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Standardized evaluation system for left ventricular segmentation algorithms in 3D echocardiography.
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2015 (English)In: IEEE Transactions on Medical Imaging, ISSN 0278-0062, E-ISSN 1558-254XArticle in journal (Refereed) Epub ahead of print
Abstract [en]

Real-time 3D Echocardiography (RT3DE) has been proven to be an accurate tool for left ventricular (LV) volume assessment. However, identification of the LV endocardium remains a challenging task, mainly because of the low tissue/blood contrast of the images combined with typical artifacts. Several semi and fully automatic algorithms have been proposed for segmenting the endocardium in RT3DE data in order to extract relevant clinical indices, but a systematic and fair comparison between such methods has so far been impossible due to the lack of a publicly available common database. Here, we introduce a standardized evaluation framework to reliably evaluate and compare the performance of the algorithms developed to segment the LV border in RT3DE. A database consisting of 45 multivendor cardiac ultrasound recordings acquired at different centers with corresponding reference measurements from 3 experts are made available. The algorithms from nine research groups were quantitatively evaluated and compared using the proposed online platform. The results showed that the best methods produce promising results with respect to the experts' measurements for the extraction of clinical indices, and that they offer good segmentation precision in terms of mean distance error in the context of the experts' variability range. The platform remains open for new submissions.

Place, publisher, year, edition, pages
2015.
Keyword [en]
image segmentation, level set, local phase analysis, shape model
National Category
Medical Image Processing
Research subject
Medical Technology
Identifiers
URN: urn:nbn:se:kth:diva-180465DOI: 10.1109/TMI.2015.2503890PubMedID: 26625409ScopusID: 2-s2.0-84963805370OAI: oai:DiVA.org:kth-180465DiVA: diva2:894109
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QP 201601

Available from: 2016-01-14 Created: 2016-01-14 Last updated: 2016-01-14Bibliographically approved

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Wang, ChunliangSmedby, Örjan
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