Multi-rater Prompting for Ambiguous Medical Image Segmentation

arXiv:2404.07580v1 Announce Type: new
Abstract: Multi-rater annotations commonly occur when medical images are independently annotated by multiple experts (raters). In this paper, we tackle two challenges arisen in multi-rater annotations for medical image segmentation (called ambiguous medical image segmentation): (1) How to train a deep learning model when a group of raters produces a set of diverse but plausible annotations, and (2) how to fine-tune the model efficiently when computation resources are not available for re-training the entire model on …

abstract annotations arxiv challenges cs.cv deep learning experts image images medical multiple paper prompting segmentation train type