动脉 发表于 2025-3-25 04:41:29

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混沌 发表于 2025-3-25 07:30:31

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falsehood 发表于 2025-3-25 12:28:55

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造反,叛乱 发表于 2025-3-25 17:23:13

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Crepitus 发表于 2025-3-25 21:31:02

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PAN 发表于 2025-3-26 03:27:31

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文件夹 发表于 2025-3-26 06:30:51

Predicting the Evolution of White Matter Hyperintensities in Brain MRI Using Generative Adversarial tion of WMH in small vessel disease. DEP-GAN is able to estimate WMH volume in the follow-up year with mean (std) estimation error of −1.91 (12.12) ml and predict WMH evolution with mean rate of . accuracy (i.e., . and . better than Wasserstein GAN).

食品室 发表于 2025-3-26 09:12:23

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Minuet 发表于 2025-3-26 13:52:04

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Negotiate 发表于 2025-3-26 20:19:10

Model Learning: Primal Dual Networks for Fast MR Imagingstruction model is finally learned from the training data by updating in k-space and image domain alternatively. Experiments on in vivo MR data demonstrate that the proposed method achieves superior MR reconstructions from highly undersampled k-space data over other state-of-the-art image reconstruction methods.
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查看完整版本: Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2019; 22nd International C Dinggang Shen,Tianming Liu,Ali Khan Conferen