AINeutralarXiv – CS AI · 10h ago6/10
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Interpretable Probabilistic Medical Image Segmentation via Gaussian Process with Explicit Modelling of Annotation Bias and Variability
Researchers propose a novel Gaussian Process-based framework for medical image segmentation that explicitly models annotation bias and variability across multiple raters rather than encoding them implicitly. The approach improves uncertainty calibration in probabilistic predictions while maintaining segmentation accuracy, with quantifiable parameters reflecting individual annotator behavior.