Prof. Dr. Bernhard Kainz

Professur für Image Data Exploration and Analysis

Three-dimensional visualisation of the fetal heart using prenatal MRI with motion-corrected slice-volume registration: a prospective, single-centre cohort study (2019) Lloyd DF, Pushparajah K, Simpson JM, van Amerom JF, van Poppel MP, Schulz A, Kainz B, et al. Journal article Evaluating reinforcement learning agents for anatomical landmark detection (2019) Alansary A, Oktay O, Li Y, Le Folgoc L, Hou B, Vaillant G, Kamnitsas K, et al. Journal article Attention gated networks: Learning to leverage salient regions in medical images (2019) Schlemper J, Oktay O, Schaap M, Heinrich M, Kainz B, Glocker B, Rueckert D Journal article Automated quality control in image segmentation: Application to the UK Biobank cardiovascular magnetic resonance imaging study (2019) Robinson R, Valindria VV, Bai W, Oktay O, Kainz B, Suzuki H, Sanghvi MM, et al. Journal article Complete Fetal Head Compounding from Multi-view 3D Ultrasound (2019) Wright R, Toussaint N, Gomez A, Zimmer V, Khanal B, Matthew J, Skelton E, et al. Conference contribution Confident head circumference measurement from ultrasound with real-time feedback for sonographers (2019) Budd S, Sinclair M, Khanal B, Matthew J, Lloyd D, Gomez A, Toussaint N, et al. Conference contribution Multiple landmark detection using multi-agent reinforcement learning (2019) Vlontzos A, Alansary A, Kamnitsas K, Rueckert D, Kainz B Conference contribution Automatic detection of bowel disease with residual networks (2019) Holland R, Patel U, Lung P, Chotzoglou E, Kainz B Conference contribution Semi-supervised learning of fetal anatomy from ultrasound (2019) Tan J, Au A, Meng Q, Kainz B Conference contribution Representation disentanglement for multi-task learning with application to fetal ultrasound (2019) Meng Q, Pawlowski N, Rueckert D, Kainz B Conference contribution