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Results 1-10 of 23
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Issue DateTitleAuthor(s)
1-Jan-2018Ensembles of Multiple Models and Architectures for Robust Brain Tumour SegmentationKamnitsas, K; Bai, W; Ferrante, E; McDonagh, SG; Sinclair, M, et al
17-Apr-2017Reverse classification accuracy: predicting segmentation performance in the absence of ground truthValindria, V; Lavdas, I; Bai, W; Kamnitsas, K; Aboagye, E, et al
31-Dec-2018Real-time prediction of segmentation qualityRobinson, R; Oktay, O; Bai, W; Valindria, V; Sanghvi, MM, et al
1-Aug-20183D reconstruction in canonical co-ordinate space from arbitrarily oriented 2D imagesHou, B; Khanal, B; Alansary, A; McDonagh, S; Davidson, A, et al
28-Nov-2016Fast fully automatic segmentation of the severely abnormal human right ventricle from cardiovascular magnetic resonance images using a multi-scale 3D convolutional neural networkGiannakidis, A; Kamnitsas, K; Spadotto, V; Keegan, J; Smith, G, et al
29-Oct-2016Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentationKamnitsas, K; Ledig, C; Newcombe, VFJ; Simpson, JP; Kane, AD, et al
15-Mar-2017Robust guidewire tracking under large deformations combining segment-like features (SEGlets)Vandini, A; Glocker, B; Hamady, M; Yang, G-Z; Engineering & Physical Science Research Council (EPSRC), et al
14-Mar-2019Automated quality control in image segmentation: application to the UK Biobank cardiac MR imaging studyRobinson, R; Valindria, VV; Bai, W; Oktay, O; Kainz, B, et al
1-Apr-2019Evaluating reinforcement learning agents for anatomical landmark detectionAlansary, A; Oktay, O; Li, Y; Folgoc, LL; Hou, B, et al
-Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion SegmentationKamnitsas, K; Ledig, C; Newcombe, VFJ; Simpson, JP; Kane, AD, et al