A new dataset for measuring the performance of blood vessel segmentation methods under distribution shifts

arXiv:2301.04517v4 Announce Type: replace
Abstract: Creating a dataset for training supervised machine learning algorithms can be a demanding task. This is especially true for medical image segmentation since one or more specialists are usually required for image annotation, and creating ground truth labels for just a single image can take up to several hours. In addition, it is paramount that the annotated samples represent well the different conditions that might affect the imaged tissues as well as possible changes in …

abstract algorithms annotation arxiv cs.cv dataset distribution image labels machine machine learning machine learning algorithms measuring medical performance segmentation supervised machine learning training true truth type