Automated tissue characterization of in vivo atherosclerotic plaques by intravascular optical coherence tomography images.

ABSTRACT: Intravascular optical coherence tomography (IVOCT) is rapidly becoming the method of choice for the in vivo investigation of coronary artery disease. While IVOCT visualizes atherosclerotic plaques with a resolution <20µm, image analysis in terms of tissue composition is currently performed by a time-consuming manual procedure based on the qualitative interpretation of image features. We illustrate an algorithm for the automated and systematic characterization of IVOCT atherosclerotic tissue. The proposed method consists in a supervised classification of image pixels according to textural features combined with the estimated value of the optical attenuation coefficient. IVOCT images of 64 plaques, from 49 in vivo IVOCT data sets, constituted the algorithm's training and testing data sets. V

SUBMITTER: Ughi GJ 

PROVIDER: S-EPMC3704084 | biostudies-literature | 2013 Jul

REPOSITORIES: biostudies-literature