1.2k citations · 1.4k across the 9 of their papers we have counts for
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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…
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…