Artifact-robust Deep Learning-based Segmentation of 3D Phase-contrast MR Angiography: A Novel Data Augmentation Approach.
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| Title: | Artifact-robust Deep Learning-based Segmentation of 3D Phase-contrast MR Angiography: A Novel Data Augmentation Approach. |
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| Authors: | Tamada D; Radiology, University of Wisconsin-Madison, Madison WI, USA., Oechtering TH; Radiology, University of Wisconsin-Madison, Madison WI, USA.; Department of Radiology, Universität zu Lübeck, Lübeck Schleswig-Holstein, Germany., Heidenreich JF; Radiology, University of Wisconsin-Madison, Madison WI, USA., Starekova J; Radiology, University of Wisconsin-Madison, Madison WI, USA., Takai E; MIRAI Technology Institute, Shiseido, Yokohama Kanagawa, Japan., Reeder SB; Radiology, University of Wisconsin-Madison, Madison WI, USA.; Medical Physics, University of Wisconsin-Madison, Madison WI, USA.; Biomedical Engineering, University of Wisconsin-Madison, Madison WI, USA.; Medicine, University of Wisconsin-Madison, Madison WI, USA.; Emergency, University of Wisconsin-Madison, Madison WI, USA. |
| Source: | Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine [Magn Reson Med Sci] 2025 Dec 25; Vol. 24 (4). Date of Electronic Publication: 2025 Jul 05. |
| 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 |
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