Mutual Evidential Deep Learning for Semi-supervised Medical Image Segmentation

Existing semi-supervised medical segmentation co-learning frameworks have realized that model performance can be diminished by the biases in model recognition caused by low-quality pseudo-labels. Due to the averaging nature of their pseudo-label integration strategy, they fail to explore the reliabi...

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Veröffentlicht in:	Proceedings (IEEE International Conference on Bioinformatics and Biomedicine) S. 2010 - 2017
Hauptverfasser:	He, Yuanpeng, Bi, Yali, Li, Lijian, Pun, Chi-Man, Jiao, Wenpin, Jin, Zhi
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 03.12.2024
Schlagworte:	Biomedical imaging Class-aware evidential fusion Data models Deep learning Heterogeneous networks Image segmentation Mutual evidential deep learning Predictive models Reliability Semi-supervised medical segmentation Semisupervised learning Training Uncertainty
ISSN:	2156-1133
Online-Zugang:	Volltext
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