430 citations · 1.8k across the 48 of their papers we have counts for
12 papers · 1 filter
Robust Medical Image Classification from Noisy Labeled Data with Global and Local Representation Guided Co-training
Cheng Xue, Lequan Yu, Pengfei Chen +2
Deep neural networks have achieved remarkable success in a wide variety of natural image and medical image computing tasks. However, these achievements indispensably rely on accura…
Comparative Validation of Machine Learning Algorithms for Surgical Workflow and Skill Analysis with the HeiChole Benchmark
Martin Wagner, Beat-Peter Müller-Stich, Anna Kisilenko +38
PURPOSE: Surgical workflow and skill analysis are key technologies for the next generation of cognitive surgical assistance systems. These systems could increase the safety of the…
Source-Free Domain Adaptive Fundus Image Segmentation with Denoised Pseudo-Labeling
Cheng Chen, Quande Liu, Yueming Jin +2
Domain adaptation typically requires to access source domain data to utilize their distribution information for domain alignment with the target data. However, in many real-world s…
Cascaded Robust Learning at Imperfect Labels for Chest X-ray Segmentation
Cheng Xue, Qiao Deng, Xiaomeng Li +2
The superior performance of CNN on medical image analysis heavily depends on the annotation quality, such as the number of labeled image, the source of image, and the expert experi…
Contrastive Cross-site Learning with Redesigned Net for COVID-19 CT Classification
Zhao Wang, Quande Liu, Qi Dou
The pandemic of coronavirus disease 2019 (COVID-19) has lead to a global public health crisis spreading hundreds of countries. With the continuous growth of new infections, develop…
Image-level Harmonization of Multi-Site Data using Image-and-Spatial Transformer Networks
R. Robinson, Q. Dou, D. C. Castro +5
We investigate the use of image-and-spatial transformer networks (ISTNs) to tackle domain shift in multi-site medical imaging data. Commonly, domain adaptation (DA) is performed wi…