Intraplaque neovascularization (IPN) is linked to progressive atherosclerotic disease and plaque instability. Contrast enhanced ultrasound (CEUS) can detect these microvessels. Quantification of IPN may allow early detection of vulnerable plaques. We developed a semi-automatic quantification of IPN in CEUS, with motion compensation, contrast spot detection, tracking and classification, and vascular tree reconstruction. Side-by-side CEUS and B-mode carotid images were analyzed (Philips iU22, L9-3 linear array). The plaque motion pattern was obtained from B-mode with block matching (BM) and multidimensional dynamic programming (MDP) and applied to CEUS images for motion correction. In BM, a 6×4mm fixed template was scanned over a 6×2mm search region and normalized correlation coefficients were used in MDP to find the optimal 2D displacement path over time. Image sequences were divided into sets of 10 frames with 80% overlap. In frame 1 of each set, artificial bubble templates detect contrast bubbles within plaque. Templates of 1.3×1.3mm around detected objects were tracked over 10 frames using BM and MDP. Tracks were classified as moving bubbles or artifacts based on their motion. From the overlapping sets, tracks were merged and vessel paths quantified. Automated detection/ tracking / grading of IPN were validated against manual tracking and visual grading by two physicians in 28 plaques. Our algorithm detected 101 of 104 visually identified contrast spots. In 90 of 101 objects (89%), mean error between automated and manual tracking was < 0.5mm. 81 detected objects (78%) were correctly classified into artifacts and microvessels. Two physicians independently scored plaques into 4 grades of IPN. Automated IPN score was identical to visual scoring in 64%, 1 grade difference in 27% and 2 grades in 9%, which is very comparable to the interobserver differences (68%, 25%, 7%). Our algorithm can successfully detect and track contrast bubbles, classify objects into microvessels and artifacts, and reconstruct microvessel trees. The automated IPN score is equivalent to an expert visual score.