Comparative Benchmarking of Failure Detection Methods in Medical Image
Segmentation: Unveiling the Role of Confidence Aggregation
Comparative Benchmarking of Failure Detection Methods in Medical Image
Segmentation: Unveiling the Role of Confidence Aggregation
Semantic segmentation is an essential component of medical image analysis research, with recent deep learning algorithms offering out-of-the-box applicability across diverse datasets. Despite these advancements, segmentation failures remain a significant concern for real-world clinical applications, necessitating reliable detection mechanisms. This paper introduces a comprehensive benchmarking framework aimed at evaluating failure …