Automated Vessel Lumen Identification in B-Mode Carotid Ultrasound Images Using Convolutional Neural Networks

OBJECTIVE: Carotid ultrasound is a screening modality used to aid in the prevention of ischemic stroke in high-risk patients. B-mode ultrasound of the carotid artery identifies the vessel wall, lumen, and potential plaque burden within the artery, but requires qualified technicians and physicians to perform and interpret the study. To date, utilization of automated state of the art machine-learning techniques like deep learning in this realm have been limited. Herein, we describe our initial experience with the use of a deep convolutional neural network called U-Net for lumen identification in carotid ultrasounds images.