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RESEARCH PRODUCT

Segmentation Integrating Watershed and Shape Priors Applied to Cardiac Delayed Enhancement MR Images

Danuta KrukTadeusz SliwaAlexandre CochetArnaud BoucherAlain Lalande

subject

DE-MRIComputer science[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/ImagingBiomedical EngineeringBiophysicsScale-space segmentation030204 cardiovascular system & hematology030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineSegmentationSørensen–Dice coefficientInformationMagnetic-Resonance ImagesSegmentationComputer vision[ SDV.IB ] Life Sciences [q-bio]/BioengineeringCardiac imaging[ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/ImagingOrientation (computer vision)business.industryImage segmentationGold standard (test)Computer aided diagnosisComputer-aided diagnosisGraph Cuts[SDV.IB]Life Sciences [q-bio]/BioengineeringArtificial intelligencebusinessShape priorsCardiac imaging

description

International audience; Background: In recent years, there has been a rapid rise in the use of shape priors applied to segmentation process of medical images. Previous approaches on left ventricle segmentation from Delayed-Enhancement Magnetic Resonance Imaging (DE-MRI) have focused on the extraction of myocardium or just diseased region in short axis orientation. However these studies did not take into account the segmentation of non-diseased myocardium from DE-MRI. The segmentation of non-diseased myocardium from DE-MRI, has some useful applications. For instance it can simplify the PET-MR registration process.Methods: This paper presents a novel semi-automatic segmentation method of non-diseased myocardium contours from DE-MRI based on watershed algorithm with shape priors application. The segmentation process was performed on long and short axis DE-MR images, acquired from patients with different cardiac diseases.Results: Segmented images were compared with gold standard contours performed by an experienced user. To assess our results the Dice Coefficient (DC) and Root Mean Square Distance (RMSD) were computed. The best value of these parameters was obtained for four cavity images (RMSD = 1.68 +/- 0.47 mm, DC = 0.78), and the computed value for two cavity images (RMSD = 1.93 +/- 0.38 mm, DC = 0.73) and short axis images (RMSD = 1.89 +/- 0.47 mm, DC = 0.71) were slightly lower.Conclusion: In conclusion, We have proposed a novel solution for non-diseased myocardium segmentation from DE-MRI, which brought very promising results. (C) 2017 AGBM. Published by Elsevier Masson SAS. All rights reserved.

https://hal-univ-bourgogne.archives-ouvertes.fr/hal-01627049