An Enhanced Detection of White Matter Lesions in MRI Brain Images

M. Ishwarya Niranjana, M. Vignesh, R. Brindha, T. Saravanakumar

Abstract


White Matter Lesions are small areas of dead cells found in the parts of the brain. In general it is difficult for medical experts accurately quantify the WMLs due to decreased contrast between White Matter (WM) and Grey Matter (GM) in MRI brain images. The main aim is to detect the White Matter Lesions present in MRI brain images which may result in memory loss or even death. This can be done by Fuzzy C-means Clustering (FCM) algorithm which is less sensitive to noise present at output and it detects false lesions also. To overcome this and to make detection more accurate Particle Swarm Optimization algorithm is used. PSO yields high sensitivity, specificity and overall accuracy over FCM.


Full Text:

PDF

References


. Anitha .M, Prof.Tamije Selvy .P and Dr.Palanisamy .V (2012) ‘ Automated detection of White matter lesions in MRI brain images using Spatio fuzzy and Spatio-possibilistic clustering models’, Volume. 2, No.2.

. Beare .R, Srikanth .V, Chen .J, Phan .T.G, Stapleton .J, Lipshut .R, and Reutens .R (2009) ‘Development and validation of morphological segmentation of age-related cerebral White Matter hyper intensities’, NeuroImage, volume.47, pp.199–203.

. F. Maes, A. Collignon, D. Vandermeulen, G. Marchal, and P. Suetens (1997), “Multimodality Image Registration by Maximization of Mutual Information”, IEEE Trans. Med. Imag. vol. 16,pp. 187-198.

. Hari Krishnan .P and Dr. Ramamoorth .P (2012) ‘An Efficient Modified Fuzzy Possibilistic C-Means Algorithm for MRI Brain Image Segmentation’, Volume. 2, pp.1106-1110.

. Khayati .R, Vafadust .M, Towhidkhah .F and Nabavi .S.M (2008) ‘Fully automatic segmentation of multiple sclerosis lesions in brain MR FLAIR images using adaptive mixtures method and Markov random field model’, Computer Biology Medical., volume. 38, pp. 379–390.

. M. Kamber, R. Shinghal, D. L. Collins, G. S. Francis, and A. C. Evans (1995), “Model-Based 3-D Segmentation of Multiple Sclerosis Lesions in Magnetic Resonance Brain Images”, IEEE Trans. Med. Imag., vol. 14, pp. 442-453.

. Mizutani .E, Sun .C.T and Jang .J.S.R, ‘Neuro-Fuzzy and Soft Computing’, http://books.google.com/books/about/Neuro_fuzzy_and_soft_ computing.html.

. Mrs. Preethi .S.J and Prof. Rajeswari .K (2007) ‘Image Enhancement Techniques for Improving the Quality of Colour and Gray scale Medical Images’.

. S. A. Hojjatoleslami, F. Kruggel, and D. Y. von Cramon, “Segmentation of White Matter Lesions from Volumetric MR images”, Medical Image Computing and Computer-Assisted Intervention, Lecture Notes in Computer Science, vol. 1679, pp.52-61, Heidelberg Springer.

. V. A. Kovalev, F. Kruggel, H. J. Gertz, D. Y. V. Cramon (2011), “Three-Dimensional Texture Analysis of MRI Brain Datasets”, IEEE Trans. Med. Imag. vol. 20, pp. 424-433.


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.