342 citations · 706 across the 57 of their papers we have counts for
57 papers
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…
Adversarial Medical Image with Hierarchical Feature Hiding
Qingsong Yao, Zecheng He, Yuexiang Li +4
Deep learning based methods for medical images can be easily compromised by adversarial examples (AEs), posing a great security flaw in clinical decision-making. It has been discov…
A New Perspective to Boost Vision Transformer for Medical Image Classification
Yuexiang Li, Yawen Huang, Nanjun He +2
Transformer has achieved impressive successes for various computer vision tasks. However, most of existing studies require to pretrain the Transformer backbone on a large-scale lab…
Seg4Reg+: Consistency Learning between Spine Segmentation and Cobb Angle Regression
Yi Lin, Luyan Liu, Kai Ma +1
Automated methods for Cobb angle estimation are of high demand for scoliosis assessment. Existing methods typically calculate the Cobb angle from landmark estimation, or simply com…
Dense Cross-Query-and-Support Attention Weighted Mask Aggregation for Few-Shot Segmentation
Xinyu Shi, Dong Wei, Yu Zhang +5
Research into Few-shot Semantic Segmentation (FSS) has attracted great attention, with the goal to segment target objects in a query image given only a few annotated support images…
Learning Shape Priors by Pairwise Comparison for Robust Semantic Segmentation
Cong Xie, Hualuo Liu, Shilei Cao +4
Semantic segmentation is important in medical image analysis. Inspired by the strong ability of traditional image analysis techniques in capturing shape priors and inter-subject si…