Patent ID: 8532360

Claim:
A computer-implemented method comprising: receiving biomedical imaging data and patient demographic data corresponding to a current scan of a patient; checking, in real time, to determine if an artery identified in the biomedical imaging data has atherosclerosis deposit in a proximal wall; acquiring arterial data related to the artery as a combination of longitudinal and transverse for B-mode Ultrasound, CT, MR, 3D IVUS, or 3D carotid Ultrasound for cross-section images; using a data processor to automatically estimate the wall borders in longitudinal ultrasound or transverse slices in B-mode ultrasound, CT, MR, 3D IVUS, or 3D carotid Ultrasound images; using the data processor to automatically recognize three sets of combinations of features using: a combination 1 consisting of: (a) higher order spectra (HOS) computing the Normalized Bi-spectral Entropy and Normalized Bi-spectral Squared Entropy; (b) Discrete Wavelet Transform (DWT)-based, computing features including Average Horizontal Discrete Wavelet Coefficient (Dh 1 ), Average vertical Discrete Wavelet Coefficient (Dv 1 ), and Energy; and (c) Gray Level Co-occurrence Matrix-based, computing features including Texture Symmetry and Texture Entropy; a type 2 combination consisting of local binary pattern, law's mask energy and Wall Variability features, and a type 3 combination consisting of Higher Order Spectra, Trace Transform, Fuzzy Grayscale Level Co-occurrence Matrix (FGLCM) and Wall Variability; using the data processor to apply classifiers using four types of classifiers including: (a) Support Vector Machine; (b) Radial Basis Probabilistic Neural Network (RBPNN), (c) Nearest Neighbor (KNN) classifier, and (d) Decision Trees (DT) Classifier; and using the data processor to automatically recognize the artery as symptomatic or asymptomatic; and using the data processor to determine a cardiovascular risk score.