Sistema de Apoyo para la Cuantificación Semiautomática de Fibrosis Pulmonar en Imágenes de TAC

D. E. Rodríguez Obregón; A. R. Mejía Rodríguez; G. Dorantes Méndez; E. R. Arce Santana; S. Charleston Villalobos; M. Mejía Ávila; H. Mateos Toledo; R. González Camarena; A. T. Aljama Corrales

doi:10.17488/RMIB.38.1.11

Support System for Semiautomatic Quantification of Pulmonary Fibrosis in CT Images

Authors

D. E. Rodríguez Obregón Facultad de Ciencias, Universidad Autónoma de San Luis Potosí,
A. R. Mejía Rodríguez Facultad de Ciencias, Universidad Autónoma de San Luis Potosí,
G. Dorantes Méndez Facultad de Ciencias, Universidad Autónoma de San Luis Potosí,
E. R. Arce Santana Facultad de Ciencias, Universidad Autónoma de San Luis Potosí,
S. Charleston Villalobos Departamento de Ingeniería Eléctrica, Universidad Autónoma Metropolitana - Iztapalapa
M. Mejía Ávila Instituto Nacional de Enfermedades Respiratorias
H. Mateos Toledo Instituto Nacional de Enfermedades Respiratorias
R. González Camarena Departamento de Ciencias de la Salud, Universidad Autónoma Metropolitana - Iztapalapa
A. T. Aljama Corrales Departamento de Ingeniería Eléctrica, Universidad Autónoma Metropolitana - Iztapalapa

DOI:

https://doi.org/10.17488/RMIB.38.1.11

Keywords:

Pulmonar Fibrosis Estimation, Computed Tomography, Chan-Vese, Medical Image Segmentation

Abstract

A method to estimate the pulmonary fibrosis in computed tomography (CT) imaging is presented. A semi-automatic segmentation algorithm based on the Chan-Vese method was used. The proposed method shows a similar fibrosis region with respect to clinical expert. However, the results need to be validated in a bigger data base. The proposed method approximates a fibrosis percentage that allows to achieve this procedure easily in order to support its implementation in the clinical practice minimizing the clinical expert subjectivity and generating a quantitative estimation of fibrosis region.

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Published

2017-01-15

How to Cite

Rodríguez Obregón, D. E., Mejía Rodríguez, A. R., Dorantes Méndez, G., Arce Santana, E. R., Charleston Villalobos, S., Mejía Ávila, M., Mateos Toledo, H., González Camarena, R., & Aljama Corrales, A. T. (2017). Support System for Semiautomatic Quantification of Pulmonary Fibrosis in CT Images. Revista Mexicana De Ingenieria Biomedica, 38(1), 155–165. https://doi.org/10.17488/RMIB.38.1.11

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Issue

Vol. 38 No. 1 (2017): Enero - Abril

Section

Special Issue

License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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