A Proficient Clustering Technique to Detect CSF Level in MRI Brain Images Using PSO Algorithm

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Abstract: Image segmentation is an indispensible part of the visualization of human tissues during the analysis of Magnetic Resonance Imaging (MRI). MRI is an advanced medical imaging technique which provides rich information for detecting Cerebrospinal Fluid (CSF) level in brain images. The changes in the CSF protein level forms abnormal brain deposits strongly linked to variety of neurological diseases. The proposed system encompasses the following steps, Pre-Processing (Contrast Limited Adaptive Histogram Equalization), the enhanced image is then subjected to CSF extraction, Clustering methods (Fuzzy C Means, Total Variation FCM, and Anisotropic Diffused TVFCM), and Particle Swarm Optimization (PSO) with clustering techniques (FCM-PSO, TVFCM-PSO, and ADTVFCM-PSO). The clustering methods provide only local optimal solution. In order to achieve global optimal solution, the clustering methods are further optimized using PSO. The performance of the clustering with optimization method is analyzed using defined set of Simulated MS Lesion Brain database. The optimized clustering methods finds the level of CSF present in MRI brain images with 98% of Accuracy, 92% of Sensitivity and 97% of Specificity.

WSEAS Transactions on Computers, ISSN / E-ISSN: 1109-2750 / 2224-2872, Volume 12, 2013

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P. Tamije Selvy, V.Palanisamy, M. Sri Radhai, "A Proficient Clustering Technique to Detect CSF Level in MRI Brain Images Using PSO Algorithm," WSEAS Transactions on Computers, vol. 12, pp. -, 2013, DOI:
P. Tamije Selvy, V.Palanisamy, M. Sri Radhai. A Proficient Clustering Technique to Detect CSF Level in MRI Brain Images Using PSO Algorithm. WSEAS Transactions on Computers. 2013;12:-.
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