Development of a Neuro-fuzzy MR Image Segmentation Approach Using Fuzzy C-Means and Recurrent Neural Network

  • Authors:
  • Dipankar Ray;D. Dutta Majumder

  • Affiliations:
  • Department of CSE, Indian School of Mines, Dhanbad, India 826 004;Institute of Cybernetics and Information Technology, Kolkata, India 700 108 and Indian Statistical Institute, Kolkata, India 700 105

  • Venue:
  • PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
  • Year:
  • 2009

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Abstract

A neuro-fuzzy clustering framework has been presented for a meaningful segmentation of Magnetic Resonance medical images. MR imaging provides detail soft tissue descriptions of the target body object and it has immense importance in today's non-invasive therapeutic planning and diagnosis methods. The unlabeled image data has been classified using fuzzy c-means approach and then the data has been used for training of an Elman neural network. The trained neural net is then used as a ready-made tool for MRI segmentation.