MTL-ABS3Net: Atlas-Based Semi-Supervised Organ Segmentation Network With Multi-Task Learning for Medical Images

Organ segmentation is one of the most important step for various medical image analysis tasks. Recently, semi-supervised learning (SSL) has attracted much attentions by reducing labeling cost. However, most of the existing SSLs neglected the prior shape and position information specialized in the me...

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Veröffentlicht in:	IEEE journal of biomedical and health informatics 2022-08, Vol.26 (8), p.3988-3998
Hauptverfasser:	Huang, Huimin, Chen, Qingqing, Lin, Lanfen, Cai, Ming, Zhang, Qiaowei, Iwamoto, Yutaro, Han, Xianhua, Furukawa, Akira, Kanasaki, Shuzo, Chen, Yen-Wei, Tong, Ruofeng, Hu, Hongjie
Format:	Artikel
Sprache:	eng
Schlagworte:	Anatomical Priors Biomedical imaging Image analysis Image processing Image reconstruction Image segmentation Labels Learning Localization Medical imaging Multi-task Learning Multitasking Organ Segmentation Probabilistic logic Reconstruction Self-training Semi-supervised learning Semi-supervised Learning (SSL) Task analysis Training
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