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Found 4 papers, 4 papers with code
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation -- Analysis of Ranking Metrics and Benchmarking Results
In this study, we explore and evaluate a metric developed during the BraTS 2019-2020 task on uncertainty quantification (QU-BraTS), and designed to assess and rank uncertainty estimates for brain tumor multi-compartment segmentation.
Towards Robust General Medical Image Segmentation
The reliability of Deep Learning systems depends on their accuracy but also on their robustness against adversarial perturbations to the input data.
The Medical Segmentation Decathlon
Segmentation is so far the most widely investigated medical image processing task, but the various segmentation challenges have typically been organized in isolation, such that algorithm development was driven by the need to tackle a single specific clinical problem.
SIMBA: Specific Identity Markers for Bone Age Assessment
With this lack of available methods as motivation, we present SIMBA: Specific Identity Markers for Bone Age Assessment.
