Does an automated deep learning-based paradigm provide fast and reliable detection and quantification of high-risk plaque lesions in B-mode common carotid ultrasound scans in an asymptomatic Japanese cohort?
An automated deep learning-based system can rapidly and reliably detect and quantify high-risk plaque lesions in common carotid ultrasound scans.
The proposed study demonstrates a fast, accurate, and reliable solution for early detection and quantification of plaque lesions in common carotid artery ultrasound scans. The system runs on a test US image in <1 second, proving overall performance to be clinically reliable.
Jain et al. (Fri,) studied this question.