most citedQUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge

5 citations · 5 across the 2 of their papers we have counts for

collaborators

2 papers

eess.IV2024★ 5 cited

QUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge

Hongwei Bran Li, Fernando Navarro, Ivan Ezhov +77

Uncertainty in medical image segmentation tasks, especially inter-rater variability, arising from differences in interpretations and annotations by various experts, presents a sign…

eess.IV2022

3D Cross-Pseudo Supervision (3D-CPS): A semi-supervised nnU-Net architecture for abdominal organ segmentation

Yongzhi Huang, Hanwen Zhang, Yan Yan +1

Large curated datasets are necessary, but annotating medical images is a time-consuming, laborious, and expensive process. Therefore, recent supervised methods are focusing on util…