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Issue DateTitleAuthor(s)
19-Mar-2019Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challengeBakas, S; Reyes, M; Jakab, A; Bauer, S; Rempfler, M, et al
7-May-2018Multi-modal learning from unpaired images: Application to multi-organ segmentation in CT and MRIValindria, V; Pawlowski, N; Rajchl, M; Lavdas, I; Aboagye, EO, et al
1-Jan-2018Ensembles of Multiple Models and Architectures for Robust Brain Tumour SegmentationKamnitsas, K; Bai, W; Ferrante, E; McDonagh, SG; Sinclair, M, et al
31-Dec-2017DLTK: State of the Art Reference Implementations for Deep Learning on Medical ImagesPawlowski, N; Ktena, SI; Lee, MCH; Kainz, B; Rueckert, D, et al
4-Jul-2018NeuroNet: fast and robust reproduction of multiple brain Image segmentation pipelinesRajchl, M; Pawlowski, N; Rueckert, D; Matthews, PM; Glocker, B, et al
14-Jun-2018Deep generative models in the real-world: an open challenge from medical imagingChen, X; Pawlowski, N; Rajchl, M; Glocker, B; Konukoglu, E
31-Dec-2017Implicit Weight Uncertainty in Neural NetworksPawlowski, N; Rajchl, M; Glocker, B;
-Ensembles of Multiple Models and Architectures for Robust Brain Tumour SegmentationKamnitsas, K; Bai, W; Ferrante, E; McDonagh, S; Sinclair, M, et al