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An improved spatial...
An improved spatial FCM algorithm for cardiac image segmentation
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- Yousefi-Banaem, Hossein (författare)
- Department of Biomedical Engineering, Faculty of Advance Medical Technology, Isfahan University of Medical Science, Isfahan Iran,Isfahan University of Med. Sci., Iran
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- Kermani, Saeed (författare)
- Department of Biomedical Engineering, Faculty of Advance Medical Technology, Isfahan University of Medical Science, Isfahan Iran,Isfahan University of Med. Sci., Iran
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- Sarrafzadeh, Omid (författare)
- Department of Biomedical Engineering, Faculty of Advance Medical Technology, Isfahan University of Medical Science, Isfahan Iran,Isfahan University of Med. Sci., Iran
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- Khodadad, Davood, 1985- (författare)
- Luleå tekniska universitet,Strömningslära och experimentell mekanik,Luleå University of Technology
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Department of Biomedical Engineering, Faculty of Advance Medical Technology, Isfahan University of Medical Science, Isfahan Iran Isfahan University of Med Sci., Iran (creator_code:org_t)
- Piscataway, NJ : IEEE, 2013
- 2013
- Engelska.
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Ingår i: 2013 13th Iranian Conference on Fuzzy Systems (IFSC). - Piscataway, NJ : IEEE. - 9781479912285 ; , s. 1-4
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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https://urn.kb.se/re...
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Abstract
Ämnesord
Stäng
- 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.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Medicinteknik -- Medicinsk bildbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Medical Engineering -- Medical Image Processing (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Maskinteknik -- Teknisk mekanik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Mechanical Engineering -- Applied Mechanics (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Kardiologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Cardiac and Cardiovascular Systems (hsv//eng)
Nyckelord
- 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
- Experimentell mekanik
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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