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Strong fuzzy c-means in medical image data analysis
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Kannan, S. R., Ramathilagam, S., Devi, R. and Hines, Evor (2012) Strong fuzzy c-means in medical image data analysis. Journal of Systems and Software, Vol.85 (No.11). pp. 2425-2438. doi:10.1016/j.jss.2011.12.020 ISSN 0164-1212.
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Official URL: http://dx.doi.org/10.1016/j.jss.2011.12.020
Abstract
This paper presents a robust fuzzy c-means (FCM) for an automatic effective segmentation of breast and brain magnetic resonance images (MRI). This paper obtains novel objective functions for proposed robust fuzzy c-means by replacing original Euclidean distance with properties of kernel function on feature space and using Tsallis entropy. By minimizing the proposed effective objective functions, this paper gets membership partition matrices and equations for successive prototypes. In order to reduce the computational complexity and running time, center initialization algorithm is introduced for initializing the initial cluster center. The initial experimental works have done on synthetic image and benchmark dataset to investigate the effectiveness of proposed, and then the proposed method has been implemented to differentiate the different region of real breast and brain magnetic resonance images. In order to identify the validity of proposed fuzzy c-means methods, segmentation accuracy is computed by using silhouette method. The experimental results show that the proposed method is more capable in segmentation of medical images than existed methods. (c) 2011 Elsevier Inc. All rights reserved.
Item Type: | Journal Article | ||||
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||
Journal or Publication Title: | Journal of Systems and Software | ||||
Publisher: | Elsevier Inc. | ||||
ISSN: | 0164-1212 | ||||
Official Date: | November 2012 | ||||
Dates: |
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Volume: | Vol.85 | ||||
Number: | No.11 | ||||
Page Range: | pp. 2425-2438 | ||||
DOI: | 10.1016/j.jss.2011.12.020 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access |
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