446 citations · 625 across the 8 of their papers we have counts for
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Generating Highly Realistic Images of Skin Lesions with GANs
Christoph Baur, Shadi Albarqouni, Nassir Navab
As many other machine learning driven medical image analysis tasks, skin image analysis suffers from a chronic lack of labeled data and skewed class distributions, which poses prob…
GANs for Medical Image Analysis
Salome Kazeminia, Christoph Baur, Arjan Kuijper +4
Generative Adversarial Networks (GANs) and their extensions have carved open many exciting ways to tackle well known and challenging medical image analysis problems such as medical…
Deep Autoencoding Models for Unsupervised Anomaly Segmentation in Brain MR Images
Christoph Baur, Benedikt Wiestler, Shadi Albarqouni +1
Reliably modeling normality and differentiating abnormal appearances from normal cases is a very appealing approach for detecting pathologies in medical images. A plethora of such…
MelanoGANs: High Resolution Skin Lesion Synthesis with GANs
Christoph Baur, Shadi Albarqouni, Nassir Navab
Generative Adversarial Networks (GANs) have been successfully used to synthesize realistically looking images of faces, scenery and even medical images. Unfortunately, they usually…
StainGAN: Stain Style Transfer for Digital Histological Images
M Tarek Shaban, Christoph Baur, Nassir Navab +1
Digitized Histological diagnosis is in increasing demand. However, color variations due to various factors are imposing obstacles to the diagnosis process. The problem of stain col…