命令变成大炮 发表于 2025-3-25 06:31:18

978-3-030-52895-9Springer Nature Switzerland AG 2020

Ingratiate 发表于 2025-3-25 10:09:30

1612-3786 usion 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 frontlin978-3-030-52895-9978-3-030-52893-5Series ISSN 1612-3786 Series E-ISSN 2197-666X

外露 发表于 2025-3-25 15:39:52

Conference proceedings 2020tributions 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 frontlin

AMPLE 发表于 2025-3-25 16:38:24

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厌恶 发表于 2025-3-25 22:04:52

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Delude 发表于 2025-3-26 03:14:12

Current Challenges and Future Directions in Diffusion MRI: From Model- to Data- Driven Analysisective of diffusion MRI as a signal that is explained by a tractable biophysical model with one in which data driven machine learning can inform us about detection, localization, and assessment of both normal and abnormal brain tissue in both local (voxels) and global connectivity. Towards this end,

maudtin 发表于 2025-3-26 05:59:00

Spatial Sparse Estimation of Fiber Orientation Distribution Using Deep Alternating Directions Methodssessed using standard tractography and automatic white matter analysis algorithms. Compared with the comparison method, the proposed method has good consistency in sparse fiber reconstruction and fiber continuity.

得体 发表于 2025-3-26 10:15:56

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幸福愉悦感 发表于 2025-3-26 14:01:50

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行为 发表于 2025-3-26 20:24:30

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查看完整版本: Titlebook: Computational Diffusion MRI; MICCAI Workshop, She Elisenda Bonet-Carne,Jana Hutter,Fan Zhang Conference proceedings 2020 Springer Nature Sw