8 citations · 8 across the 4 of their papers we have counts for
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eess.IV2021
Uncertainty-Aware Temporal Self-Learning (UATS): Semi-Supervised Learning for Segmentation of Prostate Zones and Beyond
Anneke Meyer, Suhita Ghosh, Daniel Schindele +4
Various convolutional neural network (CNN) based concepts have been introduced for the prostate's automatic segmentation and its coarse subdivision into transition zone (TZ) and pe…
eess.IV2021
Learning Multi-Modal Volumetric Prostate Registration with Weak Inter-Subject Spatial Correspondence
Oleksii Bashkanov, Anneke Meyer, Daniel Schindele +4
Recent studies demonstrated the eligibility of convolutional neural networks (CNNs) for solving the image registration problem. CNNs enable faster transformation estimation and gre…