When Experts Disagree: Characterizing Annotator Variability for Vessel Segmentation in DSA Images
By: M. Geshvadi , G. So , D. D. Chlorogiannis and more
Potential Business Impact:
Helps doctors see blood vessel problems more clearly.
We analyze the variability among segmentations of cranial blood vessels in 2D DSA performed by multiple annotators in order to characterize and quantify segmentation uncertainty. We use this analysis to quantify segmentation uncertainty and discuss ways it can be used to guide additional annotations and to develop uncertainty-aware automatic segmentation methods.
Similar Papers
What Can We Learn from Inter-Annotator Variability in Skin Lesion Segmentation?
CV and Pattern Recognition
Helps doctors find skin cancer better.
Rethinking Intracranial Aneurysm Vessel Segmentation: A Perspective from Computational Fluid Dynamics Applications
CV and Pattern Recognition
Helps doctors see brain bubbles better for treatment.
Addressing Annotation Scarcity in Hyperspectral Brain Image Segmentation with Unsupervised Domain Adaptation
CV and Pattern Recognition
Helps doctors see tiny blood vessels in the brain.