Improving MR brain image segmentation using self-organising maps and entropy-gradient clustering

Information Sciences

Volumn 262, Issue , 2014, Pages 117-136

  Ortiz, A ^a   Gorriz, J M ^b   Ramirez, J ^b   Salas Gonzalez, D ^b  

^a UNIVERSITY OF MÁLAGA   (Spain)

^b UNIVERSITY OF GRANADA   (Spain)

Author keywords

Feature extraction; Genetic algorithms; Image segmentation; MRI; Neural networks; Self organising maps

Indexed keywords

ALZHEIMER'S DISEASE; ANATOMICAL STRUCTURES; CLUSTERING MECHANISM; GENETIC ALGORITHM (GAS); MAGNETIC RESONANCE IMAGES (MRI); MR BRAIN IMAGE SEGMENTATION; SPATIAL RELATIONSHIPS; VOXEL CLASSIFICATIONS;

BRAIN MAPPING; CEREBROSPINAL FLUID; ENTROPY; FEATURE EXTRACTION; GENETIC ALGORITHMS; MAGNETIC RESONANCE IMAGING; NEURAL NETWORKS; NEURODEGENERATIVE DISEASES; NUCLEAR MEDICINE; SELF ORGANIZING MAPS;

IMAGE SEGMENTATION;

EID: 84892496947     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2013.10.002     Document Type: Article

References (68)

