MR Fingerprinting and Complex-Valued Neural Network for Amyloid Quantification : A Voxel-Wise Approach [Presidential Award Proceedings]
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- FUJITA Shohei
- Department of Radiology, Juntendo University Department of Radiology, The University of Tokyo
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- OTSUKA Yujiro
- Department of Radiology, Juntendo University Milliman Inc. Plusman LLC.
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- MURATA Katsutoshi
- Siemens Healthcare Japan K.K.
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- KOERZDOERFER Gregor
- Siemens Healthcare GmbH
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- NITTKA Mathias
- Siemens Healthcare GmbH
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- MOTOI Yumiko
- Medical Center for Dementia, Juntendo University
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- NAKAJIMA Madoka
- Medical Center for Dementia, Juntendo University
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- MURAKAMI Koji
- Department of Radiology, Juntendo University
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- BILGIC Berkin
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital Department of Radiology, Harvard Medical School Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology
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- FUKUNAGA Issei
- Department of Radiology, Juntendo University
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- KAMAGATA Koji
- Department of Radiology, Juntendo University
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- ABE Osamu
- Department of Radiology, The University of Tokyo
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- AOKI Shigeki
- Department of Radiology, Juntendo University
Bibliographic Information
- Other Title
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- MR fingerprintingと複素数ニューラルネットワークによる非侵襲アミロイドマッピングに向けて［大会長賞記録］
Abstract
<p> Synopsis : We developed a framework that quantifies voxel-level amyloid burden in the brain with MR fingerprinting (MRF) and neural networks. The neural network was trained voxel-wise on in vivo amyloid-PET imaging data and MRF acquisitions to estimate PET-derived amyloid deposition from the signal evolution.</p>
Journal
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- Japanese Journal of Magnetic Resonance in Medicine
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Japanese Journal of Magnetic Resonance in Medicine 43 (2), 66-68, 2023-05-15
Japanese Society for Magnetic Resonance in Medicine
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Details 詳細情報について
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- CRID
- 1390296376261972736
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- ISSN
- 24340499
- 09149457
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- Text Lang
- ja
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- Data Source
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- JaLC
- Crossref
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- Abstract License Flag
- Disallowed