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MS lesion segmentation using a multi-channel patch-based approach with spatial consistency., , and . Medical Imaging: Image Processing, volume 9413 of SPIE Proceedings, page 94130O. SPIE, (2015)Maintaining Natural Image Statistics with the Contextual Loss., , , and . ACCV (3), volume 11363 of Lecture Notes in Computer Science, page 427-443. Springer, (2018)Saliency Driven Image Manipulation., , and . WACV, page 1368-1376. IEEE Computer Society, (2018)Adversarial Feedback Loop., , , and . CoRR, (2018)Improving CNN Training using Disentanglement for Liver Lesion Classification in CT., , , and . CoRR, (2018)Patch-Based Segmentation with Spatial Consistency: Application to MS Lesions in Brain MRI., , and . Int. J. Biomedical Imaging, (2016)The Contextual Loss for Image Transformation with Non-aligned Data., , and . ECCV (14), volume 11218 of Lecture Notes in Computer Science, page 800-815. Springer, (2018)Improving CNN Training using Disentanglement for Liver Lesion Classification in CT., , , and . EMBC, page 886-889. IEEE, (2019)Dynamic-Net: Tuning the Objective Without Re-training., , and . CoRR, (2018)Dynamic-Net: Tuning the Objective Without Re-Training for Synthesis Tasks., , and . ICCV, page 3214-3222. IEEE, (2019)