Prof. Dr. Bernhard Kainz

Professur für Image Data Exploration and Analysis

Exploring a new paradigm for the fetal anomaly ultrasound scan: Artificial intelligence in real time (2022) Matthew J, Skelton E, Day TG, Zimmer VA, Gomez A, Wheeler G, Toussaint N, et al. Journal article Fetal Cortex Segmentation with Topology and Thickness Loss Constraints (2022) Li L, Ma Q, Li Z, Ouyang C, Zhang W, Price A, Kyriakopoulou V, et al. Conference contribution Natural Synthetic Anomalies for Self-supervised Anomaly Detection and Localization (2022) Schlüter HM, Tan J, Hou B, Kainz B Conference contribution A variational Bayesian method for similarity learning in non-rigid image registration (2022) Grzech D, Azampour MF, Glocker B, Schnabel J, Navab N, Kainz B, Folgoc LL Conference contribution nnOOD: A Framework for Benchmarking Self-supervised Anomaly Localisation Methods (2022) Baugh M, Tan J, Vlontzos A, Müller J, Kainz B Conference contribution Improved Post-hoc Probability Calibration for Out-of-Domain MRI Segmentation (2022) Ouyang C, Wang S, Chen C, Li Z, Bai W, Kainz B, Rueckert D Conference contribution Adnexal Mass Segmentation with Ultrasound Data Synthesis (2022) Lebbos C, Barcroft J, Tan J, Müller J, Baugh M, Vlontzos A, Saso S, Kainz B Conference contribution D’ARTAGNAN: Counterfactual Video Generation (2022) Reynaud H, Vlontzos A, Dombrowski M, Gilligan Lee C, Beqiri A, Leeson P, Kainz B Conference contribution Video Summarization Through Reinforcement Learning with a 3D Spatiooral U-Net (2022) Kainz B Journal article, Original article PRETUS: A plug-in based platform for real-time ultrasound imaging research (2022) Gomez A, Zimmer VA, Wheeler G, Toussaint N, Deng S, Wright R, Skelton E, et al. Journal article, Original article