Cardiovascular events are considered as the leading cause of death in the developed countries. It has been reported that there is a higher probability of cardiovascular events in the case of vulnerable plaques. Intra-plaque neovascularization and inflammation are considered as important indications of plaque vulnerability. The purpose of this research was to develop a semi-automatic method of quantifying carotid plaque neovascularization using contrast-enhanced ultrasound images, thus enabling assessment of plaque vulnerability. Contrast-enhanced ultrasound examination of the carotid artery was performed by applying low mechanical index and harmonics imaging using pulse inversion. An algorithm was developed that implemented several image processing methods to automatically quantify neovascularization and reconstruct its vascular tree in the atheromatous plaque. Neovascularization area and the number of inflammatory cells were also calculated. The algorithm was designed to detect and track “contrast spots” in the images using Multidimensional Dynamic Programming. Classification of tracking outlines of the contrast agent movements to blood vessels and artifacts was performed. Grading of the neovascularization load within the plaque was also applied. The last step of the research includes development of computerized simulation, to examine the algorithm abilities to cope with 3D volumetric data.