446 citations · 625 across the 8 of their papers we have counts for
8 papers · 1 filter
Millimeter-wave Imaging for Anthropometric Body Measurement
Miriam Senne, Benjamin D. Killeen, Christoph Baur +2
Body shape and circumferences are clinically informative biomarkers for risk stratification, including measures such as waist to hip ratio, limb and trunk girths, yet conventional…
Adversarial Networks for Camera Pose Regression and Refinement
Mai Bui, Christoph Baur, Nassir Navab +2
Despite recent advances on the topic of direct camera pose regression using neural networks, accurately estimating the camera pose of a single RGB image still remains a challenging…
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…
Semi-Supervised Deep Learning for Fully Convolutional Networks
Christoph Baur, Shadi Albarqouni, Nassir Navab
Deep learning usually requires large amounts of labeled training data, but annotating data is costly and tedious. The framework of semi-supervised learning provides the means to us…