Deep Learning-Based Brainstem Segmentation and Multi-Class Classification for Parkinsonian Syndrome.

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Bibliographic Details
Title: Deep Learning-Based Brainstem Segmentation and Multi-Class Classification for Parkinsonian Syndrome.
Authors: Kim S; Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea., Suh PS; Department of Radiology, Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Republic of Korea., Shim WH; Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea., Heo H; Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea., Park C; VUNO Inc., Seoul, Republic of Korea., Hong E; VUNO Inc., Seoul, Republic of Korea., Kim S; VUNO Inc., Seoul, Republic of Korea., Lee SH; VUNO Inc., Seoul, Republic of Korea., Lee D; VUNO Inc., Seoul, Republic of Korea., Jung W; VUNO Inc., Seoul, Republic of Korea., Kim J; VUNO Inc., Seoul, Republic of Korea., Jo S; Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea., Chung SJ; Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea., Sung YH; Department of Neurology, Gil Medical Center, Gachon University School of Medicine, Seoul, Republic of Korea., Kim HS; Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea., Kim SJ; Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea., Kim EY; Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea., Suh CH; Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Source: Journal of magnetic resonance imaging : JMRI [J Magn Reson Imaging] 2026 Apr; Vol. 63 (4), pp. 1108-1121. Date of Electronic Publication: 2025 Dec 24.
Publication Type: Journal Article
Journal Info: Publisher: Wiley-Liss Country of Publication: United States NLM ID: 9105850 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1522-2586 (Electronic) Linking ISSN: 10531807 NLM ISO Abbreviation: J Magn Reson Imaging Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1522-2586
DOI:10.1002/jmri.70215