1.2k citations · 1.4k across the 6 of their papers we have counts for
6 papers
Robust Segmentation Models using an Uncertainty Slice Sampling Based Annotation Workflow
Grzegorz Chlebus, Andrea Schenk, Horst K. Hahn +2
Semantic segmentation neural networks require pixel-level annotations in large quantities to achieve a good performance. In the medical domain, such annotations are expensive, beca…
Anisotropic 3D Multi-Stream CNN for Accurate Prostate Segmentation from Multi-Planar MRI
Anneke Meyer, Grzegorz Chlebus, Marko Rak +8
Background and Objective: Accurate and reliable segmentation of the prostate gland in MR images can support the clinical assessment of prostate cancer, as well as the planning and…
Relevance analysis of MRI sequences for automatic liver tumor segmentation
Grzegorz Chlebus, Nasreddin Abolmaali, Andrea Schenk +1
Explainability of decisions made by deep neural networks is of high value as it allows for validation and improvement of models. This work proposes an approach to explain semantic…
The Liver Tumor Segmentation Benchmark (LiTS)
Patrick Bilic, Patrick Christ, Hongwei Bran Li +106
In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedi…
Comparison of U-net-based Convolutional Neural Networks for Liver Segmentation in CT
Hans Meine, Grzegorz Chlebus, Mohsen Ghafoorian +2
Various approaches for liver segmentation in CT have been proposed: Besides statistical shape models, which played a major role in this research area, novel approaches on the basis…
Neural Network-Based Automatic Liver Tumor Segmentation With Random Forest-Based Candidate Filtering
Grzegorz Chlebus, Hans Meine, Jan Hendrik Moltz +1
We present a fully automatic method employing convolutional neural networks based on the 2D U-net architecture and random forest classifier to solve the automatic liver lesion segm…