A computational strategy for the identification of pulmonary squamous cell carcinoma in computerized tomography images
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Fecha
2019
Autores
Huerfano, Y.
Vera, M.
Gelvez, E.
Salazar, J.
Del Mar, A.
Valbuena, O.
Molina, V.
Título de la revista
ISSN de la revista
Título del volumen
Editor
IOP Publishing
Resumen
The objective of the work is to propose a computational strategy to identify lung
squamous cell carcinoma in three-dimensional databases (3D) of multislice computerized
tomography. This strategy consists of the pre-processing, segmentation, and post-processing
stages. During pre-processing, an anisotropic, gradient-based diffusion algorithm and a filter
bank are used to address artifact and image noise issues. During segmentation, the technique
called region growing is applied to pre-processed images. Finally, in the post-processing, a
morphological dilation filter is used to process the segmented images. In order to make value
judgments about the performance of the proposed strategy, the relative percentage error is used
to compare the dilated segmentations of the squamous cell carcinoma with the segmentations
of the squamous cell carcinoma generated, manually, by a pulmonologist. The combination of
parameters linked to the highest PrE, allows establishing the optimal parameters of each of the
algorithms that make up the proposed strategy.
Descripción
Palabras clave
Carcinoma, Tomography, Lungs-Diseases