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Computational strategy for the segmentation of the aortic annulus in cardiac computed tomography images

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dc.contributor.authorValbuena, O.
dc.contributor.authorVera, M.
dc.contributor.authorHuérfano, Y.
dc.contributor.authorGelvez, E.
dc.contributor.authorSalazar, J.
dc.contributor.authorMolina, V.
dc.contributor.authorSáenz, F.
dc.contributor.authorVera, M I.
dc.contributor.authorSalazar, W.
dc.date.accessioned2019-03-06T20:47:17Z
dc.date.available2019-03-06T20:47:17Z
dc.date.issued2019
dc.description.abstractThe purpose of this research is to segment the aortic annulus, present in cardiac computed tomography images, from a computational strategy generated using global similarity enhancement, vector least squares support machines and a segmentation technique named region growing. This enhancement is obtained by applying the following steps: a) Obtain an image of similarity by calculating the absolute value of the arithmetic subtraction that considers the original image and an image of contours. The image of contours is obtained by processing the original image with a filter based on the magnitude of the gradient. b) Is is processed with a Gaussian filter, generating a smoothed similarity image. On the other hand, considering the smoothed similarity image, the least squares support machines are used both to construct two cutting planes (that isolate the aortic artery) and to detect the coordinates of a seed voxel. In order to produce the morphology of the aortic valve annulus, the seed voxel initializes the technique of growth of regions during the segmentation process. From this morphology, some useful quantitative descriptors are calculated for the aortic ring characterization.eng
dc.identifier.issn09767673
dc.identifier.urihttp://hdl.handle.net/20.500.12442/2738
dc.language.isoengeng
dc.publisherIOP Publishingeng
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.licenseLicencia de Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacionalspa
dc.sourceJournal of Physicseng
dc.sourceIOP Conf. Series: Journal of Physics: Conf. Series 1160 (2019) 012005eng
dc.source.uridoi:10.1088/1742-6596/1160/1/012005eng
dc.subjectCardiac tomographyeng
dc.subjectaortic ringeng
dc.subjectAortic aneurysmseng
dc.titleComputational strategy for the segmentation of the aortic annulus in cardiac computed tomography imageseng
dc.typeConferenceeng
dcterms.referencesRamírez L, Martín P, Gil P, Quevedo V, Morera O, Amalfi E, Valdivia D, Medina A 2011 Análisis cuantitativo del anillo aórtico en pacientes con estenosis aórtica severa mediante cardio-TAC de 64 detectores previo al implante de prótesis valvular aórtica percutánea Rev Esp Cardiol. 64(3) 396spa
dcterms.referencesCarabello B 2011 Valvulopatías Goldman's Cecil Medicine ed L Goldman and D Ausiello (Philadelphia: Elsevier) chapter 75 p 524eng
dcterms.referencesShapiro L and Stockman G 2001 Computer vision (New Jersey: Prentice Hall)eng
dcterms.referencesSun W, Martin C and Pham T 2014 Computational modeling of cardiac valve function and intervention. Annual Review of Biomedical Engineering 16 53eng
dcterms.referencesPrimak A, McCollough C, Bruesewitz M, Zhang J and Fletcher J 2006 Relationship between noise, dose, and pitch in cardiac multi-detector row CT Radiographics 26(6) 1785eng
dcterms.referencesKroft L, De Roos A, Geleijns J 2007 Artifacts in ecg-synchronized mdct coronary angiography Am. J. Roentgenol. 189(3) 581eng
dcterms.referencesKirisli H et al. 2010 Evaluation of a multi–atlas based method for segmentation of cardiac CTA data: A large scale, multi–center and multi–vendor study Med Phys 37 6279eng
dcterms.referencesZheng Y, John M, Liao R, Nöttling A, Boese J, Kempfert J, Walther T, Brockmann G, Comaniciu D 2012 Automatic aorta segmentation and valve landmark detection in C–Arm CT for transcatheter aortic valve implantation IEEE Transactions on Medical Imaging 31 2307eng
dcterms.referencesGrbic S, Ionasec R, Vitanovski D, Voigt I, Wang Y, Georgescu B, Navab N, Comaniciu D 2012 Complete valvular heart apparatus model from 4D cardiac CT Medical Image Analysis 16 1003eng
dcterms.referencesFernández N, González S, Rodríguez C, Ciobanu C and Saint–Pierre G 2012 FE analysis applied for validation of a biostable aortic valve replacement device: stent and leaflet material selection Int. J. of Biomedical Engineering and Technology 9 378eng
dcterms.referencesGrbic S, Mansi T, Ionasec R, Voigt I, Houle H, John M, Schoebinger M, Navab N, Comaniciu D 2013 Image–based computational models for TAVI planning: From CT images to implant deployment Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2013 vol 8150, ed Kensaku Mori, Ichiro Sakuma, Yoshinobu Sato, Christian Barillot and Nassir Navab (Berlin Heidelberg: Springer- Verlag) 395eng
dcterms.referencesElattar M, Wiegerinck E, Planken R, Vanbavel E, Van Assen H, Baan J and Marquering H 2014 Automatic segmentation of the aortic root in ct angiography of candidate patients for transcatheter aortic valve implantation Medical & Biological Engineering & Computing 52 611eng
dcterms.referencesGhesu F, Krubasik E, Georgescu B, Singh V, Zheng Y, Hornegger J and Comaniciu D 2016 Marginal space deep learning: efficient architecture for volumetric image parsing IEEE Transactions on Medical Imaging 35 1217eng
dcterms.referencesLe Couteulx S, Caudron J, Dubourg B and Dacher J 2018 Multidetector computed tomography sizing of aortic annulus prior to transcatheter aortic valve replacement (TAVR): Variability and impact of observer experience Diagnostic and Interventional Imaging 99(5) 279eng
dcterms.referencesAbdeldayem E, Ibrahim A and Osman A 2018 CT aortic annulus parameters for pre-operative TAVI assessment: a comparative study between manual post processing and automated software tool The Egyptian Journal of Radiology and Nuclear Medicine 49(2) 352eng
dcterms.referencesAlmolla R, Enaba M, Abdel-Rahman H 2017 Pre-procedural multi-slice computed tomography (MSCT) in aortic valve replacement. Important measurements The Egyptian Journal of Radiology and Nuclear Medicine 48(2) 365eng
dcterms.referencesMurphy D et al. 2016 Dynamism of the aortic annulus: Effect of diastolic versus systolic ct annular measurements on device selection in transcatheter aortic valve replacement (TAVR) Journal of Cardiovascular Computed Tomography 10(1) 37eng
dcterms.referencesVera M, Bravo A, Garreau M and Medina R 2011 Similarity Enhancement for Automatic Segmentation of Cardiac Structures in Computed Tomography Annual International Conference of the IEEE Engineering in Medicine and Biology Society (Boston: IEEE) p 8094eng
dcterms.referencesPratt W 2007 Digital image processing (New York: John Wiley & Sons Inc)eng
dcterms.referencesBravo A, Clemente J, Vera M, Avila J, Medina R 2010 An hybrid boundary region left ventricle segmentation in computed tomography Proceedings of the International Conference on Computer Vision Theory and Applications 2 107-114eng
dcterms.referencesReal R and Vargas J 1996 The probabilistic basis of Jaccard's index of similarity Sys Biol 45(3) 380eng

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