Computational strategy for the segmentation of the aortic annulus in cardiac computed tomography images
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Fecha
2019
Autores
Valbuena, O.
Vera, M.
Huérfano, Y.
Gelvez, E.
Salazar, J.
Molina, V.
Sáenz, F.
Vera, M I.
Salazar, W.
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Editor
IOP Publishing
Resumen
The 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.
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Palabras clave
Cardiac tomography, aortic ring, Aortic aneurysms