40 citations · 84 across the 6 of their papers we have counts for
6 papers
Automatic segmentation of clear cell renal cell tumors, kidney, and cysts in patients with von Hippel-Lindau syndrome using U-net architecture on magnetic resonance images
Pouria Yazdian Anari, Nathan Lay, Aditi Chaurasia +13
We demonstrate automated segmentation of clear cell renal cell carcinomas (ccRCC), cysts, and surrounding normal kidney parenchyma in patients with von Hippel-Lindau (VHL) syndrome…
Auto-FedRL: Federated Hyperparameter Optimization for Multi-institutional Medical Image Segmentation
Pengfei Guo, Dong Yang, Ali Hatamizadeh +14
Federated learning (FL) is a distributed machine learning technique that enables collaborative model training while avoiding explicit data sharing. The inherent privacy-preserving…
Auto-FedAvg: Learnable Federated Averaging for Multi-Institutional Medical Image Segmentation
Yingda Xia, Dong Yang, Wenqi Li +15
Federated learning (FL) enables collaborative model training while preserving each participant's privacy, which is particularly beneficial to the medical field. FedAvg is a standar…
Multi-Domain Image Completion for Random Missing Input Data
Liyue Shen, Wentao Zhu, Xiaosong Wang +9
Multi-domain data are widely leveraged in vision applications taking advantage of complementary information from different modalities, e.g., brain tumor segmentation from multi-par…
Adipose Tissue Segmentation in Unlabeled Abdomen MRI using Cross Modality Domain Adaptation
Samira Masoudi, Syed M. Anwar, Stephanie A. Harmon +3
Abdominal fat quantification is critical since multiple vital organs are located within this region. Although computed tomography (CT) is a highly sensitive modality to segment bod…
When Unseen Domain Generalization is Unnecessary? Rethinking Data Augmentation
Ling Zhang, Xiaosong Wang, Dong Yang +7
Recent advances in deep learning for medical image segmentation demonstrate expert-level accuracy. However, in clinically realistic environments, such methods have marginal perform…