This chapter focuses on the algorithms implemented in CASCADE to perform the four principal processing steps in carotid plaque characterization. It presents an overall framework for measuring the volumes of atherosclerotic plaque components in the carotid artery. To evaluate the effects of plaque composition on outcome, noninvasive imaging techniques must be paired with algorithms to segment the plaque into its constituent components and quantify the relative amounts of each. The extent of high-density regions in computed tomography (CT) images of vessel walls is associated with the extent of calcification, and can be used as a risk factor for heart attack and stroke. The image processing challenge for measuring morphological indices of atherosclerotic plaque is one of boundary detection. From the lumen and wall boundaries, a number of morphological indices can be derived. These include the minimal lumen area, maximal wall area, total wall volume, and maximal wall thickness.