{"version":1,"kind":"Article","sha256":"","slug":"678","location":"","dependencies":[],"doi":"10.54294/ub0ptg","thumbnail":"https://pub.desci.com/ipfs/bafkreibysurwhnbtqnzgtnmonbd6f75iirplb52gaf6pyatubyaohncnpm","frontmatter":{"title":"Semi-automated cardiac segmentation on cine magnetic resonance images using GVF-Snake deformable models","abstract":"The segmentation of left ventricular structures is necessary for the evaluation of the ejection fraction (EF) and the myocardial mass (LVM). A semi-automated 2D algorithm using connected filters and a deformable model allowing an accurate endocardial detection was proposed. The epicardial border was deduced using a deformable model restricted inside a region of interest defined from the endocardial border. Papillary muscles were detected using a fuzzy k-means algorithm. The method was applied to the challenge training and validation databases, consisting of 15 subjects each. The evaluation was performed using the tools provided by the challenge. For both datasets, results show a mean Dice metric of 0.89 for endocardial borders (0.92 for epicardial borders). Overall average perpendicular distance was 2.2 mm. Very good correlation was obtained for the EF and LVM parameters. Visual overall rating given by the challenge’s cardiologist was 1.2. Segmentation was robust and performed successfully on both datasets. ","license":"You are licensing your work to Kitware Inc. under the\nCreative Commons Attribution License Version 3.0.\n\nKitware Inc. agrees to the following:\n\nKitware is free\n * to copy, distribute, display, and perform the work\n * to make derivative works\n * to make commercial use of the work\n\nUnder the following conditions:\n\\\"by Attribution\\\" - Kitware must attribute the work in the manner specified by the author or licensor.\n\n * For any reuse or distribution, they must make clear to others the license terms of this work.\n * Any of these conditions can be waived if they get permission from the copyright holder.\n\nYour fair use and other rights are in no way affected by the above.\n\nThis is a human-readable summary of the Legal Code (the full license) available at\nhttp://creativecommons.org/licenses/by/3.0/legalcode","keywords":["cine MRI","deformation models","segmentation","evaluation"],"authors":[{"name":"Constantinides, Constantin","email":"cconstan@imed.jussieu.fr","affiliations":["Inserm"],"corresponding":true},{"name":"Chenoune, Yasmina","affiliations":[]},{"name":"Kachenoura, Nadjia","affiliations":[]},{"name":"Roullot, Elodie","affiliations":[]},{"name":"Mousseaux, Elie","affiliations":[]},{"name":"Herment, Alain","affiliations":[]},{"name":"Frouin, Frederique","affiliations":[]}],"date_submitted":"2009-07-26 19:08:40","external_publication_id":678,"revision_cids":["bafkreihu2q2ld5mhujskyj6rdmijoqkfjstvk67nnkoryroqp3gt2g47yq"],"thumbnail":"https://pub.desci.com/ipfs/bafkreibysurwhnbtqnzgtnmonbd6f75iirplb52gaf6pyatubyaohncnpm"},"mdast":{"type":"root"},"downloads":[{"url":"https://ipfs.desci.com/ipfs/bafkreifcx5pza4qn2c6pczp6zymrokmk4pthvex3age2ppknyd72ohmb3m","title":"root/insight-journal-metadata.json","filename":"insight-journal-metadata.json","extra":{"size_bytes":6690,"type":"file"}},{"url":"https://dweb.link/ipfs/bafkreid7ssydbthvpoz6zf25qbw7xye7xarqrlf7wkpth4uvkgq5qjrx3e","title":"root/article.pdf","filename":"article.pdf","extra":{"size_bytes":177958,"type":"file"}}],"references":{"cite":{"order":["ref1","ref2","ref3","ref4","ref5","ref6","ref7","ref8","ref9"]},"data":{"ref1":{"label":"ref1","enumerator":"1","url":"https://doi.org/10.1002/jmri.21798","html":"An Automated Estimation of Regional Mean Transition Times and Radial Velocities from Cine Magnetic Resonance Images. 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