Τίτλος:
Clinical validation of an algorithm for rapid and accurate automated
segmentation of intracoronary optical coherence tomography images
Γλώσσες Τεκμηρίου:
Αγγλικά
Περίληψη:
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 semi-automated 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 semi-automated 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 semi-automated 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. (C) 2014 Elsevier Ireland Ltd. All rights reserved.
Συγγραφείς:
Chatzizisis, Yiannis S.
Koutkias, Vassilis G.
Toutouzas,
Konstantinos
Giannopoulos, Andreas
Chouvarda, Ioanna
Riga,
Maria
Antoniadis, Antonios P.
Cheimariotis, Grigorios and
Doulaverakis, Charalampos
Tsampoulatidis, Ioannis
Bouki,
Konstantina
Kompatsiaris, Ioannis
Stefanadis, Christodoulos and
Maglaveras, Nicos
Giannoglou, George D.
Περιοδικό:
International Journal of Cardiology
Εκδότης:
Elsevier Ireland Ltd
Λέξεις-κλειδιά:
Optical coherence tomography; Image processing; Image segmentation;
Method comparison study
DOI:
10.1016/j.ijcard.2014.01.071
