Computer Science - Machine Learning

GAN-based generation of realistic 3D data: A systematic review and taxonomy

André Ferreira, Jianning Li, Kelsey L. Pomykala, Jens Kleesiek, Victor Alves, Jan Egger

GAN-based generation of realistic 3D data: A systematic review and taxonomy

k-strip: A novel segmentation algorithm in k-space for the application of skull stripping

Moritz Rempe, Florian Mentzel, Kelsey L. Pomykala, Johannes Haubold, Felix Nensa, Kevin Kröninger, Jan Egger, Jens Kleesiek

k-strip: A novel segmentation algorithm in k-space for the application of skull stripping

Stochastic Modeling of Inhomogeneities in the Aortic Wall and Uncertainty Quantification using a Bayesian Encoder-Decoder Surrogate

Sascha Ranftl, Malte Rolf-Pissarczyk, Gloria Wolkerstorfer, Antonio Pepe, Jan Egger, Wolfgang von der Linden, Gerhard A. Holzapfel

Stochastic Modeling of Inhomogeneities in the Aortic Wall and Uncertainty Quantification using a Bayesian Encoder-Decoder Surrogate

Reference-guided Pseudo-Label Generation for Medical Semantic Segmentation

Constantin Seibold, Simon Reiß, Jens Kleesiek, Rainer Stiefelhagen

Reference-guided Pseudo-Label Generation for Medical Semantic Segmentation

A Relational-learning Perspective to Multi-label Chest X-ray Classification

Anjany Sekuboyina, Daniel Oñoro-Rubio, Jens Kleesiek, Brandon Malone

A Relational-learning Perspective to Multi-label Chest X-ray Classification

Prediction of low-keV monochromatic images from polyenergetic CT scans for improved automatic detection of pulmonary embolism

Constantin Seibold, Matthias A. Fink, Charlotte Goos, Hans-Ulrich Kauczor, Heinz-Peter Schlemmer, Rainer Stiefelhagen, Jens Kleesiek

Prediction of low-keV monochromatic images from polyenergetic CT scans for improved automatic detection of pulmonary embolism