Semi-automatic detection of hepatic tumor in computed tomography images
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Fecha
2019
Autores
Sáenz, F
Vera, M
López, J
Huérfano, Y
Valbuena, O
Vera, M I
Gelvez-Almeida, E
Salazar-Torres, J
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Editor
IOP Publishing
Resumen
In this work, the main purpose is develop a computational segmentation strategy for
liver tumor semiautomatic detection. This strategy considers three-dimensional computed
tomography images and it consists of techniques application that, on the one hand, diminish the
noise and detect the edges of the objects present in those images and, on the other hand, generate
the liver tumor morphology. For this, the sequence of techniques composed of gaussian
smoothing, gradient magnitude, median filter, region growing and binary morphological dilation
are used. The value obtained, for the metric called Dice score, show a good correlation between
manual segmentation, performed by a hepatologist, and the tumor segmentation obtained using
the proposed technique. This type of segmentation is the extreme utility for the characterization
of hepatic tumors and the planning of the clinical behavior to be followed in the treatment of this
human liver disease.