COMPUTER-AIDED DIAGNOSIS OF BRAIN TUMORS USING IMAGE ENHANCEMENT AND FUZZY LOGIC

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1. Verfasser: JEAN MARIE VIANNEY-KINANI
Format: Artículo científico
Sprache:en
Veröffentlicht: Universidad Nacional de Colombia 2014
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author JEAN MARIE VIANNEY-KINANI
author_facet JEAN MARIE VIANNEY-KINANI
contents COMPUTER-AIDED DIAGNOSIS OF BRAIN TUMORS USING IMAGE ENHANCEMENT AND FUZZY LOGIC JEAN MARIE VIANNEY-KINANI ALBERTO J. ROSALES-SILVA FRANCISCO J. GALLEGOS-FUNES ALFONSO ARELLANO Ingeniería MRI Clustering Segmentation Region of interest A robust medical image processing system depends upon a variety of aspects, including a proper image enhancement, and an optimal segmentation. An algorithm was proposed in this paper to facilitate the implementation of these two steps. First a Magnetic Resonance (MR) image is enhanced via spatial domain filtering and its contrast is improved, next, the image is segmented using fuzzy C-mean clustering, then the region of interest which might be the tumor or edema, is detected and delineated. The key advantage of this image processing pipeline is the simultaneous use of features computed from the intensity properties of the image in a cascading pattern which makes the computation self-contained. Performance evaluation of the proposed algorithm was carried out on brain images from different MRI’s and the algorithm proved to be successful, comparing it with other dedicated applications. 2014 artículo científico 0012-7353 https://www.redalyc.org/articulo.oa?id=49630072018 en http://www.redalyc.org/revista.oa?id=496 Dyna application/pdf Universidad Nacional de Colombia Dyna (Colombia) Num.183 Vol.81
format Artículo científico
id redalyc_49630072018
institution Redalyc
language en
publishDate 2014
publisher Universidad Nacional de Colombia
spellingShingle COMPUTER-AIDED DIAGNOSIS OF BRAIN TUMORS USING IMAGE ENHANCEMENT AND FUZZY LOGIC
JEAN MARIE VIANNEY-KINANI
Ingeniería
MRI
Clustering
Segmentation
Region of interest
COMPUTER-AIDED DIAGNOSIS OF BRAIN TUMORS USING IMAGE ENHANCEMENT AND FUZZY LOGIC JEAN MARIE VIANNEY-KINANI ALBERTO J. ROSALES-SILVA FRANCISCO J. GALLEGOS-FUNES ALFONSO ARELLANO Ingeniería MRI Clustering Segmentation Region of interest A robust medical image processing system depends upon a variety of aspects, including a proper image enhancement, and an optimal segmentation. An algorithm was proposed in this paper to facilitate the implementation of these two steps. First a Magnetic Resonance (MR) image is enhanced via spatial domain filtering and its contrast is improved, next, the image is segmented using fuzzy C-mean clustering, then the region of interest which might be the tumor or edema, is detected and delineated. The key advantage of this image processing pipeline is the simultaneous use of features computed from the intensity properties of the image in a cascading pattern which makes the computation self-contained. Performance evaluation of the proposed algorithm was carried out on brain images from different MRI’s and the algorithm proved to be successful, comparing it with other dedicated applications. 2014 artículo científico 0012-7353 https://www.redalyc.org/articulo.oa?id=49630072018 en http://www.redalyc.org/revista.oa?id=496 Dyna application/pdf Universidad Nacional de Colombia Dyna (Colombia) Num.183 Vol.81
title COMPUTER-AIDED DIAGNOSIS OF BRAIN TUMORS USING IMAGE ENHANCEMENT AND FUZZY LOGIC
topic Ingeniería
MRI
Clustering
Segmentation
Region of interest
url https://www.redalyc.org/articulo.oa?id=49630072018