Scheduled System Maintenance on May 29th, 2015:
IEEE Xplore will be upgraded between 11:00 AM and 10:00 PM EDT. During this time there may be intermittent impact on performance. For technical support, please contact us at We apologize for any inconvenience.
By Topic

A new approach to brain tumour diagnosis using fuzzy logic based genetic programming

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Shen, S. ; Dept. of Electron. & Electr. Eng., Strathclyde Univ., Glasgow, UK ; Sandham, W.A. ; Granat, M.H. ; Dempsey, M.F.
more authors

Brain tumour diagnosis generally requires a histological analysis, involving invasive surgery which can cause pain and discomfort to patients. In this paper, a new brain tumour diagnostic procedure is described using magnetic-resonance imaging (MRI) only. First, the MR images are preprocessed, using standardizing, non-brain removal and enhancement. Second, an improved fuzzy clustering algorithm is applied to segment the brain into different tissues. Finally, brain tumour diagnosis is performed using fuzzy logic based genetic programming (GP) to search for classification rules. Classification results on a variety of MR images for different pathologies, indicate this technique to be promising.

Published in:

Engineering in Medicine and Biology Society, 2003. Proceedings of the 25th Annual International Conference of the IEEE  (Volume:1 )

Date of Conference:

17-21 Sept. 2003