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A Dynamic Particle Swarm Optimisation and Fuzzy Clustering Means Algorithm for
        
        Fuzzy  Clustering  Means  (FCM) algorithm  is a  widely  used clustering  method  in  image  segmentation,  but  it often 
falls into local minimum  and is quite sensitive  to initial values which are random  in most cases.  In this work, we consider the 
extension  to  FCM  to  multimodal  data improved by a  Dynamic  Particle  Swarm Optimization (DPSO) algorithm  which  by 
construction  incorporates  local  and  global  optimization  capabilities. Image  segmentation  of  three-variate  MRI  brain  data  is 
achieved using FCM-3 and DPSOFCM-3 where the three modalities T1-weighted, T2-weighted and Proton Density (PD), are 
treated  at  once  (the  suffix-3  is  added  to  distinguish  our  three-variate  method  from  mono-variate  methods  usually  using  T1-
weighted  modality). FCM-3  and  DPSOFCM-3  were  evaluated  on  several Magnetic  Resonance (MR) brain  images  corrupted 
by  different  levels  of  noise  and  intensity  non-uniformity.  By  means  of  various  performance  criteria,  our  results  show  that  the 
proposed  method  substantially  improves  segmentation  results.  For  noisiest  and  most  no-uniform  images,  the  performance 
improved as much as 9% with respect to other methods.    
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[29] Zanaty E., “Determination of Gray Matter (GM) and White Matter (WM) Volume in Brain Magnetic Resonance Images (MRI),” International Journal of Computer Applications, vol. 45, no. 3, pp.16-22, 2012. Kies Karima is currently an assistant professor and a permanent member of SIMPA laboratory in informatics department at University of Science and Technology of Oran-Mohamed Boudiaf (USTO-MB). She received her engineering degree in Computer Science, M.Sc. and Ph.D from USTO-MB (1999- 2009). She is the head of Computer Science department and has published more than ten papers in journals and conference proceedings. Her main research interests include medical image processing, 3D image segmentation and pattern recognition. Benamrane Nacera is currently a full professor and a director of SIMPA laboratory in informatics department at University of Science and Technology of Oran-Mohamed Boudiaf (USTO-MB). She received her engineering degree in Computer Science from University of Oran, the M.Sc. and Ph.D. degrees from University of Valenciennes, France, in 1988 and 1994. Since 2002, she is the head of vision and medical imaging team at SIMPA laboratory. She has published more than 90 papers in journals and conference proceedings. Her main research interests include image processing, medical imaging, computer vision, biomedical engineering and pattern recognition.
