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Titlebook: Computational Diffusion MRI; 14th International W Muge Karaman,Remika Mito,Stefan Winzeck Conference proceedings 2023 The Editor(s) (if app

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書目名稱Computational Diffusion MRI
副標(biāo)題14th International W
編輯Muge Karaman,Remika Mito,Stefan Winzeck
視頻videohttp://file.papertrans.cn/233/232242/232242.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Computational Diffusion MRI; 14th International W Muge Karaman,Remika Mito,Stefan Winzeck Conference proceedings 2023 The Editor(s) (if app
描述.This book constitutes the proceedings of the 14th International Workshop, CDMRI 2023, held in conjunction with MICCAI 2023, the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention. The conference took place in Vancouver, BC, Canada, on October 8, 2023...The 17regular papers presented in this book were carefully reviewed and selected from 19 submissions. These contributions cover various aspects, including preprocessing, signal modeling, tractography, bundle segmentation, and clinical applications. Many of these studies employ novel machine learning implementations, highlighting the evolving landscape of techniques beyond the more traditional physics-based algorithms..
出版日期Conference proceedings 2023
關(guān)鍵詞diffusion MRI; diffusion-weighted imaging; magnetic resonance imaging; neuroimaging; medical image compu
版次1
doihttps://doi.org/10.1007/978-3-031-47292-3
isbn_softcover978-3-031-47291-6
isbn_ebook978-3-031-47292-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Conference proceedings 2023nference on Medical Image Computing and Computer-Assisted Intervention. The conference took place in Vancouver, BC, Canada, on October 8, 2023...The 17regular papers presented in this book were carefully reviewed and selected from 19 submissions. These contributions cover various aspects, including
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,Automatic Fast and?Reliable Recognition of?a?Small Brain White Matter Bundle,ty data, we demonstrate that the novel method proposed here generalizes broadly in subjects from three different datasets with differing data quality and a broad age range. Finally, we describe how this approach could be easily extended to other small bundles.
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,Diffusion Phantom Study of?Fiber Crossings at?Varied Angles Reconstructed with?ODF-Fingerprinting,fusion phantoms composed of textile tubes with 0.8?.m diameter, approaching the anatomical scale of axons. Our results show that ODF-FP is able to correctly identify . of the crossing fibers regardless of the crossing angle and provide the highest average reconstruction accuracy.
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