36 citations · 61 across the 6 of their papers we have counts for
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eess.IV2022★ 36 cited
Federated Multi-organ Segmentation with Inconsistent Labels
Xuanang Xu, Hannah H. Deng, Jaime Gateno +1
Federated learning is an emerging paradigm allowing large-scale decentralized learning without sharing data across different data owners, which helps address the concern of data pr…
eess.IV2022★ 11 cited
Federated Cross Learning for Medical Image Segmentation
Xuanang Xu, Hannah H. Deng, Tianyi Chen +6
Federated learning (FL) can collaboratively train deep learning models using isolated patient data owned by different hospitals for various clinical applications, including medical…
eess.IV2021★ 1 cited
SkullEngine: A Multi-stage CNN Framework for Collaborative CBCT Image Segmentation and Landmark Detection
Qin Liu, Han Deng, Chunfeng Lian +8
We propose a multi-stage coarse-to-fine CNN-based framework, called SkullEngine, for high-resolution segmentation and large-scale landmark detection through a collaborative, integr…