The identification, quantification and characterization of coronary atherosclerotic plaque has a major influence on diagnosis and treatment of coronary artery disease (CAD). Recent studies have reported the ability of Computed Tomography Coronary Angiography (CTCA) to identify non-invasively coronary plaque features. In this study, we present a novel methodology for the identification of the plaque burden of the coronary artery and the volumetric quantification of calcified plaques (CP) and non-calcified plaques (NCP), utilizing CTCA images in comparison with virtual histology intravascular ultrasound (VH-IVUS). The proposed methodology includes six steps: CTCA images pre-processing, vessel centerline extraction using Multistencil Fast Marching Method (MSFM), estimation of membership sigmoidal distribution functions, implementation of an extension of active contour models using prior shapes for the lumen, the outer wall and CP segmentation, detection and quantification of NCP and finally three-dimensional (3D) models construction. Bland-Altman analyses were performed to assess the agreement between the presented methodology and VH-IVUS. Assessment of CP and NCP volume and length of lesion length 18 lesions indicated excellent correlation with VH-IVUS, (r = 0.92, p < 0.001), (r= 0.95, p < 0.001) and (r= 0.81, p < 0.001), respectively.