45 citations
- Ping An (China)6 papers
- Chang Gung UniversityTW5 papers
- National Tsing Hua UniversityTW4 papers
- Johns Hopkins UniversityUS3 papers
- Artificial Intelligence in Medicine (Canada)CA2 papers
- First Affiliated Hospital Zhejiang UniversityCN2 papers
- Linkou Chang Gung Memorial HospitalTW2 papers
- University of South CarolinaUS2 papers
- University of TartuEE2 papers
- University of TorontoCA2 papers
- Vanderbilt UniversityUS2 papers
- Bennett UniversityIN1 paper
5 papers · 1 filter
Merlin: A Computed Tomography Vision-Language Foundation Model and Dataset
Louis Blankemeier, Ashwin Kumar, Joseph Paul Cohen +37
The large volume of abdominal computed tomography (CT) scans coupled with the shortage of radiologists have intensified the need for automated medical image analysis tools. Previou…
Contour Transformer Network for One-shot Segmentation of Anatomical Structures
Yuhang Lu, Kang Zheng, Weijian Li +8
Accurate segmentation of anatomical structures is vital for medical image analysis. The state-of-the-art accuracy is typically achieved by supervised learning methods, where gather…
Deep Volumetric Universal Lesion Detection using Light-Weight Pseudo 3D Convolution and Surface Point Regression
Jinzheng Cai, Ke Yan, Chi-Tung Cheng +4
Identifying, measuring and reporting lesions accurately and comprehensively from patient CT scans are important yet time-consuming procedures for physicians. Computer-aided lesion/…
Lymph Node Gross Tumor Volume Detection in Oncology Imaging via Relationship Learning Using Graph Neural Network
Chun-Hung Chao, Zhuotun Zhu, Dazhou Guo +10
Determining the spread of GTV is essential in defining the respective resection or irradiating regions for the downstream workflows of surgical resection and radiotherapy fo…
Learning to Segment Anatomical Structures Accurately from One Exemplar
Yuhang Lu, Weijian Li, Kang Zheng +8
Accurate segmentation of critical anatomical structures is at the core of medical image analysis. The main bottleneck lies in gathering the requisite expert-labeled image annotatio…