1.2k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Beijing Tongren HospitalCN2 papers
- Capital Medical UniversityCN2 papers
- Tencent (China)CN2 papers
- Barcelona Supercomputing CenterES1 paper
- Brigham and Women's HospitalUS1 paper
- Chinese Academy of SciencesCN1 paper
- Chinese University of Hong KongHK1 paper
- ETH ZurichCH1 paper
- Fraunhofer Institute for Digital MedicineDE1 paper
- German Cancer Research CenterDE1 paper
- Guangdong University of Foreign StudiesCN1 paper
- Hadassah Medical CenterIL1 paper
6 papers
Lesion Guided Explainable Few Weak-shot Medical Report Generation
Jinghan Sun, Dong Wei, Liansheng Wang +1
Medical images are widely used in clinical practice for diagnosis. Automatically generating interpretable medical reports can reduce radiologists' burden and facilitate timely care…
Domain Adaptation Meets Zero-Shot Learning: An Annotation-Efficient Approach to Multi-Modality Medical Image Segmentation
Cheng Bian, Chenglang Yuan, Kai Ma +3
Due to the lack of properly annotated medical data, exploring the generalization capability of the deep model is becoming a public concern. Zero-shot learning (ZSL) has emerged in…
TR-GAN: Topology Ranking GAN with Triplet Loss for Retinal Artery/Vein Classification
Wenting Chen, Shuang Yu, Junde Wu +5
Retinal artery/vein (A/V) classification lays the foundation for the quantitative analysis of retinal vessels, which is associated with potential risks of various cardiovascular an…
Difficulty-aware Glaucoma Classification with Multi-Rater Consensus Modeling
Shuang Yu, Hong-Yu Zhou, Kai Ma +4
Medical images are generally labeled by multiple experts before the final ground-truth labels are determined. Consensus or disagreement among experts regarding individual images re…
Leveraging Undiagnosed Data for Glaucoma Classification with Teacher-Student Learning
Junde Wu, Shuang Yu, Wenting Chen +5
Recently, deep learning has been adopted to the glaucoma classification task with performance comparable to that of human experts. However, a well trained deep learning model deman…
The Liver Tumor Segmentation Benchmark (LiTS)
Patrick Bilic, Patrick Christ, Hongwei Bran Li +106
In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedi…