695.

2. 2. Kobelt G, Berg J, Atherly D, Hadjimichael O. Costs and quality of life in multiple sclerosis: A cross-sectional study in the United States. Neurology 2006; 66:1696–1702.

3. 3. OECD. Magnetic resonance imaging (MRI) exams. https://data.oecd.org/healthcare/magnetic-resonance-imaging-mri-exams.htm (Accessed: Nov 15, 2023)

4. 4. Sodickson DK, Manning WJ. Simultaneous acquisition of spatial harmonics (SMASH): Fast imaging with radiofrequency coil arrays. Magn Reson Med 1997; 38:591–603.

5. 5. Pruessmann KP, Weiger M, Scheidegger MB, Boesiger P. SENSE: sensitivity encoding for fast MRI. Magn Reson Med 1999; 42:952–962.

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Advanced Techniques for MR Neuroimaging;Magnetic Resonance in Medical Sciences;2024