eng URI http://hdl.handle.net/10795/3175 ασθένεια πρόληψη των ασθενειών ιατρική διάγνωση 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 was also applied. Using certain lumen size and lumen shape characteristics, the fully- and semi-automated segmentation algorithms were validated over manual segmentation, which was considered as the gold standard. Results: Linear regression and Bland–Altman analysis demonstrated that both the fully-automated and semiautomated segmentation had a very high agreement with the manual segmentation, with the semi-automated approach being slightly more accurate than the fully-automated method. The fully-automated and semiautomated OCT segmentation reduced the analysis time by more than 97% and 86%, respectively, compared to manual segmentation. Conclusions: In the current work we validated a fully-automated OCT segmentation algorithm, as well as a semiautomated variation of it in an extensive “real-life” dataset of OCT images. The study showed that our algorithm can perform rapid and reliable segmentation of OCT images. 13 pp. LOMv1.0 creator LOMv1.0 publisher LOMv1.0 Project Executing Organisation 2014-01-24 Digital Library of the Operational Programme "Education and Lifelong Learning" abstract types Text Optical coherence tomography Image processing Image segmentation Method comparison study OCT Automated segmentation algorithms Οπτική συνεκτική τομογραφία Αρτηρίες Επεξεργασία εικόνων Διάγνωση ασθενειών http://www.sciencedirect.com/science/article/pii/S0167527314002800 3206084 application/pdf http://repository.edulll.gr/edulll/bitstream/10795/3175/2/3175_1.63_%ce%94%ce%97%ce%9c_24_1_14.pdf URI http://hdl.handle.net/10795/3175 LOMv1.0creator 2016-05-17T13:26:32Z LOMv1.0validator 2016-05-17T13:26:32Z LOMv1.0 gre no no Copyright EYD-EPEDBM (Operational Programme "Education and Lifelong Learning")