CMRSegTools: An open-source software enabling reproducible research in segmentation of acute myocardial infarct in CMR images Article Swipe
William Romero
,
Magalie Viallon
,
Joël Spaltenstein
,
Lorena Petrusca
,
Olivier Bernard
,
Loïc Belle
,
Patrick Clarysse
,
Pierre Croisille
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1371/journal.pone.0274491
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1371/journal.pone.0274491
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.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1371/journal.pone.0274491
- OA Status
- gold
- Cited By
- 7
- References
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- Related Works
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4295445031Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1371/journal.pone.0274491Digital Object Identifier
- Title
-
CMRSegTools: An open-source software enabling reproducible research in segmentation of acute myocardial infarct in CMR imagesWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
-
2022-09-13Full publication date if available
- Authors
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William Romero, Magalie Viallon, Joël Spaltenstein, Lorena Petrusca, Olivier Bernard, Loïc Belle, Patrick Clarysse, Pierre CroisilleList of authors in order
- Landing page
-
https://doi.org/10.1371/journal.pone.0274491Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1371/journal.pone.0274491Direct OA link when available
- Concepts
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Segmentation, Computer science, DICOM, Plug-in, Visualization, Software, Bespoke, Artificial intelligence, Image segmentation, Myocardial infarction, Image processing, Computer vision, Medicine, Image (mathematics), Cardiology, Programming language, Political science, LawTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
7Total citation count in OpenAlex
- Citations by year (recent)
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2025: 4, 2024: 2, 2023: 1Per-year citation counts (last 5 years)
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47Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.results | 98 |
| abstract_inverted_index.several | 242 |
| abstract_inverted_index.testing | 202 |
| abstract_inverted_index.(labeled | 205 |
| abstract_inverted_index.American | 162 |
| abstract_inverted_index.Learning | 218 |
| abstract_inverted_index.Magnetic | 15 |
| abstract_inverted_index.advanced | 154 |
| abstract_inverted_index.analysis | 130, 156 |
| abstract_inverted_index.clinical | 8, 137 |
| abstract_inverted_index.cohorts. | 138 |
| abstract_inverted_index.creating | 58 |
| abstract_inverted_index.creation | 198 |
| abstract_inverted_index.database | 116 |
| abstract_inverted_index.deployed | 12 |
| abstract_inverted_index.designed | 72 |
| abstract_inverted_index.enabling | 82 |
| abstract_inverted_index.evaluate | 19 |
| abstract_inverted_index.features | 122, 206 |
| abstract_inverted_index.in-house | 53 |
| abstract_inverted_index.methods, | 153, 219 |
| abstract_inverted_index.reducing | 24 |
| abstract_inverted_index.sharing. | 99 |
| abstract_inverted_index.software | 50, 71 |
| abstract_inverted_index.studies, | 36 |
| abstract_inverted_index.studies. | 245 |
| abstract_inverted_index.training | 200 |
| abstract_inverted_index.Resonance | 16 |
| abstract_inverted_index.automatic | 150 |
| abstract_inverted_index.includes, | 140 |
| abstract_inverted_index.language. | 194 |
| abstract_inverted_index.libraries | 185 |
| abstract_inverted_index.performed | 46 |
| abstract_inverted_index.platform. | 234 |
| abstract_inverted_index.research. | 63 |
| abstract_inverted_index.17-segment | 165 |
| abstract_inverted_index.algorithms | 95 |
| abstract_inverted_index.assessment | 224 |
| abstract_inverted_index.commercial | 49 |
| abstract_inverted_index.components | 178 |
| abstract_inverted_index.developing | 177 |
| abstract_inverted_index.integrated | 172, 233 |
| abstract_inverted_index.introduces | 66 |
| abstract_inverted_index.leveraging | 114 |
| abstract_inverted_index.management | 117 |
| abstract_inverted_index.myocardial | 27, 41, 79 |
| abstract_inverted_index.processing | 182 |
| abstract_inverted_index.strategies | 21 |
| abstract_inverted_index.supervised | 216 |
| abstract_inverted_index.Association | 164 |
| abstract_inverted_index.CMRSegTools | 139, 195 |
| abstract_inverted_index.application | 70 |
| abstract_inverted_index.comparative | 223 |
| abstract_inverted_index.development | 56 |
| abstract_inverted_index.implemented | 105 |
| abstract_inverted_index.integration | 92 |
| abstract_inverted_index.interaction | 121 |
| abstract_inverted_index.obstruction | 211 |
| abstract_inverted_index.open-source | 69 |
| abstract_inverted_index.parameters, | 90 |
| abstract_inverted_index.programming | 193 |
| abstract_inverted_index.statistical | 155 |
| abstract_inverted_index.CMRSegTools: | 67 |
| abstract_inverted_index.OsiriX/Horos | 111 |
| abstract_inverted_index.irreversible | 26 |
| abstract_inverted_index.reperfusion. | 33 |
| abstract_inverted_index.reproducible | 62 |
| abstract_inverted_index.segmentation | 37, 75, 87, 144, 152, 168, 227 |
| abstract_inverted_index.standardised | 97 |
| abstract_inverted_index.successfully | 239 |
| abstract_inverted_index.closed-source | 54 |
| abstract_inverted_index.microvascular | 210 |
| abstract_inverted_index.user-assisted | 143 |
| abstract_inverted_index.visualisation | 158, 184 |
| abstract_inverted_index.quantification | 39, 77 |
| abstract_inverted_index.functionalities | 118 |
| abstract_inverted_index.left-ventricle, | 147 |
| abstract_inverted_index.post-processing | 101 |
| abstract_inverted_index.cardioprotective | 20 |
| abstract_inverted_index.state-of-the-art | 86 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5112341585, https://openalex.org/A5055991510 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 8 |
| corresponding_institution_ids | https://openalex.org/I4210133838 |
| citation_normalized_percentile.value | 0.75677116 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |