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Bibliographic Details
Main Author: Fabián Torres-Robles
Format: Artículo científico
Language:en
Published: Universidad Nacional de Colombia 2014
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Online Access:https://www.redalyc.org/articulo.oa?id=49631663004
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author Fabián Torres-Robles
author_facet Fabián Torres-Robles
contents A robust neuro-fuzzy classifier for the detection of cardiomegaly in digital chest radiographies Fabián Torres-Robles Alberto Jorge Rosales-Silva Francisco Javier Gallegos-Funes Ivonne Bazán-Trujillo Ingeniería Cardiomegaly fuzzy classifier chest image radiographies Radial Basis Function neural network We present a novel procedure that automatically and reliably determines the presence of cardiomegaly in chest image radiographies. The cardiothoracic ratio (CTR) shows the relationship between the size of the heart and the size of the chest. The proposed scheme uses a robust fuzzy classifier to find the correct feature values of chest size, and the right and left heart boundaries to measure the heart enlargement to detect cardiomegaly. The proposed approach uses classical morphology operations to segment the lungs providing low computational complexity and the proposed fuzzy method is robust to find the correct measures of CTR providing a fast computation because the fuzzy rules use elementary arithmetic operations to perform a good detection of cardiomegaly. Finally, we improve the classification results of the proposed fuzzy method using a Radial Basis Function (RBF) neural network in terms of accuracy, sensitivity, and specificity. 2014 artículo científico 0012-7353 https://www.redalyc.org/articulo.oa?id=49631663004 en http://www.redalyc.org/revista.oa?id=496 Dyna application/pdf Universidad Nacional de Colombia Dyna (Colombia) Num.186 Vol.81
format Artículo científico
id redalyc_49631663004
language en
publishDate 2014
publisher Universidad Nacional de Colombia
spellingShingle A robust neuro-fuzzy classifier for the detection of cardiomegaly in digital chest radiographies
Fabián Torres-Robles
Ingeniería
Cardiomegaly
fuzzy classifier
chest image radiographies
Radial Basis Function neural network
A robust neuro-fuzzy classifier for the detection of cardiomegaly in digital chest radiographies Fabián Torres-Robles Alberto Jorge Rosales-Silva Francisco Javier Gallegos-Funes Ivonne Bazán-Trujillo Ingeniería Cardiomegaly fuzzy classifier chest image radiographies Radial Basis Function neural network We present a novel procedure that automatically and reliably determines the presence of cardiomegaly in chest image radiographies. The cardiothoracic ratio (CTR) shows the relationship between the size of the heart and the size of the chest. The proposed scheme uses a robust fuzzy classifier to find the correct feature values of chest size, and the right and left heart boundaries to measure the heart enlargement to detect cardiomegaly. The proposed approach uses classical morphology operations to segment the lungs providing low computational complexity and the proposed fuzzy method is robust to find the correct measures of CTR providing a fast computation because the fuzzy rules use elementary arithmetic operations to perform a good detection of cardiomegaly. Finally, we improve the classification results of the proposed fuzzy method using a Radial Basis Function (RBF) neural network in terms of accuracy, sensitivity, and specificity. 2014 artículo científico 0012-7353 https://www.redalyc.org/articulo.oa?id=49631663004 en http://www.redalyc.org/revista.oa?id=496 Dyna application/pdf Universidad Nacional de Colombia Dyna (Colombia) Num.186 Vol.81
title A robust neuro-fuzzy classifier for the detection of cardiomegaly in digital chest radiographies
topic Ingeniería
Cardiomegaly
fuzzy classifier
chest image radiographies
Radial Basis Function neural network
url https://www.redalyc.org/articulo.oa?id=49631663004