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Background: Automated carotid intima-media thickness (cIMT) measurement from B-mode ultrasound is important for cardiovascular risk stratification. Direct comparisons of deep learning architectures on the same cohort under controlled conditions remain limited. This study aimed to compare the accuracy and computational cost of three deep learning architectures with the commercial AtheroEdge™ 2.0 (AE 2.0) system for carotid ultrasound analysis.
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
