Segmentation of Medical Images using Fuzzy Mathematical Morphology

Currently, Mathematical Morphology (MM) has become a powerful tool in Digital Image Processing (DIP). It allows processing images to enhance fuzzy areas, segment objects, detect edges and analyze structures. The techniques developed for binary images are a major step forward in the application of th...

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Detalles Bibliográficos
Autores principales: Bouchet, A., Pastore, Juan Ignacio, Ballarín, Virginia Laura
Formato: Articulo
Lenguaje:Inglés
Publicado: 2007
Materias:
Ciencias Informáticas
mathematical morphology
Fuzzy set
Segmentation
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/9565
http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct07-10.pdf
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-9565
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
mathematical morphology
Fuzzy set
Segmentation
spellingShingle Ciencias Informáticas
mathematical morphology
Fuzzy set
Segmentation
Bouchet, A.
Pastore, Juan Ignacio
Ballarín, Virginia Laura
Segmentation of Medical Images using Fuzzy Mathematical Morphology
topic_facet Ciencias Informáticas
mathematical morphology
Fuzzy set
Segmentation
description Currently, Mathematical Morphology (MM) has become a powerful tool in Digital Image Processing (DIP). It allows processing images to enhance fuzzy areas, segment objects, detect edges and analyze structures. The techniques developed for binary images are a major step forward in the application of this theory to gray level images. One of these techniques is based on fuzzy logic and on the theory of fuzzy sets. Fuzzy sets have proved to be strongly advantageous when representing inaccuracies, not only regarding the spatial localization of objects in an image but also the membership of a certain pixel to a given class. Such inaccuracies are inherent to real images either because of the presence of indefinite limits between the structures or objects to be segmented within the image due to noisy acquisitions or directly because they are inherent to the image formation methods. Our approach is to show how the fuzzy sets specifically utilized in MM have turned into a functional tool in DIP.
format Articulo
Articulo
author Bouchet, A.
Pastore, Juan Ignacio
Ballarín, Virginia Laura
author_facet Bouchet, A.
Pastore, Juan Ignacio
Ballarín, Virginia Laura
author_sort Bouchet, A.
title Segmentation of Medical Images using Fuzzy Mathematical Morphology
title_short Segmentation of Medical Images using Fuzzy Mathematical Morphology
title_full Segmentation of Medical Images using Fuzzy Mathematical Morphology
title_fullStr Segmentation of Medical Images using Fuzzy Mathematical Morphology
title_full_unstemmed Segmentation of Medical Images using Fuzzy Mathematical Morphology
title_sort segmentation of medical images using fuzzy mathematical morphology
publishDate 2007
url http://sedici.unlp.edu.ar/handle/10915/9565
http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct07-10.pdf
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AT ballarinvirginialaura segmentationofmedicalimagesusingfuzzymathematicalmorphology
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