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Computational Diffusion MRI : MICCAI Workshop, Shenzhen, China, October 2019 / edited by Elisenda Bonet-Carne, Jana Hutter, Marco Palombo, Marco Pizzolato, Farshid Sepehrband, Fan Zhang
(Mathematics and Visualization. ISSN:2197666X)
版 | 1st ed. 2020. |
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出版者 | (Cham : Springer International Publishing : Imprint: Springer) |
出版年 | 2020 |
本文言語 | 英語 |
大きさ | XI, 210 p. 78 illus., 64 illus. in color : online resource |
著者標目 | Bonet-Carne, Elisenda editor Hutter, Jana editor Palombo, Marco editor Pizzolato, Marco editor Sepehrband, Farshid editor Zhang, Fan editor SpringerLink (Online service) |
件 名 | LCSH:Biomathematics LCSH:Numerical analysis LCSH:Computer science -- Mathematics 全ての件名で検索 LCSH:Computer vision LCSH:Artificial intelligence FREE:Mathematical and Computational Biology FREE:Numerical Analysis FREE:Mathematical Applications in Computer Science FREE:Computer Vision FREE:Artificial Intelligence |
一般注記 | Diffusion MRI signal acquisition and processing strategies -- Machine learning for diffusion MRI -- Combined diffusion-relaxometry MRI This volume gathers papers presented at the Workshop on Computational Diffusion MRI (CDMRI 2019), held under the auspices of the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), which took place in Shenzhen, China on October 17, 2019. This book presents the latest advances in the rapidly expanding field of diffusion MRI. It shares new perspectives on the latest research challenges for those currently working in the field, but also offers a valuable starting point for anyone interested in learning about computational techniques in diffusion MRI. The book includes rigorous mathematical derivations, a wealth of rich, full-colour visualisations and extensive clinically relevant results. As such, it will be of interest to researchers and practitioners in the fields of computer science, MRI physics and applied mathematics. Readers will find contributions covering a broad range of topics, from the mathematical foundations of the diffusion process and signal generation, to new computational methods and estimation techniques for the in vivo recovery of microstructural and connectivity features, as well as diffusion-relaxometry and frontline applications in research and clinical practice. This edition includes invited works from high-profile researchers with a specific focus on three new and important topics that are gaining momentum within the diffusion MRI community, including diffusion MRI signal acquisition and processing strategies, machine learning for diffusion MRI, and diffusion MRI outside the brain and clinical applications HTTP:URL=https://doi.org/10.1007/978-3-030-52893-5 |
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電子ブック | 配架場所 | 資料種別 | 巻 次 | 請求記号 | 状 態 | 予約 | コメント | ISBN | 刷 年 | 利用注記 | 指定図書 | 登録番号 |
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電子ブック | オンライン | 電子ブック |
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Springer eBooks | 9783030528935 |
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電子リソース |
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EB00227361 |
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データ種別 | 電子ブック |
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分 類 | LCC:QH323.5 LCC:QH324.2-324.25 DC23:570.285 |
書誌ID | 4000135326 |
ISBN | 9783030528935 |