Volume 13 Number 5 (May 2018)
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JCP 2018 Vol.13(5): 537-544 ISSN: 1796-203X
doi: 10.17706/jcp.13.5.537-544

Brain Image Segmentation Using Multistable Cellular Neural Networks

Burak Yılmaz, Akif Durdu, Güzin Özmen
Selcuk Unversity Faculty of Enginnering Electrics-Electronics Engineering Department Konya, Turkey.
Abstract—This study proposes a new method on “brain image segmentation”. Algorithm is based on the Multistable Cellular Neural Networks (Multistable-CNN). Evaluations are performed on well-known BRAINWEB database. The metrics for performance evaluations of the algorithm were JACCARD, DICE, TPF and TNF. The results are compared with the SPM8, FSL FAST and Brain Suite software packages. The Multistable CNN algorithm used in this study differs from conventional CNN algorithm. The Multistable CNN's can perform multiple segmentations in a single run. Algorithm is simple and doesn't require complex calculations. Evaluations show that proposed algorithm’s performance is adequate. Algorithm also does not require any atlas or image registration

Index Terms—MRI, brain, segmentation, cellular neural networks, multistable cellular neural networks, cerebrospinal fluid (CSF), gray matter (GM) and white matter (WM).

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Cite: Burak Yılmaz, Akif Durdu, Güzin Özmen, "Brain Image Segmentation Using Multistable Cellular Neural Networks," Journal of Computers vol. 13, no. 5, pp. 537-544, 2018.

General Information

ISSN: 1796-203X
Frequency: Monthly (2006-2014); Bimonthly (Since 2015)
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO, DOAJ, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, CNKI,etc
E-mail: jcp@iap.org
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