Abstract
The question is: what size of the region of interest is likely to lead to better training outcomes? To answer this: The U-net is used for semantic segmentation. Image interpolation algorithms are used to double the cropped image size and create new datasets. Depending on the selected image interpolation algorithm category, non-original classes are created in the ground truth images thus a filtering strategy is introduced to remove such spurious classes. Evaluation results of effects on the myocardium segmentation and quantification of the myocardial infarction are provided and discussed.
Abstract (translated)
URL
https://arxiv.org/abs/2101.11508