WML detection of brain images using fuzzy and possibilistic approach in feature space

WSEAS Transactions on Computers

Volumn 11, Issue 6, 2012, Pages 180-189

  Anitha, M ^a   Selvy, P Tamije ^a   Palanisamy, V ^a  

^a ANNA UNIVERSITY   (India)

Author keywords

Fuzzy clustering; Geostatistics; Image segmentation; Magnetic resonance imaging; Possibilistic clustering; White matter changes

Indexed keywords

AUTOMATED DETECTION; BRAIN IMAGES; COMPUTATIONAL NEUROSCIENCE; DATA SETS; DEAD CELLS; DISTANCE MEASURE; FEATURE SPACE; FUZZY C MEANS CLUSTERING; GEO-STATISTICS; GEOSTATISTICAL; HIDDEN STRUCTURES; IMAGE SEGMENTATION MODEL; LARGE REGIONS; POSSIBILISTIC APPROACH; POSSIBILISTIC CLUSTERING; POSSIBILISTIC CLUSTERING ALGORITHMS; REGION OF INTEREST; SMALL AREA; UNLABELED DATA; UNSUPERVISED CLUSTERING; UNSUPERVISED CLUSTERING ALGORITHM; WHITE MATTER; WHITE MATTER LESIONS;

BRAIN MODELS; CLUSTERING ALGORITHMS; FUZZY CLUSTERING; FUZZY SYSTEMS; MAGNETIC RESONANCE IMAGING; UNSUPERVISED LEARNING;

IMAGE SEGMENTATION;

EID: 84867029131     PISSN: 11092750     EISSN: 22242872     Source Type: Journal    
DOI: None     Document Type: Article

References (13)

1. L. O. Wahlund, F. Barkhof, F. Fazekas, L. Bronge, M. Augustin,M. Sjögren, A. Wallin, H. Ader, D. Leys, L. Pantoni, F. Pasquier, T. Erkinjuntti, and P. Scheltens, "A new rating scale for age-related white matter changes applicable to MRI and CT," Stroke, vol. 32, pp. 1318-1322, 2001.
2. E. Matsusue, S. Sugihara, S. Fujii, E. Ohama, T. Kinoshita, and T. Ogawa, "White matter changes in elderly people: MR-pathologic correlations," Magn. Reson. Med. Sci., vol. 5, pp. 99-104, 2006.
3. F. Fazekas, "Pathological correlates of incidental MRI white matter signal hyper intensities," Neurology, vol. 43, pp. 1683- 1689, 1993.
4. J. Udupa, L. Wei, S. Samarasekera, Y. Miki, M. A. van Buchem, and R. I. Grossman, "Multiple sclerosis lesion quantification using fuzzy connectedness principles," IEEE Trans. Med. Imaging, vol. 16, no. 5, pp. 598-609, Oct. 1997.
5. B. Alfano, A. Brunetti, M. Larobina, M. Quarantelli, E. Tedeschi, A. Ciarmiello, E. M. Covelli, and M. Salvatore, "Automated segmentation and measurement of global white matter lesion volume in patients with multiple sclerosis," J. Magn. Reson. Imaging, vol. 12, pp. 799-807, 2000.
6. Y. Wu, S. K. Warfield, I. L. Tan, W. M. Wells III, D. S. Meier, R. A. van Schijndel, F. Barkhof, and C. R. G. Guttmann, "Automated segmentation of multiple sclerosis lesion subtypes with multichannel MRI," NeuroImage, vol. 32, pp. 1205-1215, 2006.
7. P. Anbeek, K. L. Vincken, M. J. P. van Osch, R. H. C. Bisschops, and J. van der Grond, "Automatic segmentation of different-sized white matter lesions by voxel probability estimation," Med. Image Anal., vol. 8, pp. 205- 215, 2004.
8. R. Khayati, M. Vafadust, F. Towhidkhah, and S. M. Nabavi, "Fully automatic segmentation of multiple sclerosis lesions in brain MR FLAIR images using adaptive mixtures method and Markov random field model," Comput. Biol. Med., vol. 38, pp. 379-390, 2008.
9. Z. Lao, D. Shen, D. Liu, A. F. Jawad, E. R. Melhem, L. J. Launer, R. N. Bryan, and C. Davatzikos, "Computer assisted segmentation of white matter lesions in 3D MR images using support vector machine," Acad. Radiol., vol. 15, pp. 300-313, 2008.
10. M. L. Seghier, A. Ramlackhansingh, J. Crinion, A. P Leff, and C. J. Price, "Lesion identification using unified segmentationnormalisation models and fuzzy clustering," NeuroImage, vol. 41, pp. 1253-1266, 2008.
11. R. Beare, V. Srikanth, J. Chen, T. G. Phan, J. Stapleton, R. Lipshut, and D. Reutens, "Development and validation of morphological segmentation of age-related cerebral white matter hyper intensities," NeuroImage, vol. 47, pp.199-203, 2009.
12. R. de Boer, H. A. Vrooman, F. van der Lijn, M.W. Vernooij, M. A. Ikram, A. van der Lugt, M. M. B. Breteler, and W. J. Niessen, "White matter lesion extension to automatic brain tissue segmentation on MRI," NeuroImage, vol. 45, pp. 1151-1161, 2009.
13. M. delC .V. Hernendez, K. J. Ferguson, F. M. Chappell, and J. M. Wardlaw, "New multispectral MRI data fusion technique for white matter lesion segmentation: method and comparison with thresholding in FLAIR images,"Eur. Radiol., Feb. 16, 2010.