Johannes Hofmanninger

According to our database, Johannes Hofmanninger authored at least 10 papers between 2015 and 2021.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

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

Continual Active Learning for Efficient Adaptation of Machine Learning Models to Changing Image Acquisition.

Matthias Perkonigg, Johannes Hofmanninger, Georg Langs

Proceedings of the Information Processing in Medical Imaging, 2021

2020

Separation of target anatomical structure and occlusions in chest radiographs.

Johannes Hofmanninger, Sebastian Röhrich, Helmut Prosch, Georg Langs

CoRR, 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

Dynamic Memory to Alleviate Catastrophic Forgetting in Continuous Learning Settings.

Johannes Hofmanninger, Matthias Perkonigg, James A. Brink, Oleg S. Pianykh, Christian Herold, Georg Langs

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

2018

Detecting Bone Lesions in Multiple Myeloma Patients Using Transfer Learning.

Matthias Perkonigg, Johannes Hofmanninger, Björn H. Menze, Marc-André Weber, Georg Langs

Proceedings of the Data Driven Treatment Response Assessment - and - Preterm, Perinatal, and Paediatric Image Analysis, 2018

Predicting Future Bone Infiltration Patterns in Multiple Myeloma.

Roxane Licandro, Johannes Hofmanninger, Marc-André Weber, Björn H. Menze, Georg Langs

Proceedings of the Patch-Based Techniques in Medical Imaging, 2018

2017

Mapping Multi-Modal Routine Imaging Data to a Single Reference via Multiple Templates.

Johannes Hofmanninger, Bjoern H. Menze, Marc-André Weber, Georg Langs

Proceedings of the Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 2017

2016

Unsupervised Identification of Clinically Relevant Clusters in Routine Imaging Data.

Johannes Hofmanninger, Markus Krenn, Markus Holzer, Thomas Schlegl, Helmut Prosch, Georg Langs

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016

2015

Mapping visual features to semantic profiles for retrieval in medical imaging.

Johannes Hofmanninger, Georg Langs

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015