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Intravascular optical coherence tomography (IV-OCT) allows evaluation of atherosclerotic plaques; however, plaque characterization is performed by visual assessment and requires a trained expert for interpretation of the large data sets. Here, we present a novel computational method for automated IV-OCT plaque characterization. This method is based on the modeling of each A-line of an IV-OCT data set as a linear combination of a number of depth profiles. After estimating these depth profiles by means of an alternating least square optimization strategy, they are automatically classified to predefined tissue types based on their morphological characteristics. The performance of our proposed method was evaluated with IV-OCT scans of cadaveric human coronary arteries and corresponding tissue histopathology. Our results suggest that this methodology allows automated identification of fibrotic and lipid-containing plaques. Moreover, this novel computational method has the potential to enable high throughput atherosclerotic plaque characterization. © 2016 Optical Society of America.
Image analysis; Medical and biological imaging; Optical coherence tomography; Pattern recognition; Tissue characterization Characterization; Computational methods; Image analysis; Image classification; Medical imaging; Pattern recognition; Tissue; Alternating least squares; Automated identification; Automatic classification; Human coronary arteries; Medical and biological imaging; Morphological characteristic; Plaque characterizations; Tissue characterization; Optical tomography; lipid; algorithm; Article; atherosclerotic plaque; cell structure; coronary artery; entropy; histopathology; human; human tissue; mathematical computing; optical coherence tomography; polarization; process optimization; sensitivity and specificity; validation process
Automatic classification of atherosclerotic plaques imaged with intravascular OCT
National Institute of Biomedical Imaging and Bioengineering, NIBIB: P41EB015903
National Heart, Lung, and Blood Institute, NHLBI: 1R01HL111361
Generically Dependent Continuant
RDF description of Automatic classification of atherosclerotic plaques imaged with intravascular OCT - http://orbis.uaslp.mx/vivo/individual/scopus4631
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