762 citations · 889 across the 6 of their papers we have counts for
3 papers · 1 filter
Adversarial Networks for Prostate Cancer Detection
Simon Kohl, David Bonekamp, Heinz-Peter Schlemmer +5
The large number of trainable parameters of deep neural networks renders them inherently data hungry. This characteristic heavily challenges the medical imaging community and to ma…
Adversarial Networks for the Detection of Aggressive Prostate Cancer
Simon Kohl, David Bonekamp, Heinz-Peter Schlemmer +5
Semantic segmentation constitutes an integral part of medical image analyses for which breakthroughs in the field of deep learning were of high relevance. The large number of train…
Revealing Hidden Potentials of the q-Space Signal in Breast Cancer
Paul Jaeger, Sebastian Bickelhaupt, Frederik Bernd Laun +10
Mammography screening for early detection of breast lesions currently suffers from high amounts of false positive findings, which result in unnecessary invasive biopsies. Diffusion…