BET 发表于 2025-3-28 16:52:11

Svitlana Matviyenko,Judith Roofial information of the third dimension from volumetric image data. The proposed approach was tested in the 2021 MICCAI MOOD challenge, and it ranked the first place in both sample-level and pixel-level tasks.

conscience 发表于 2025-3-28 19:13:39

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Metamorphosis 发表于 2025-3-29 02:59:06

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勾引 发表于 2025-3-29 03:06:29

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愉快吗 发表于 2025-3-29 10:45:09

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Asseverate 发表于 2025-3-29 11:36:17

SS3D: Unsupervised Out-of-Distribution Detection and Localization for Medical Volumesance among the slices that contain it. On the sample-level task of the 2021 MICCAI Medical Out-of-Distribution Analysis Challenge [.], our method ranked second on the challenging abdominal dataset, and fourth overall. Moreover, we show that with pretrained features and the right choice of architecture, a further boost in performance can be gained.

哑巴 发表于 2025-3-29 17:22:05

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合并 发表于 2025-3-29 20:36:41

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古文字学 发表于 2025-3-30 03:14:52

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Decongestant 发表于 2025-3-30 06:16:59

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查看完整版本: Titlebook: Biomedical Image Registration, Domain Generalisation and Out-of-Distribution Analysis; MICCAI 2021 Challeng Marc Aubreville,David Zimmerer,