11 citations · 34 across the 5 of their papers we have counts for
6 papers
Mask Mining for Improved Liver Lesion Segmentation
Karsten Roth, Jürgen Hesser, Tomasz Konopczyński
We propose a novel procedure to improve liver and lesion segmentation from CT scans for U-Net based models. Our method extends standard segmentation pipelines to focus on higher ta…
Liver Lesion Segmentation with slice-wise 2D Tiramisu and Tversky loss function
Karsten Roth, Tomasz Konopczyński, Jürgen Hesser
At present, lesion segmentation is still performed manually (or semi-automatically) by medical experts. To facilitate this process, we contribute a fully-automatic lesion segmentat…
Automated Multiscale 3D Feature Learning for Vessels Segmentation in Thorax CT Images
Tomasz Konopczyński, Thorben Kröger, Lei Zheng +2
We address the vessel segmentation problem by building upon the multiscale feature learning method of Kiros et al., which achieves the current top score in the VESSEL12 MICCAI chal…
Fully Convolutional Deep Network Architectures for Automatic Short Glass Fiber Semantic Segmentation from CT scans
Tomasz Konopczyński, Danish Rathore, Jitendra Rathore +5
We present the first attempt to perform short glass fiber semantic segmentation from X-ray computed tomography volumetric datasets at medium (3.9 μm isotropic) and low (8.3 μm isot…
Reference Setup for Quantitative Comparison of Segmentation Techniques for Short Glass Fiber CT Data
Tomasz Konopczyński, Jitendra Rathore, Thorben Kröger +4
Comparing different algorithms for segmenting glass fibers in industrial computed tomography (CT) scans is difficult due to the absence of a standard reference dataset. In this wor…
Instance Segmentation of Fibers from Low Resolution CT Scans via 3D Deep Embedding Learning
Tomasz Konopczyński, Thorben Kröger, Lei Zheng +1
We propose a novel approach for automatic extraction (instance segmentation) of fibers from low resolution 3D X-ray computed tomography scans of short glass fiber reinforced polyme…