1. Clinical Validation of an Algorithm for Rapid and Accurate Automated Segmentation of Intracoronary Optical Coherence Tomography Image

    Clinical Validation of an Algorithm for Rapid and Accurate Automated Segmentation of Intracoronary Optical Coherence Tomography Image

    Objectives The analysis of intracoronary optical coherence tomography (OCT) images is based on manual identification of the lumen contours and relevant structures. However, manual image segmentation is a cumbersome and time-consuming process, subject to significant intra- and inter-observer variability. This study aims to present and validate a fully-automated method for segmentation of intracoronary OCT images. Methods We studied 20 coronary arteries (mean length = 39.7 ± 10.0 mm) from 20 patients who underwent a clinically indicated cardiac catheterization. The OCT images (n = 1812) were segmented manually, as well as with a fully-automated approach. A semi-automated variation of the fully-automated algorithm ...

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