Mapping visual features to semantic profiles for retrieval in medical imaging. - Johannes Hofmanninger; Georg Langs (CVPR, 2015)

Unsupervised Identification of Clinically Relevant Clusters in Routine Imaging Data. - Johannes Hofmanninger; Markus Krenn; Markus Holzer 003; Thomas Schlegl; Helmut Prosch; Georg Langs (MICCAI (1), 2016)

Mapping Multi-Modal Routine Imaging Data to a Single Reference via Multiple Templates. - Johannes Hofmanninger; Bjoern H. Menze; Marc-André Weber; Georg Langs (DLMIA/ML-CDS@MICCAI, 2017)

Predicting Future Bone Infiltration Patterns in Multiple Myeloma. - Roxane Licandro; Johannes Hofmanninger; Marc-André Weber; Björn H. Menze; Georg Langs (Patch-MI@MICCAI, 2018)

Detecting Bone Lesions in Multiple Myeloma Patients Using Transfer Learning. - Matthias Perkonigg; Johannes Hofmanninger; Björn H. Menze; Marc-André Weber; Georg Langs (DATRA/PIPPI@MICCAI, 2018)

Dynamic Memory to Alleviate Catastrophic Forgetting in Continuous Learning Settings. - Johannes Hofmanninger; Matthias Perkonigg; James A. Brink; Oleg S. Pianykh; Christian Herold; Georg Langs (MICCAI (2), 2020)

Automatic lung segmentation in routine imaging is a data diversity problem, not a methodology problem. - Johannes Hofmanninger; Florian Prayer; Jeanny Pan; Sebastian Rohrich; Helmut Prosch; Georg Langs (CoRR, 2020)

Separation of target anatomical structure and occlusions in chest radiographs. - Johannes Hofmanninger; Sebastian Röhrich; Helmut Prosch; Georg Langs (CoRR, 2020)

Continual Active Learning for Efficient Adaptation of Machine Learning Models to Changing Image Acquisition. - Matthias Perkonigg; Johannes Hofmanninger; Georg Langs (IPMI, 2021)

Continual Active Learning Using Pseudo-Domains for Limited Labelling Resources and Changing Acquisition Characteristics. - Matthias Perkonigg; Johannes Hofmanninger; Christian Herold; Helmut Prosch; Georg Langs (CoRR, 2021)