Enhanced Visualization of Intracranial Cortical Arteries Using Deep Learning Reconstruction in Vessel Wall MR Imaging.

Saved in:
Bibliographic Details
Title: Enhanced Visualization of Intracranial Cortical Arteries Using Deep Learning Reconstruction in Vessel Wall MR Imaging.
Authors: Ide S; Department of Radiology, University of Occupational and Environmental Health, School of Medicine, Kitakyushu, Fukuoka, Japan., Futatsuya K; Department of Radiology, University of Occupational and Environmental Health, School of Medicine, Kitakyushu, Fukuoka, Japan., Yoshimatsu Y; Department of Radiology, University of Occupational and Environmental Health, School of Medicine, Kitakyushu, Fukuoka, Japan., Sakamoto T; Department of Radiology, University of Occupational and Environmental Health, School of Medicine, Kitakyushu, Fukuoka, Japan., Kajio K; Department of Radiology, University of Occupational and Environmental Health, School of Medicine, Kitakyushu, Fukuoka, Japan., Inoue H; Department of Radiology, University of Occupational and Environmental Health, School of Medicine, Kitakyushu, Fukuoka, Japan., Ogawa N; Department of Radiology, University of Occupational and Environmental Health, School of Medicine, Kitakyushu, Fukuoka, Japan., Murakami Y; Department of Radiology, University of Occupational and Environmental Health, School of Medicine, Kitakyushu, Fukuoka, Japan., Aoki T; Department of Radiology, University of Occupational and Environmental Health, School of Medicine, Kitakyushu, Fukuoka, Japan.
Source: Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine [Magn Reson Med Sci] 2026 Feb 26; Vol. 25 (1). Date of Electronic Publication: 2025 Nov 22.
Publication Type: Journal Article
Journal Info: Publisher: Japan Society of Magnetic Resonance in Medicine Country of Publication: Japan NLM ID: 101153368 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1880-2206 (Electronic) Linking ISSN: 13473182 NLM ISO Abbreviation: Magn Reson Med Sci Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1880-2206
DOI:10.2463/mrms.tn.2025-0091