469 citations · 1.4k across the 20 of their papers we have counts for
8 papers · 1 filter
Anatomy-informed Data Augmentation for Enhanced Prostate Cancer Detection
Balint Kovacs, Nils Netzer, Michael Baumgartner +17
Data augmentation (DA) is a key factor in medical image analysis, such as in prostate cancer (PCa) detection on magnetic resonance images. State-of-the-art computer-aided diagnosis…
Exploring new ways: Enforcing representational dissimilarity to learn new features and reduce error consistency
Tassilo Wald, Constantin Ulrich, Fabian Isensee +4
Independently trained machine learning models tend to learn similar features. Given an ensemble of independently trained models, this results in correlated predictions and common f…
Taming Detection Transformers for Medical Object Detection
Marc K. Ickler, Michael Baumgartner, Saikat Roy +2
The accurate detection of suspicious regions in medical images is an error-prone and time-consuming process required by many routinely performed diagnostic procedures. To support c…
Transformer Utilization in Medical Image Segmentation Networks
Saikat Roy, Gregor Koehler, Michael Baumgartner +4
Owing to success in the data-rich domain of natural images, Transformers have recently become popular in medical image segmentation. However, the pairing of Transformers with convo…
Accurate Detection of Mediastinal Lesions with nnDetection
Michael Baumgartner, Peter M. Full, Klaus H. Maier-Hein
The accurate detection of mediastinal lesions is one of the rarely explored medical object detection problems. In this work, we applied a modified version of the self-configuring m…
MultiTalent: A Multi-Dataset Approach to Medical Image Segmentation
Constantin Ulrich, Fabian Isensee, Tassilo Wald +3
The medical imaging community generates a wealth of datasets, many of which are openly accessible and annotated for specific diseases and tasks such as multi-organ or lesion segmen…