Semi-Supervised Multimodal Multi-Instance Learning for Aortic Stenosis Diagnosis

arXiv:2403.06024v1 Announce Type: cross
Abstract: Automated interpretation of ultrasound imaging of the heart (echocardiograms) could improve the detection and treatment of aortic stenosis (AS), a deadly heart disease. However, existing deep learning pipelines for assessing AS from echocardiograms have two key limitations. First, most methods rely on limited 2D cineloops, thereby ignoring widely available Doppler imaging that contains important complementary information about pressure gradients and blood flow abnormalities associated with AS. Second, obtaining labeled data is difficult. There are often …

abstract arxiv automated cs.cv cs.et cs.lg deep learning detection diagnosis disease heart disease however imaging instance interpretation key limitations multimodal pipelines semi-supervised treatment type