40 citations · 93 across the 5 of their papers we have counts for
11 papers
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…
Federated Semi-Supervised Learning for COVID Region Segmentation in Chest CT using Multi-National Data from China, Italy, Japan
Dong Yang, Ziyue Xu, Wenqi Li +17
The recent outbreak of COVID-19 has led to urgent needs for reliable diagnosis and management of SARS-CoV-2 infection. As a complimentary tool, chest CT has been shown to be able t…
Enhancing Foreground Boundaries for Medical Image Segmentation
Dong Yang, Holger Roth, Xiaosong Wang +3
Object segmentation plays an important role in the modern medical image analysis, which benefits clinical study, disease diagnosis, and surgery planning. Given the various modaliti…
Edge-Gated CNNs for Volumetric Semantic Segmentation of Medical Images
Ali Hatamizadeh, Demetri Terzopoulos, Andriy Myronenko
Textures and edges contribute different information to image recognition. Edges and boundaries encode shape information, while textures manifest the appearance of regions. Despite…
Robust Semantic Segmentation of Brain Tumor Regions from 3D MRIs
Andriy Myronenko, Ali Hatamizadeh
Multimodal brain tumor segmentation challenge (BraTS) brings together researchers to improve automated methods for 3D MRI brain tumor segmentation. Tumor segmentation is one of the…
NeurReg: Neural Registration and Its Application to Image Segmentation
Wentao Zhu, Andriy Myronenko, Ziyue Xu +5
Registration is a fundamental task in medical image analysis which can be applied to several tasks including image segmentation, intra-operative tracking, multi-modal image alignme…