Segmentation of medical images by region growing

Itzel Abundez Barrera; Citlalih Gutiérrez Estrada; Sergio Díaz Zagal; Martín De Jesús Nieto Perez

doi:10.1109/IRI.2008.4583071

Segmentation of medical images by region growing

Itzel Abundez Barrera, Citlalih Gutiérrez Estrada, Sergio Díaz Zagal, Martín De Jesús Nieto Perez

Research output: Contribution to conference › Paper

2 Scopus citations

Abstract

The possibility of combining different technologies and developing better performing systems that offer quality results leads to the creation of systems with enhanced adaptation and analysis. Such analysis allows the interaction with previously evaluated techniques, providing reliable, successful results. Such is the case for the research work detailed in this article, which is focused on a technique that allows reusing previously analyzed and formalized information with the support of the Unified Modeled Language (UML). Information is handled in modules aimed to generate the segmentation of medical images without intervention of a specialist. The purpose is to deliver regions of interest for the early detection of cervical cancer. ©2008 IEEE.

Original language	American English
Pages	441-444
Number of pages	4
DOIs	https://doi.org/10.1109/IRI.2008.4583071
State	Published - 23 Sep 2008
Externally published	Yes
Event	2008 IEEE International Conference on Information Reuse and Integration, IEEE IRI-2008 - Duration: 23 Sep 2008 → …

Conference

Conference	2008 IEEE International Conference on Information Reuse and Integration, IEEE IRI-2008
Period	23/09/08 → …

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/IRI.2008.4583071

Cite this

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abstract = "The possibility of combining different technologies and developing better performing systems that offer quality results leads to the creation of systems with enhanced adaptation and analysis. Such analysis allows the interaction with previously evaluated techniques, providing reliable, successful results. Such is the case for the research work detailed in this article, which is focused on a technique that allows reusing previously analyzed and formalized information with the support of the Unified Modeled Language (UML). Information is handled in modules aimed to generate the segmentation of medical images without intervention of a specialist. The purpose is to deliver regions of interest for the early detection of cervical cancer. {\textcopyright}2008 IEEE.",

author = "Barrera, {Itzel Abundez} and Estrada, {Citlalih Guti{\'e}rrez} and Zagal, {Sergio D{\'i}az} and Perez, {Mart{\'i}n De Jes{\'u}s Nieto}",

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AU - Estrada, Citlalih Gutiérrez

AU - Zagal, Sergio Díaz

AU - Perez, Martín De Jesús Nieto

PY - 2008/9/23

Y1 - 2008/9/23

N2 - The possibility of combining different technologies and developing better performing systems that offer quality results leads to the creation of systems with enhanced adaptation and analysis. Such analysis allows the interaction with previously evaluated techniques, providing reliable, successful results. Such is the case for the research work detailed in this article, which is focused on a technique that allows reusing previously analyzed and formalized information with the support of the Unified Modeled Language (UML). Information is handled in modules aimed to generate the segmentation of medical images without intervention of a specialist. The purpose is to deliver regions of interest for the early detection of cervical cancer. ©2008 IEEE.

AB - The possibility of combining different technologies and developing better performing systems that offer quality results leads to the creation of systems with enhanced adaptation and analysis. Such analysis allows the interaction with previously evaluated techniques, providing reliable, successful results. Such is the case for the research work detailed in this article, which is focused on a technique that allows reusing previously analyzed and formalized information with the support of the Unified Modeled Language (UML). Information is handled in modules aimed to generate the segmentation of medical images without intervention of a specialist. The purpose is to deliver regions of interest for the early detection of cervical cancer. ©2008 IEEE.

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ER -

Segmentation of medical images by region growing

Abstract

Conference

UN SDGs

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