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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, Isfahan Iran.
Department of Biomedical Engineering, Faculty of Advance Medical Technology, Isfahan University of Medical Science, Isfahan Iran.
Department of Biomedical Engineering, Faculty of Advance Medical Technology, Isfahan University of Medical Science, Isfahan Iran.
Experimental Mechanics, Luleå University of Technology, Luleå, Sweden.ORCID iD: 0000-0003-2960-3094
2013 (English)In: 2013 13th Iranian Conference on Fuzzy Systems (IFSC), IEEE, 2013, p. 1-4Conference 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
IEEE, 2013. p. 1-4
Keywords [en]
cardiology, fuzzy set theory, image segmentation, medical image processing, spatial FCM algorithm, cardiac image segmentation, cardiac wall segmentation, heart functionality, cardiac image analysis, fuzzy c- means algorithm, segmentation field, naive FCM algorithm, spatial domain neighborhood information, membership function, ISFCM, ventricular wall segmentation, Biomedical imaging, Clustering algorithms, Motion segmentation, Noise, Accuracy, Magnetic resonance imaging, improved FCM, spatial information, cardiac wall
National Category
Medical Image Processing
Identifiers
URN: urn:nbn:se:oru:diva-72561DOI: 10.1109/IFSC.2013.6675656ISI: 000335007500073Scopus ID: 2-s2.0-84899109983OAI: oai:DiVA.org:oru-72561DiVA, id: diva2:1289908
Conference
13th Iranian Conference on Fuzzy Systems (IFSC), Qazvin, Iran, August 27-29, 2013
Available from: 2019-02-19 Created: 2019-02-19 Last updated: 2019-02-28Bibliographically approved

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Khodadad, Davood

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CiteExportLink to record
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  • apa
  • harvard1
  • ieee
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Output format
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