Video segmentation of the common carotid artery intima media complex

The correct identification of the intima-media thickness (IMT) of the common carotid artery (CCA) walls has a high clinical relevance as it represents one of the most reliable predictor for future cardiovascular events. In this work we propose and evaluate an integrated system for the segmentation of the intima-media complex (IMC) and the lumen diameter in longitudinal ultrasound video of the CCA based on normalization, speckle reduction filtering (with a first order statistics filter) and snakes segmentation. The algorithm is initialized in the first video frame of the cardiac cycle by an automated initialization procedure and the borders of the far wall and near wall of the CCA are estimated. The IMC and the carotid diameter are then segmented automatically in the consecutive video frames for one cardiac cycle. The proposed algorithm was evaluated on 10 longitudinal ultrasound B-mode videos of the CCA and is compared with the manual tracings of a neurovascular expert, for every 20 frames in a time span of 3-5 seconds, covering in general 1-2 cardiac cycles. The algorithm estimated an IMT_mean± standard deviation of (0.72±0.22) mm while the manual results were (0.70±0.19). The mean maximum and minimum diameter was (7.08±1.37) mm and (6.53±1.13) mm respectively. The results were validated based on statistical measures and univariate statistical analysis. It was shown that there was no significant difference between the snakes segmentation measurements and the manual measurements. The proposed integrated system could successfully segment the IMC in ultrasound CCA video sequences thus complementing manual measurements.