Aggregating Multi-Annotator Segmentations for Medical Images
Just like the last term, I decided to present on a topic spanning 2-3 papers instead of a single paper. This time, I chose to present on how existing works “aggregate” multi-annotator segmentations for medical images. These are the papers that I covered in this presentation: Warfield et al., “Simultaneous Truth and Performance Level Estimation (STAPLE): An Algorithm for the Validation of Image Segmentation”, IEEE Transactions on Medical Imaging, 2004 [URL]. Kats et al., “A Soft STAPLE Algorithm Combined with Anatomical Knowledge”, MICCAI 2019 [URL]. Zhang et al., “Learning to Segment When Experts Disagree”, MICCAI 2020 [URL]. Here are the slides I made to present this topic in our reading group: ...