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An improved spatial FCM algorithm for cardiac image segmentation
Department of Biomedical Engineering, Faculty of Advance Medical Technology, Isfahan University of Medical Science.
Department of Biomedical Engineering, Faculty of Advance Medical Technology, Isfahan University of Medical Science.
Department of Biomedical Engineering, Faculty of Advance Medical Technology, Isfahan University of Medical Science.
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
2013 (English)In: 13th Iranian Conference on Fuzzy Systems: IFSC 2013, Qazvin, Iran; 27-29 August 2013, Piscataway, NJ: IEEE Communications Society, 2013, article id 6675656Conference paper, Published paper (Refereed)
Abstract [en]

Image segmentation is one of challenging field in medical image processing. Segmentation of cardiac wall is one of challenging work and it is very important step in evaluation of heart functionality by existing methods. For cardiac image analysis, Fuzzy C- Means (FCM) algorithm proved to be superior over the other clustering approaches in segmentation field. However, the nave FCM algorithm is sensitive to noise because of not considering the spatial information in the image. In this paper an improved FCM algorithm is formulated by incorporating the spatial domain neighborhood information into the membership function for clustering (ISFCM). In this paper we applied improved Fuzzy c-Means with spatial information for left ventricular wall segmentation. Obtained results showed that the proposed method can segment cardiac wall automatically with acceptable accuracy. The comparison of proposed method with nave FCM proved that ISFCM can segment with more accuracy than nave FCM.

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Communications Society, 2013. article id 6675656
National Category
Applied Mechanics
Research subject
Experimental Mechanics
Identifiers
URN: urn:nbn:se:ltu:diva-29823DOI: 10.1109/IFSC.2013.6675656Scopus ID: 84899109983Local ID: 36ef4139-bc36-4c68-917a-8f5419a0aedeISBN: 978-1-4799-1227-8 (print)OAI: oai:DiVA.org:ltu-29823DiVA, id: diva2:1003049
Conference
Iranian Conference on Fuzzy Systems : 27/08/2013 - 29/08/2013
Note
Godkänd; 2014; 20140509 (andbra)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2017-11-25Bibliographically approved

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Khodadad, Davood

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CiteExportLink to record
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