COMPUTER AIDED SEGMENTATION OF BRAIN TISSUES USING SOFT COMPUTING TECHNIQUES
- 1 Department of ECE, Theni Kammavar Sangam College of Technology, Theni, India
- 2 Department of EEE, Noorul Islam Centre for Higher Education, Nagercoil, India
- 3 Department of ECE, PSNA College of Engineering and Technology, Dindigul, India
In this study, an efficient computer aided classification of brain tissue in to Gray Matter (GM), White Matter (WM) and Cerebro-Spinal Fluid (CSF) is proposed. The proposed work consists of the following sub blocks like denosing, feature extraction and Classifier. This initial partition is performed by ANFIS after extracting the textural features like local binary pattern and histogram features. The main motivation behind this research work is to classify the brain tissue. By comparing the proposed method with other conventional methods, it is clear that our algorithm can estimate the correct tissues WM, GM and CSF much more accurately than the existing algorithms with respect to ground truth image patterns. We achieved an accuracy rate of 98.9% for Gray matter segmentation, 94.1% for White matter segmentation and 90.8% for CSF segmentation.
Copyright: © 2014 D. Ramkumar, I. Jacob Raglend and K. Batri. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- 1,728 Views
- 1,862 Downloads
- 1 Citations
- Brain MRI
- Medical Diagnostic Imaging
- Medical Image Compression