Research Article Open Access

An Improved Implementation of Brain Tumor Detection Using Segmentation Based on Neuro Fuzzy Technique

S. Murugavalli1 and V. Rajamani1
  • 1 ,
Journal of Computer Science
Volume 3 No. 11, 2007, 841-846

DOI: https://doi.org/10.3844/jcssp.2007.841.846

Submitted On: 25 April 2007 Published On: 30 November 2007

How to Cite: Murugavalli, S. & Rajamani, V. (2007). An Improved Implementation of Brain Tumor Detection Using Segmentation Based on Neuro Fuzzy Technique . Journal of Computer Science, 3(11), 841-846. https://doi.org/10.3844/jcssp.2007.841.846

Abstract

Implementation of a neuro-fuzzy segmentation process of the MRI data is presented in this study to detect various tissues like white matter, gray matter, csf and tumor. The advantage of hierarchical self organizing map and fuzzy c means algorithms are used to classify the image layer by layer. The lowest level weight vector is achieved by the abstraction level. We have also achieved a higher value of tumor pixels by this neuro-fuzzy approach. The computation speed of the proposed method is also studied. The multilayer segmentation results of the neuro fuzzy are shown to have interesting consequences from the viewpoint of clinical diagnosis. Neuro fuzzy technique shows that MRI brain tumor segmentation using HSOM-FCM also perform more accurate one.

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Keywords

  • Image analysis
  • segmentation
  • HSOM
  • FCM
  • neuro fuzzy technique
  • tumor detection