Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2019; 22nd International C Dinggang Shen,Tianming Liu,Ali Khan Conferen

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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).

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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.