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Clinical validation of an algorithm for rapid and accurate automated segmentation of intracoronary optical coherence tomography images

Identifieur interne : 000132 ( Main/Exploration ); précédent : 000131; suivant : 000133

Clinical validation of an algorithm for rapid and accurate automated segmentation of intracoronary optical coherence tomography images

Auteurs : Yiannis S. Chatzizisis [Grèce] ; Vassilis G. Koutkias [Grèce] ; Konstantinos Toutouzas [Grèce] ; Andreas Giannopoulos [Grèce] ; Ioanna Chouvarda [Grèce] ; Maria Riga [Grèce] ; Antonios P. Antoniadis [Grèce] ; Grigorios Cheimariotis [Grèce] ; Charalampos Doulaverakis [Grèce] ; Ioannis Tsampoulatidis [Grèce] ; Konstantina Bouki [Grèce] ; Ioannis Kompatsiaris [Grèce] ; Christodoulos Stefanadis [Grèce] ; Nicos Maglaveras [Grèce] ; George D. Giannoglou [Grèce]

Source :

RBID : Pascal:14-0101693

Descripteurs français

English descriptors

Abstract

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 ocr 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.


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<s2>Thessaloniki</s2>
<s3>GRC</s3>
<sZ>1 aut.</sZ>
<sZ>4 aut.</sZ>
<sZ>7 aut.</sZ>
<sZ>15 aut.</sZ>
</inist:fA14>
<country>Grèce</country>
<wicri:noRegion>Thessaloniki</wicri:noRegion>
</affiliation>
</author>
</analytic>
<series>
<title level="j" type="main">International journal of cardiology</title>
<title level="j" type="abbreviated">Int. j. cardiol.</title>
<idno type="ISSN">0167-5273</idno>
<imprint>
<date when="2014">2014</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
<seriesStmt>
<title level="j" type="main">International journal of cardiology</title>
<title level="j" type="abbreviated">Int. j. cardiol.</title>
<idno type="ISSN">0167-5273</idno>
</seriesStmt>
</fileDesc>
<profileDesc>
<textClass>
<keywords scheme="KwdEn" xml:lang="en">
<term>Algorithm</term>
<term>Cardiology</term>
<term>Cardiovascular disease</term>
<term>Comparative study</term>
<term>Coronary artery</term>
<term>Decision tree</term>
<term>Image processing</term>
<term>Method study</term>
<term>Optical coherence tomography</term>
<term>Segmentation</term>
<term>Test validation</term>
</keywords>
<keywords scheme="Pascal" xml:lang="fr">
<term>Pathologie de l'appareil circulatoire</term>
<term>Validation test</term>
<term>Algorithme</term>
<term>Arbre décision</term>
<term>Traitement image</term>
<term>Segmentation</term>
<term>Artère coronaire</term>
<term>Tomographie en cohérence optique</term>
<term>Etude méthode</term>
<term>Etude comparative</term>
<term>Cardiologie</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front>
<div type="abstract" xml:lang="en">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 ocr 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.</div>
</front>
</TEI>
<affiliations>
<list>
<country>
<li>Grèce</li>
</country>
</list>
<tree>
<country name="Grèce">
<noRegion>
<name sortKey="Chatzizisis, Yiannis S" sort="Chatzizisis, Yiannis S" uniqKey="Chatzizisis Y" first="Yiannis S." last="Chatzizisis">Yiannis S. Chatzizisis</name>
</noRegion>
<name sortKey="Antoniadis, Antonios P" sort="Antoniadis, Antonios P" uniqKey="Antoniadis A" first="Antonios P." last="Antoniadis">Antonios P. Antoniadis</name>
<name sortKey="Bouki, Konstantina" sort="Bouki, Konstantina" uniqKey="Bouki K" first="Konstantina" last="Bouki">Konstantina Bouki</name>
<name sortKey="Cheimariotis, Grigorios" sort="Cheimariotis, Grigorios" uniqKey="Cheimariotis G" first="Grigorios" last="Cheimariotis">Grigorios Cheimariotis</name>
<name sortKey="Chouvarda, Ioanna" sort="Chouvarda, Ioanna" uniqKey="Chouvarda I" first="Ioanna" last="Chouvarda">Ioanna Chouvarda</name>
<name sortKey="Doulaverakis, Charalampos" sort="Doulaverakis, Charalampos" uniqKey="Doulaverakis C" first="Charalampos" last="Doulaverakis">Charalampos Doulaverakis</name>
<name sortKey="Giannoglou, George D" sort="Giannoglou, George D" uniqKey="Giannoglou G" first="George D." last="Giannoglou">George D. Giannoglou</name>
<name sortKey="Giannopoulos, Andreas" sort="Giannopoulos, Andreas" uniqKey="Giannopoulos A" first="Andreas" last="Giannopoulos">Andreas Giannopoulos</name>
<name sortKey="Kompatsiaris, Ioannis" sort="Kompatsiaris, Ioannis" uniqKey="Kompatsiaris I" first="Ioannis" last="Kompatsiaris">Ioannis Kompatsiaris</name>
<name sortKey="Koutkias, Vassilis G" sort="Koutkias, Vassilis G" uniqKey="Koutkias V" first="Vassilis G." last="Koutkias">Vassilis G. Koutkias</name>
<name sortKey="Maglaveras, Nicos" sort="Maglaveras, Nicos" uniqKey="Maglaveras N" first="Nicos" last="Maglaveras">Nicos Maglaveras</name>
<name sortKey="Riga, Maria" sort="Riga, Maria" uniqKey="Riga M" first="Maria" last="Riga">Maria Riga</name>
<name sortKey="Stefanadis, Christodoulos" sort="Stefanadis, Christodoulos" uniqKey="Stefanadis C" first="Christodoulos" last="Stefanadis">Christodoulos Stefanadis</name>
<name sortKey="Toutouzas, Konstantinos" sort="Toutouzas, Konstantinos" uniqKey="Toutouzas K" first="Konstantinos" last="Toutouzas">Konstantinos Toutouzas</name>
<name sortKey="Tsampoulatidis, Ioannis" sort="Tsampoulatidis, Ioannis" uniqKey="Tsampoulatidis I" first="Ioannis" last="Tsampoulatidis">Ioannis Tsampoulatidis</name>
</country>
</tree>
</affiliations>
</record>

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