Intra-plaque neovascularization is considered to be an important indication for plaque vulnerability. We propose a semi-automatic algorithm that may supply quantitative analysis of neovasculature and reconstruction of its tree, thus enabling assessment of plaque vulnerability. An algorithm for automatic contrast spot detection and for tracking these spots using Multidimensional Dynamic Programming was developed to map the intra-plaque neovascularization. Classification of contrast tracks into blood vessels and artifacts was performed, based on their motion pattern characteristics. Seventy-three different contrast spots in 25 plaques were visually identified. The automatic contrast spot detection method found 70of these objects. In 65 objects the automatic tracking determined the contrast motion correctly. In addition, the objects were correctly classified in 89% of the cases. These results show that the method can successfully quantify features that are linked to vulnerability of the carotid plaque.