Semi-supervised Strong-Teacher Consistency Learning for few-shot cardiac MRI image segmentation.
Journal:
Computer methods and programs in biomedicine
PMID:
39893807
Abstract
BACKGROUND AND OBJECTIVE: Cardiovascular disease is a leading cause of mortality worldwide. Automated analysis of heart structures in MRI is crucial for effective diagnostics. While supervised learning has advanced the field of medical image segmentation, it however requires extensive labelled data, which is often limited for cardiac MRI.