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Biomed Opt Express. 2012 Dec 01;3(12):3291-303. doi: 10.1364/BOE.3.003291. Epub 2012 Nov 20.

Fully automatic three-dimensional visualization of intravascular optical coherence tomography images: methods and feasibility in vivo.

Biomedical optics express

Giovanni J Ughi, Tom Adriaenssens, Walter Desmet, Jan D'hooge

Affiliations

  1. Cardiovascular Diseases, University Hospitals Leuven, & Department of Cardiovascular Sciences, KU Leuven, Belgium.

PMID: 23243578 PMCID: PMC3521298 DOI: 10.1364/BOE.3.003291

Abstract

Intravascular optical coherence tomography (IV-OCT) is an imaging modality that can be used for the assessment of intracoronary stents. Recent publications pointed to the fact that 3D visualizations have potential advantages compared to conventional 2D representations. However, 3D imaging still requires a time consuming manual procedure not suitable for on-line application during coronary interventions. We propose an algorithm for a rapid and fully automatic 3D visualization of IV-OCT pullbacks. IV-OCT images are first processed for the segmentation of the different structures. This also allows for automatic pullback calibration. Then, according to the segmentation results, different structures are depicted with different colors to visualize the vessel wall, the stent and the guide-wire in details. Final 3D rendering results are obtained through the use of a commercial 3D DICOM viewer. Manual analysis was used as ground-truth for the validation of the segmentation algorithms. A correlation value of 0.99 and good limits of agreement (Bland Altman statistics) were found over 250 images randomly extracted from 25 in vivo pullbacks. Moreover, 3D rendering was compared to angiography, pictures of deployed stents made available by the manufacturers and to conventional 2D imaging corroborating visualization results. Computational time for the visualization of an entire data sets resulted to be ~74 sec. The proposed method allows for the on-line use of 3D IV-OCT during percutaneous coronary interventions, potentially allowing treatments optimization.

Keywords: (100.6890) Three-dimensional image processing; (170.4500) Optical coherence tomography; (330.5000) Vision - patterns and recognition

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