15.4k citations · 21.2k across the 31 of their papers we have counts for
5 papers · 1 filter
The Medical Segmentation Decathlon
Michela Antonelli, Annika Reinke, Spyridon Bakas +55
International challenges have become the de facto standard for comparative assessment of image analysis algorithms given a specific task. Segmentation is so far the most widely inv…
Common Limitations of Image Processing Metrics: A Picture Story
Annika Reinke, Minu D. Tizabi, Carole H. Sudre +90
While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation. Performance metrics are…
Deep Learning for Chest X-ray Analysis: A Survey
Ecem Sogancioglu, Erdi Çallı, Bram van Ginneken +2
Recent advances in deep learning have led to a promising performance in many medical image analysis tasks. As the most commonly performed radiological exam, chest radiographs are a…
Deep Learning with robustness to missing data: A novel approach to the detection of COVID-19
Erdi Çallı, Keelin Murphy, Steef Kurstjens +5
In the context of the current global pandemic and the limitations of the RT-PCR test, we propose a novel deep learning architecture, DFCN (Denoising Fully Connected Network). Since…
Adversarial cycle-consistent synthesis of cerebral microbleeds for data augmentation
Khrystyna Faryna, Kevin Koschmieder, Marcella M. Paul +4
We propose a novel framework for controllable pathological image synthesis for data augmentation. Inspired by CycleGAN, we perform cycle-consistent image-to-image translation betwe…