FKD-Med: Privacy-Aware, Communication-Optimized Medical Image Segmentation via Federated Learning and Model Lightweighting Through Knowledge Distillation

Advances in deep learning have revolutionized medical image segmentation, facilitating the precise delineation of complex anatomical structures. The scarcity of annotated training samples remains a significant bottleneck. To tackle the data limitation, federated learning (FL) offers the promise of p...

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Principais autores:	Guanqun Sun, Han Shu, Feihe Shao, Teeradaj Racharak, Weikun Kong, Yizhi Pan, Jingjing Dong, Shuang Wang, Le-Minh Nguyen, Junyi Xin
Formato:	Artigo
Idioma:	Inglês
Publicado:	IEEE 2024-01-01
Series:	IEEE Access
Assuntos:	Medical image segmentation federated learning knowledge distillation U-net
Acceso en liña:	https://ieeexplore.ieee.org/document/10456909/
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