Paper Info
Title
Atherosclerotic plaque characterization in Optical Coherence Tomography images.
Abstract
Optical Coherence Tomography (OCT) is a fiber--optic imaging modality which produces high resolution tomographic images of the coronary lumen and outer vessel wall. While OCT images present morphological information in highly resolved detail, the characterization of the various plaque components relies on trained readers. The aim of this study is to extract a set of features in grayscale OCT images and to use them in order to classify the atherosclerotic plaque. Intensity and texture based features we used in order to classify the plaque in four plaque types: Calcium (C), Lipid Pool (LP), Fibrous Tissue (FT) and Mixed Plaque (MP). 50 OCT annotated images from 3 patients were used to train and test the proposed plaque characterization method. Using a Random Forests classifier overall classification accuracy 80.41% is reported.
Year
DOI
Venue
2011
10.1109/IEMBS.2011.6091112
EMBC
Keywords
Field
DocType
mixed plaque,optical tomography,fibrous tissue,outer vessel wall,optical coherence tomography,blood vessels,fiber optic imaging modality,lipid pool,grayscale oct images,feature extraction,atherosclerotic plaque characterization,coronary lumen,medical image processing,lipidomics,accuracy,random forest,optical imaging,tomography,high resolution,fiber optic
Computer vision,Optical coherence tomography,Computer science,Tomography,Feature extraction,Artificial intelligence,Optical tomography,Optical imaging,Grayscale
Conference
Volume
ISSN
ISBN
2011
1557-170X
978-1-4244-4122-8
Citations 
PageRank 
References 
4
0.88
0
Authors
6
Name
Order
Citations
PageRank
Lambros S. Athanasiou1339.54
Themis P Exarchos223524.31
Katerina K Naka3175.20
Lampros K. Michalis417721.89
F Prati562.02
D I Fotiadis641.22