Research Papers: Imaging

Methodology for fully automated segmentation and plaque characterization in intracoronary optical coherence tomography images

[+] Author Affiliations
Lambros S. Athanasiou

University of Ioannina, Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, GR 45110 Ioannina, Greece

Christos V. Bourantas

ThoraxCenter, Erasmus Medical Center, ’s-Gravendijkwal 230, 3015 CE Rotterdam, The Netherlands

George Rigas

University of Ioannina, Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, GR 45110 Ioannina, Greece

FORTH-Institute of Molecular Biology and Biotechnology, Department of Biomedical Research, GR 45110 Ioannina, Greece

Antonis I. Sakellarios

University of Ioannina, Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, GR 45110 Ioannina, Greece

Themis P. Exarchos

University of Ioannina, Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, GR 45110 Ioannina, Greece

FORTH-Institute of Molecular Biology and Biotechnology, Department of Biomedical Research, GR 45110 Ioannina, Greece

Panagiotis K. Siogkas

University of Ioannina, Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, GR 45110 Ioannina, Greece

Andrea Ricciardi

Ettore Sansavini Health Science Foundation, 48100 Ravenna, Italy

Katerina K. Naka

University of Ioannina, Medical School, Michaelidion Cardiac Center and Department of Cardiology, GR 45110 Ioannina, Greece

Michail I. Papafaklis

Brigham and Women’s Hospital, Harvard Medical School Cardiovascular Division, Boston, Massachusetts 02115

Lampros K. Michalis

University of Ioannina, Medical School, Michaelidion Cardiac Center and Department of Cardiology, GR 45110 Ioannina, Greece

Francesco Prati

San Giovanni Hospital, Interventional Cardiology, Via dell’Amba Aradam 8, 00184 Rome, Italy

Dimitrios I. Fotiadis

University of Ioannina, Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, GR 45110 Ioannina, Greece

FORTH-Institute of Molecular Biology and Biotechnology, Department of Biomedical Research, GR 45110 Ioannina, Greece

J. Biomed. Opt. 19(2), 026009 (Feb 13, 2014). doi:10.1117/1.JBO.19.2.026009
History: Received June 26, 2013; Revised January 16, 2014; Accepted January 17, 2014
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Abstract.  Optical coherence tomography (OCT) is a light-based intracoronary imaging modality that provides high-resolution cross-sectional images of the luminal and plaque morphology. Currently, the segmentation of OCT images and identification of the composition of plaque are mainly performed manually by expert observers. However, this process is laborious and time consuming and its accuracy relies on the expertise of the observer. To address these limitations, we present a methodology that is able to process the OCT data in a fully automated fashion. The proposed methodology is able to detect the lumen borders in the OCT frames, identify the plaque region, and detect four tissue types: calcium (CA), lipid tissue (LT), fibrous tissue (FT), and mixed tissue (MT). The efficiency of the developed methodology was evaluated using annotations from 27 OCT pullbacks acquired from 22 patients. High Pearson’s correlation coefficients were obtained between the output of the developed methodology and the manual annotations (from 0.96 to 0.99), while no significant bias with good limits of agreement was shown in the Bland-Altman analysis. The overlapping areas ratio between experts’ annotations and methodology in detecting CA, LT, FT, and MT was 0.81, 0.71, 0.87, and 0.81, respectively.

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© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Lambros S. Athanasiou ; Christos V. Bourantas ; George Rigas ; Antonis I. Sakellarios ; Themis P. Exarchos, et al.
"Methodology for fully automated segmentation and plaque characterization in intracoronary optical coherence tomography images", J. Biomed. Opt. 19(2), 026009 (Feb 13, 2014). ; http://dx.doi.org/10.1117/1.JBO.19.2.026009


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