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Deep-learning reconstruction enables about one minute 3D T1-weighted MRI: quantitative evaluation of Acceleration-quality Trade-offs and motion reduction.

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Title: Deep-learning reconstruction enables about one minute 3D T1-weighted MRI: quantitative evaluation of Acceleration-quality Trade-offs and motion reduction.
Authors: Watanabe K; Department of Radiology, Kyoto Prefectural University of Medicine, Kyoto, Japan. kw0928@koto.kpu-m.ac.jp.; Department of Radiology, Hirosaki University, Hirosaki, Japan. kw0928@koto.kpu-m.ac.jp., Oyu K; Department of Radiology, Hirosaki University, Hirosaki, Japan., Kasai S; Department of Radiology, Hirosaki University, Hirosaki, Japan., Saito K; Department of Radiology, Hirosaki University, Hirosaki, Japan., Shintaku T; Department of Radiology, Hirosaki University, Hirosaki, Japan., Kakehata S; Department of Radiology, Hirosaki University, Hirosaki, Japan., Tsushima F; Department of Radiology, Hirosaki University, Hirosaki, Japan., Nozaki A; GE Healthcare, Hino, Japan., Zhu X; GE healthcare, Menlo Park, United States., Wakayama T; GE Healthcare, Hino, Japan., Kakeda S; Department of Radiology, Hirosaki University, Hirosaki, Japan.
Source: Neuroradiology [Neuroradiology] 2026 May; Vol. 68 (5), pp. 1377-1385. Date of Electronic Publication: 2025 Nov 22.
Publication Type: Journal Article
Journal Info: Publisher: Springer-Verlag Country of Publication: Germany NLM ID: 1302751 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1432-1920 (Electronic) Linking ISSN: 00283940 NLM ISO Abbreviation: Neuroradiology Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1432-1920
DOI:10.1007/s00234-025-03846-0