URCA: Uncertainty-based region clipping algorithm for semi-supervised medical image segmentation

•Uncertainty-based region clipping algorithm is proposed for semi-supervised medical image segmentation.•More reliable targets can be learned by the model using uncertainty information.•The ablation experiments demonstrate the validity of the proposed model. Training convolutional neural networks ba...

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Veröffentlicht in:	Computer methods and programs in biomedicine 2024-09, Vol.254, p.108278, Article 108278
Hauptverfasser:	Qin, Chendong, Wang, Yongxiong, Zhang, Jiapeng
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Brain Neoplasms - diagnostic imaging Distribution bias Humans Image Processing, Computer-Assisted - methods Magnetic Resonance Imaging - methods Medical image segmentation Monte Carlo Method Neural Networks, Computer Non-maximum suppression Semi-supervised Supervised Machine Learning Uncertainty Uncertainty-aware
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