Completely automated multiresolution edge snapper (CAMES): A new technique for an accurate carotid ultrasound IMT measurement and its validation on a multi-institutional database

Abstract

Since 2005, our research team has been developing automated techniques for carotid artery (CA) wall segmentation and intima-media thickness (IMT) measurement. We developed a snake-based technique (which we named CULEX 1,2), a method based on an integrated approach of feature extraction, fitting, and classification (which we named CALEX3), and a watershed transform based algorithm4. Each of the previous methods substantially consisted in two distinct stages: Stage-I - Automatic carotid artery detection. In this step, intelligent procedures were adopted to automatically locate the CA in the image frame. Stage-II - CA wall segmentation and IMT measurement. In this second step, the CA distal (or far) wall is segmented in order to trace the lumen-intima (LI) and media-adventitia (MA) boundaries. The distance between the LI/MA borders is the IMT estimation. The aim of this paper is the description of a novel and completely automated technique for carotid artery segmentation and IMT measurement based on an innovative multi-resolution approach. © 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).