Iterative fuzzy segmentation for an accurate delimitation of the breast region.
Identifieur interne : 000330 ( Main/Exploration ); précédent : 000329; suivant : 000331Iterative fuzzy segmentation for an accurate delimitation of the breast region.
Auteurs : Asma Touil [Tunisie] ; Karim Kalti [Tunisie]Source :
- Computer methods and programs in biomedicine [ 1872-7565 ] ; 2016.
Descripteurs français
- KwdFr :
- MESH :
- imagerie diagnostique : Région mammaire.
- Femelle, Humains, Logique floue, Mammographie.
English descriptors
- KwdEn :
- MESH :
- diagnostic imaging : Breast.
- Female, Fuzzy Logic, Humans, Mammography.
Abstract
In mammographic images, extracting different anatomical structures and tissues types is a critical requirement for the breast cancer diagnosis. For instance, separating breast and background regions increases the accuracy and efficiency of mammographic processing algorithms. In this paper, we propose a new region-based method to properly segment breast and background regions in mammographic images. These regions are estimated by an Iterative Fuzzy Breast Segmentation method (IFBS). Based on the Fuzzy C-Means (FCM) algorithm, IFBS method iteratively increases the precision of an initially extracted breast region. This proposal is evaluated using the MIAS database. Experimental results show high accuracy and reliability in breast extraction when compared with Ground-Truth (GT) images.
DOI: 10.1016/j.cmpb.2016.04.020
PubMed: 27282234
Affiliations:
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Le document en format XML
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Electronic address: asmaa.touil@gmail.com.</nlm:affiliation><country xml:lang="fr">Tunisie</country><wicri:regionArea>Computer Science Department, Faculty of Science of Monastir</wicri:regionArea><wicri:noRegion>Faculty of Science of Monastir</wicri:noRegion></affiliation></author><author><name sortKey="Kalti, Karim" sort="Kalti, Karim" uniqKey="Kalti K" first="Karim" last="Kalti">Karim Kalti</name><affiliation wicri:level="1"><nlm:affiliation>Computer Science Department, Faculty of Science of Monastir, Tunisia. Electronic address: karim.kalti@gmail.com.</nlm:affiliation><country xml:lang="fr">Tunisie</country><wicri:regionArea>Computer Science Department, Faculty of Science of Monastir</wicri:regionArea><wicri:noRegion>Faculty of Science of Monastir</wicri:noRegion></affiliation></author></analytic><series><title level="j">Computer methods and programs in biomedicine</title><idno type="eISSN">1872-7565</idno><imprint><date when="2016" type="published">2016</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Breast (diagnostic imaging)</term><term>Female (MeSH)</term><term>Fuzzy Logic (MeSH)</term><term>Humans (MeSH)</term><term>Mammography (MeSH)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Femelle (MeSH)</term><term>Humains (MeSH)</term><term>Logique floue (MeSH)</term><term>Mammographie (MeSH)</term><term>Région mammaire (imagerie diagnostique)</term></keywords><keywords scheme="MESH" qualifier="diagnostic imaging" xml:lang="en"><term>Breast</term></keywords><keywords scheme="MESH" qualifier="imagerie diagnostique" xml:lang="fr"><term>Région mammaire</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Female</term><term>Fuzzy Logic</term><term>Humans</term><term>Mammography</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Femelle</term><term>Humains</term><term>Logique floue</term><term>Mammographie</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">In mammographic images, extracting different anatomical structures and tissues types is a critical requirement for the breast cancer diagnosis. For instance, separating breast and background regions increases the accuracy and efficiency of mammographic processing algorithms. In this paper, we propose a new region-based method to properly segment breast and background regions in mammographic images. These regions are estimated by an Iterative Fuzzy Breast Segmentation method (IFBS). Based on the Fuzzy C-Means (FCM) algorithm, IFBS method iteratively increases the precision of an initially extracted breast region. This proposal is evaluated using the MIAS database. Experimental results show high accuracy and reliability in breast extraction when compared with Ground-Truth (GT) images. </div></front></TEI><affiliations><list><country><li>Tunisie</li></country></list><tree><country name="Tunisie"><noRegion><name sortKey="Touil, Asma" sort="Touil, Asma" uniqKey="Touil A" first="Asma" last="Touil">Asma Touil</name></noRegion><name sortKey="Kalti, Karim" sort="Kalti, Karim" uniqKey="Kalti K" first="Karim" last="Kalti">Karim Kalti</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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