95 citations
- Shenzhen Technology UniversityCN9 papers
- Chang Gung Memorial HospitalTW6 papers
- Beijing University of Posts and TelecommunicationsCN5 papers
- National Institutes of Health Clinical CenterUS5 papers
- University of Science and Technology of ChinaCN5 papers
- Beijing Institute of TechnologyCN4 papers
- Huazhong University of Science and TechnologyCN4 papers
- Johns Hopkins UniversityUS3 papers
- Alibaba Group (China)CN2 papers
- Association for Computing MachineryUS2 papers
- Beihang UniversityCN2 papers
- China Medical UniversityTW2 papers
8 papers · 2 filters
Dual Encoder Fusion U-Net (DEFU-Net) for Cross-manufacturer Chest X-ray Segmentation
Lipei Zhang, Aozhi Liu, Jing Xiao +1
A number of methods based on deep learning have been applied to medical image segmentation and have achieved state-of-the-art performance. Due to the importance of chest x-ray data…
Lymph Node Gross Tumor Volume Detection and Segmentation via Distance-based Gating using 3D CT/PET Imaging in Radiotherapy
Zhuotun Zhu, Dakai Jin, Ke Yan +7
Finding, identifying and segmenting suspicious cancer metastasized lymph nodes from 3D multi-modality imaging is a clinical task of paramount importance. In radiotherapy, they are…
DeepPrognosis: Preoperative Prediction of Pancreatic Cancer Survival and Surgical Margin via Contrast-Enhanced CT Imaging
Jiawen Yao, Yu Shi, Le Lu +2
Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers and carries a dismal prognosis. Surgery remains the best chance of a potential cure for patients who are e…
Robust Pancreatic Ductal Adenocarcinoma Segmentation with Multi-Institutional Multi-Phase Partially-Annotated CT Scans
Ling Zhang, Yu Shi, Jiawen Yao +5
Accurate and automated tumor segmentation is highly desired since it has the great potential to increase the efficiency and reproducibility of computing more complete tumor measure…
One Click Lesion RECIST Measurement and Segmentation on CT Scans
Youbao Tang, Ke Yan, Jing Xiao +1
In clinical trials, one of the radiologists' routine work is to measure tumor sizes on medical images using the RECIST criteria (Response Evaluation Criteria In Solid Tumors). Howe…
ENet: An Edge Enhanced Network for Accurate Liver and Tumor Segmentation on CT Scans
Youbao Tang, Yuxing Tang, Yingying Zhu +2
Developing an effective liver and liver tumor segmentation model from CT scans is very important for the success of liver cancer diagnosis, surgical planning and cancer treatment.…