Prof. Dr. Bernhard Kainz

Professur für Image Data Exploration and Analysis

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 MetaDetector: Detecting Outliers by Learning to Learn from Self-supervision (2022) Tan J, Kart T, Hou B, Batten J, Kainz B Conference contribution Video Summarization Through Reinforcement Learning with a 3D Spatiooral U-Net (2022) Liu T, Meng Q, Huang JJ, Vlontzos A, Rueckert D, Kainz B Journal article Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study (2021) Dou Q, So TY, Jiang M, Liu Q, Vardhanabhuti V, Kaissis G, Li Z, et al. Journal article RATCHET: Medical Transformer for Chest X-ray Diagnosis and Reporting (2021) Hou B, Kaissis G, Summers R, Kainz B Authored book, Volume of book series