In:
PLOS ONE, Public Library of Science (PLoS), Vol. 17, No. 9 ( 2022-9-13), p. e0274491-
Abstract:
In the last decade, a large number of clinical trials have been deployed using Cardiac Magnetic Resonance (CMR) to evaluate cardioprotective strategies aiming at reducing the irreversible myocardial damage at the time of reperfusion. In these studies, segmentation and quantification of myocardial infarct lesion are often performed with a commercial software or an in-house closed-source code development thus creating a barrier for reproducible research. This paper introduces CMRSegTools: an open-source application software designed for the segmentation and quantification of myocardial infarct lesion enabling full access to state-of-the-art segmentation methods and parameters, easy integration of new algorithms and standardised results sharing. This post-processing tool has been implemented as a plug-in for the OsiriX/Horos DICOM viewer leveraging its database management functionalities and user interaction features to provide a bespoke tool for the analysis of cardiac MR images on large clinical cohorts. CMRSegTools includes, among others, user-assisted segmentation of the left-ventricle, semi- and automatic lesion segmentation methods, advanced statistical analysis and visualisation based on the American Heart Association 17-segment model. New segmentation methods can be integrated into the plug-in by developing components based on image processing and visualisation libraries such as ITK and VTK in C++ programming language. CMRSegTools allows the creation of training and testing data sets (labeled features such as lesion, microvascular obstruction and remote ROI) for supervised Machine Learning methods, and enables the comparative assessment of lesion segmentation methods via a single and integrated platform. The plug-in has been successfully used by several CMR imaging studies.
Type of Medium:
Online Resource
ISSN:
1932-6203
DOI:
10.1371/journal.pone.0274491
DOI:
10.1371/journal.pone.0274491.g001
DOI:
10.1371/journal.pone.0274491.g002
DOI:
10.1371/journal.pone.0274491.g003
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10.1371/journal.pone.0274491.g004
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10.1371/journal.pone.0274491.g005
DOI:
10.1371/journal.pone.0274491.g006
DOI:
10.1371/journal.pone.0274491.g007
DOI:
10.1371/journal.pone.0274491.g008
DOI:
10.1371/journal.pone.0274491.t001
DOI:
10.1371/journal.pone.0274491.s001
DOI:
10.1371/journal.pone.0274491.s002
DOI:
10.1371/journal.pone.0274491.s003
DOI:
10.1371/journal.pone.0274491.r001
DOI:
10.1371/journal.pone.0274491.r002
DOI:
10.1371/journal.pone.0274491.r003
DOI:
10.1371/journal.pone.0274491.r004
DOI:
10.1371/journal.pone.0274491.r005
DOI:
10.1371/journal.pone.0274491.r006
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2022
detail.hit.zdb_id:
2267670-3
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