Proc. SPIE. 9040, Medical Imaging 2014: Ultrasonic Imaging and Tomography
KEYWORDS: Ultrasonography, Image segmentation, Video, Chemical vapor deposition, Arteries, Software development, Electrocardiography, Signal detection, Autoregressive models, Simulation of CCA and DLA aggregates
Carotid intima-media thickness (CIMT) has proven to be sensitive for predicting individual risk of cardiovascular diseases (CVD). The CIMT is measured based on region of interest (ROIs) in end-diastolic ultrasound frames (EUFs). To interpret CIMT videos, in the current practice, the EUFs and ROIs must be manually selected, a process that is tedious and time consuming. To reduce CIMT interpretation time, this paper presents a novel method for automatically selecting EUFs and determining ROIs in ultrasound videos. The EUFs are selected based on the QRS complex of the electrocardiogram (ECG) signal associated with the ultrasound video, and the ROI is detected based on image intensity and curvature of the carotid artery bulb. Once a EUF is selected and its corresponding ROI is determined, our system measures CIMT using the snake algorithm extended with hard constraints [1,6-7] by computing the average thickness and maximum thickness, calculating the vascular age, and generating a patient’s report. In this study, we utilize 23 subjects. Each subject has 4 videos, and 3 EUFs are selected in each video, resulting in a total of 272 ROIs. By comparing with the reference provided by an expert for both frame selection and ROI detection, we achieve 92.96% sensitivity and 97.62% specificity for EUF selection, and 81.25% accuracy in ROI detection.