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Synthetic X-Q space learning for diffusion MRI parameter estimation: a pilot study in breast DKI.

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Bibliographic Details
Title: Synthetic X-Q space learning for diffusion MRI parameter estimation: a pilot study in breast DKI.
Authors: Masutani Y; Department of Medical Image Computation, Tohoku University Graduate School of Medicine, Sendai, Japan. yoshitaka.masutani.a8@tohoku.ac.jp., Konya K; Department of Medical Image Computation, Tohoku University Graduate School of Medicine, Sendai, Japan., Kato E; Department of Diagnostic Radiology, Tohoku University Hospital, Sendai, Japan., Mori N; Department of Radiology, Akita University Graduate School of Medicine, Akita, Japan.; Division of Image Statistics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan., Ota H; Department of Diagnostic Radiology, Tohoku University Hospital, Sendai, Japan., Mugikura S; Division of Image Statistics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan., Takase K; Department of Diagnostic Radiology, Tohoku University Hospital, Sendai, Japan., Ichinoseki Y; Department of Medical Image Computation, Tohoku University Graduate School of Medicine, Sendai, Japan.
Source: International journal of computer assisted radiology and surgery [Int J Comput Assist Radiol Surg] 2025 Dec; Vol. 20 (12), pp. 2423-2435. Date of Electronic Publication: 2025 Nov 24.
Publication Type: Journal Article
Journal Info: Publisher: Springer Country of Publication: Germany NLM ID: 101499225 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1861-6429 (Electronic) Linking ISSN: 18616410 NLM ISO Abbreviation: Int J Comput Assist Radiol Surg Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1861-6429
DOI:10.1007/s11548-025-03550-7