Topological Concepts applied to Digital Image Processing

Autores
Pastore, Juan Ignacio; Bouchet, A.; Moler, Emilce Graciela; Ballarín, Virginia Laura
Año de publicación
2006
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This article describes an automatic method applicable to the segmentation of mediastinum Computerized Axial Tomography (CAT) images with tumors, by means of Alternating Sequential Filters (ASFs) of Mathematical Morphology, and connected components extraction based on continuous topology concepts. Digital images can be related to topological space structures, and then general topology principles can be straightforwardly implemented. This method allows not only to accurately determine the area and external boundary of the segmented structures but also to obtain their precise location. Throughout these last years, technological development has significantly improved diagnostic imaging, enabling renal tumor and incidental hepatic tumor detection -usually small in size- in younger people and with an eventually lower malignant potential. This has led to a remarkable advance in interventionist techniques such as cryosurgery and radiofrequency ablation, preventing, in some cases, major surgeries, decreasing morbid-mortality rate, hospital stay and total treatment costs. Notwithstanding this, both cryosurgery and radiofrequency ablation, through extremely low and high temperatures, respectively, kill tumor as well as healthy cells, rendering crucial the identification of tumors with an extraordinary spatial accuracy.
Facultad de Informática
Materia
Ciencias Informáticas
topological spaces
connected components
Segmentation
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/9542

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spelling Topological Concepts applied to Digital Image ProcessingPastore, Juan IgnacioBouchet, A.Moler, Emilce GracielaBallarín, Virginia LauraCiencias Informáticastopological spacesconnected componentsSegmentationThis article describes an automatic method applicable to the segmentation of mediastinum Computerized Axial Tomography (CAT) images with tumors, by means of Alternating Sequential Filters (ASFs) of Mathematical Morphology, and connected components extraction based on continuous topology concepts. Digital images can be related to topological space structures, and then general topology principles can be straightforwardly implemented. This method allows not only to accurately determine the area and external boundary of the segmented structures but also to obtain their precise location. Throughout these last years, technological development has significantly improved diagnostic imaging, enabling renal tumor and incidental hepatic tumor detection -usually small in size- in younger people and with an eventually lower malignant potential. This has led to a remarkable advance in interventionist techniques such as cryosurgery and radiofrequency ablation, preventing, in some cases, major surgeries, decreasing morbid-mortality rate, hospital stay and total treatment costs. Notwithstanding this, both cryosurgery and radiofrequency ablation, through extremely low and high temperatures, respectively, kill tumor as well as healthy cells, rendering crucial the identification of tumors with an extraordinary spatial accuracy.Facultad de Informática2006-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf80-84http://sedici.unlp.edu.ar/handle/10915/9542enginfo:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct06-4.pdfinfo:eu-repo/semantics/altIdentifier/issn/1666-6038info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc/3.0/Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-11-05T12:30:40Zoai:sedici.unlp.edu.ar:10915/9542Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-11-05 12:30:40.87SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Topological Concepts applied to Digital Image Processing
title Topological Concepts applied to Digital Image Processing
spellingShingle Topological Concepts applied to Digital Image Processing
Pastore, Juan Ignacio
Ciencias Informáticas
topological spaces
connected components
Segmentation
title_short Topological Concepts applied to Digital Image Processing
title_full Topological Concepts applied to Digital Image Processing
title_fullStr Topological Concepts applied to Digital Image Processing
title_full_unstemmed Topological Concepts applied to Digital Image Processing
title_sort Topological Concepts applied to Digital Image Processing
dc.creator.none.fl_str_mv Pastore, Juan Ignacio
Bouchet, A.
Moler, Emilce Graciela
Ballarín, Virginia Laura
author Pastore, Juan Ignacio
author_facet Pastore, Juan Ignacio
Bouchet, A.
Moler, Emilce Graciela
Ballarín, Virginia Laura
author_role author
author2 Bouchet, A.
Moler, Emilce Graciela
Ballarín, Virginia Laura
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
topological spaces
connected components
Segmentation
topic Ciencias Informáticas
topological spaces
connected components
Segmentation
dc.description.none.fl_txt_mv This article describes an automatic method applicable to the segmentation of mediastinum Computerized Axial Tomography (CAT) images with tumors, by means of Alternating Sequential Filters (ASFs) of Mathematical Morphology, and connected components extraction based on continuous topology concepts. Digital images can be related to topological space structures, and then general topology principles can be straightforwardly implemented. This method allows not only to accurately determine the area and external boundary of the segmented structures but also to obtain their precise location. Throughout these last years, technological development has significantly improved diagnostic imaging, enabling renal tumor and incidental hepatic tumor detection -usually small in size- in younger people and with an eventually lower malignant potential. This has led to a remarkable advance in interventionist techniques such as cryosurgery and radiofrequency ablation, preventing, in some cases, major surgeries, decreasing morbid-mortality rate, hospital stay and total treatment costs. Notwithstanding this, both cryosurgery and radiofrequency ablation, through extremely low and high temperatures, respectively, kill tumor as well as healthy cells, rendering crucial the identification of tumors with an extraordinary spatial accuracy.
Facultad de Informática
description This article describes an automatic method applicable to the segmentation of mediastinum Computerized Axial Tomography (CAT) images with tumors, by means of Alternating Sequential Filters (ASFs) of Mathematical Morphology, and connected components extraction based on continuous topology concepts. Digital images can be related to topological space structures, and then general topology principles can be straightforwardly implemented. This method allows not only to accurately determine the area and external boundary of the segmented structures but also to obtain their precise location. Throughout these last years, technological development has significantly improved diagnostic imaging, enabling renal tumor and incidental hepatic tumor detection -usually small in size- in younger people and with an eventually lower malignant potential. This has led to a remarkable advance in interventionist techniques such as cryosurgery and radiofrequency ablation, preventing, in some cases, major surgeries, decreasing morbid-mortality rate, hospital stay and total treatment costs. Notwithstanding this, both cryosurgery and radiofrequency ablation, through extremely low and high temperatures, respectively, kill tumor as well as healthy cells, rendering crucial the identification of tumors with an extraordinary spatial accuracy.
publishDate 2006
dc.date.none.fl_str_mv 2006-10
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info:eu-repo/semantics/publishedVersion
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info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/9542
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dc.language.none.fl_str_mv eng
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dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc/3.0/
Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc/3.0/
Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
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