1. M.H. Ahmed, S.M. Yamany, N. Mohamed, A. Farag, and T. Moriarty A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data IEEE Transactions on Medical Imaging 21 3 2002 193 199
2. E. Alhoniemi, J. Himberg, J. Parhankagas, J. Vesanta, SOM Toolbox for Matlab v2.0 < http://www.cis.hut.fi/projects/somtoolbox >, 2005 (accessed 09.09.13).
3. J. Alirezaie, M. Jernigan, and C. Nahmias Automatic segmentation of cerebral MR images using artificial neural networks IEEE Transactions on Nuclear Science 45 4 1998 2174 2182
4. I. Álvarez, J.M. Górriz, J. Ramírez, D. Salas-Gonzalez, M.M. López, F. Segovia, R. Chaves, M. Gómez-Río, and C. García Puntonet 18F-FDG PET imaging analysis for computer aided Alzheimer's diagnosis Information Sciences 181 4 2011 903 916
5. I. Álvarez, J.M. Gorriz, M.M. López, J. Pérez, D. Salas-Gonzalez, F. Segovia, R.M. Chaves, and C. Puntonet Computer aided diagnosis of Alzheimer's disease using component-based SVM Applied Soft Computing 11 2011 2376 2382
6. Alzheimer's Disease Neuroimaging Initiative < http://adni.loni.ucla. edu/ > (accessed 20.09.13).
7. E. Arsuaga, and F. Díaz Topology preservation in SOM International Journal of Mathematical and Computer Sciences 1 1 2005 19 22
8. M. Berthod, Z. Kato, S. Yu, and J. Zerubia Bayesian image classification using Markov random fields Image and Vision Computing 14 1996 195 285
9. J.C. Bezdek, L.O. Ifall, and L.P. Clarke Review of MR image segmentation techniques using pattern recognition Medical Physics 20 4 1993 1033 1048
10. Brain Extraction Tool, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK < http//www.fmrib.ox.ac.uk/analysis/ research/bet/ >.
11. L.P. Clarke, R.P. Veltuizen, M.A. Camacho, J.J. Heine, M. Vaidyanathan, L.O. Hall, R.W. Thatcher, and M.L. Silbiger MRI segmentation methods and applications Magnetic Resonance Imaging 13 3 1995 343 368
12. D.L. Davies, and D.W. Bouldin A cluster separation measure IEEE Transactions on Pattern Analysis and Machine Intelligence 1 4 1979 224 227
13. X. Du, Y. Li, D. Yao, A support vector machine based algorithm for magnetic resonance image segmentation, in: Paper presented at the Fourth International Conference on Natural Computation, Jinan, Shandong (China), 2008.
14. J. Dunn Well separated clusters and optimal fuzzy partitions Journal of Cybernetics 4 1974 95 104
15. L. Fan, D. Tian, A brain MR image segmentation method based on SOM neural network, in: Paper presented at the IEEE International Conference on Bioinformatics and Biomedical Engineering, Wuhan, 2007.
16. FAST segmentation software, Nuffield Department of Clinical Neurosciences, Functional Magnetic Resonance Image of the Brain (FMRIB) Centre, University of Oxford, Oxford, UK, 2012 < http//www.fmrib.ox.ac.uk/analysis/ research/fast/ >.
17. J.M. Gorriz, F. Segovia, J. Ramírez, A. Lassl, and D. Salas-Gonzalez GMM based SPECT image classification for the diagnosis of Alzheimer's disease Applied Soft Computing 11 2011 2313 2325
18. M. Graña, D. Chyzhyk, M. García-Sebastián, and C. Hernández Lattice independent component analysis for functional magnetic resonance imaging Information Sciences 181 10 2011 1910 1928
19. H. Greenspan, A. Ruf, and J. Goldberger Constrained Gaussian mixture model framework for automatic segmentation of MR brain images IEEE Transactions on Medical Imaging 25 9 2006 1233 1245
20. I. Güler, A. Demirhan, and R. Karakis Interpretation of MR images using self-organizing maps and knowledge-based expert systems Digital Signal Processing 19 2009 668 677
21. R.M. Haralick, K. Shanmugam, and I. Dinstein Textural features for image classification IEEE Transactions on Systems and Cyberneicst 6 1973 610 621
22. M.E. Hodgson What size window for image classification? A cognitive perspective American Society for Photogrammetry and Remote Sensing 64 8 1998 797 807
23. M. Hu Visual pattern recognition by moments invariants IRE Transactions on Information Theory 8 1962 179 187
24. Internet Brain Database Repository, Massachusetts General Hospital, Center for Morphometric Analysis, 2010 < http//www.cma.mgh.harvard.edu/ibsr/ data.html > (accessed 10.09.13).
25. J.R. Jiménez-Alaniz, V. Medina-Bañuelos, and O. Yáñez-Suárez Data-driven brain MRI segmentation supported on edge confidence and a priori tissue information IEEE Transactions on Medical Imaging 25 1 2006 74 83
26. M. Kamber, R. Shinghal, D. Collins, G. Francis, and A. Evans Model-based 3D segmentation of multiple sclerosis lesions in magnetic resonance brain images IEEE Transactions on Medical Imaging 14 3 1995 442 453
27. T. Kapur, W. Grimson, I. Wells, and R. Kikinis Segmentation of brain tissue from magnetic resonance images Medical Image Analysis 1 2 1996 109 127
28. D. Kennedy, P. Filipek, and V. Caviness Anatomic segmentation and volumetric calculations in nuclear magnetic resonance imaging IEEE Transactions on Medical Imaging 8 1 1989 1 7
29. A. Khan, and A.M. Mirza Genetic perceptual shaping utilizing cover image and conceivable attack information using genetic programming Information Fusion 8 4 2007 354 365
30. A. Khan, S.F. Tahir, A. Majid, and T.S. Choi Machine learning based adaptive watermark decoding in view of an anticipated attack Pattern Recognition 41 2008 2594 2610
31. T. Kohonen Self-Organizing Maps 2001 Springer
32. S.V.B. Kumar, R. Mullick, U. Patil, Textural content in 3T MR an image-based marker for Alzheimer's disease, in: Proceedings of the SPIE 5747, Medical Imaging 2005: Image Processing, 1366, May 2005, 2005.
33. K.V. Leemput, F. Maes, D. Vandermeulen, and P. Seutens Automated model-based tissue classification of MR images of the brain IEEE Transactions on Medical Imaging 18 1999 897 908
34. K. Lim, and A. Pfefferbaum Segmentation of MR brain images into cerebrospinal fluid spaces, white and gray matter Journal of Computer Assisted Tomography 13 4 1989 588 593
35. T. Logeswari, M. Karnan, Hybrid self-organizing map for improved implementation of brain MRI segmentation, in: International Conference on Signal Acquisition and Processing, Bangalore, 2010.
36. J.L. Marroquin, B.C. Vemuri, S. Botello, F. Calderon, and A. Fernandez-Bouzas An accurate and efficient Bayesian method for automatic segmentation of brain MRI IEEE Transactions on Medical Imaging 21 8 2002 934 945
37. S. Mitra, and P.P. Kundu Satellite image segmentation with shadowed C-means Information Sciences 181 17 2011 3601 3613
38. N. Mohamed, M. Ahmed, A. Farag, Modified fuzzy c-mean in medical image segmentation, in: IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 6, Phoenix, AZ, 1999, pp. 3429-3432.
39. M. Nixson, and A. Aguado Feature Extraction and Image Processing 2008 Academic Press
40. A. Ortiz, J.M. Górriz, J. Ramírez, and D. Salas-Gonzalez MR brain image segmentation by hierarchical growing SOM and probability clustering Electronics Letters 47 10 2011 585 586
41. N. Otsu A threshold selection method from gray-level histograms IEEE Transactions on Systems, Man, and Cybernetics 9 1 1979 62 66
42. C. Parra, K. Iftekharuddin, R. Kozma, Automated brain tumor segmentation and pattern recognition using AAN, in: Computational Intelligence, Robotics and Autonomous Systems, Singapore, 2005.
43. D.L. Pham, and J. Prince Adaptive fuzzy segmentation of magnetic resonance images IEEE Transactions on Medical Imaging 18 9 1999 737 752
44. M. Przytulska, J.L. Kulikowski, A. Bajera, and L. Krolicki Comparison of SPECT cerebral images examination methods based on luminance level and morphological spectra evaluation Biocybernetics and Biomedical Engineering 29 1 2009 29 42
45. J.C. Rajapakse, J.N. Giedd, and J.L. Rapoport Statistical approach to segmentation of single-channel cerebral MR images IEEE Transactions on Medical Imaging 16 2 1997 176 186
46. J.C. Rajapakse, and F. Kruggel Segmentation of MR images with intensity inhomogeneities Image and Vision Computing 16 1998 165 180
47. J. Ramírez, J.M. Gorriz, D. Salas-Gonzalez, A. Romero, M.M. López, I. Alvarez, M. Gomez, Computer aided diagnosis of Alzheimer's type dementia combining support vector machines and discriminative set of features, Information Sciences 2013 237(10) (2011) 59-72.
48. D. Rivest-Hénault, and M. Cheriet Unsupervised MRI segmentation of brain tissues using a local linear model and level set Magnetic Resonance Imaging 29 2 2011 243 259
49. P. Sahoo, S. Soltani, A. Wong, and Y. Chen A survey of thresholding techniques Computer Vision, Graphics Image Process 41 2004 233 260
50. D.W. Shattuck, S.R. Sandor-Leathy, K.A. Schaper, D.A. Rottenberg, and R.M. Leathy Magnetic resonance image tissue classification using a partial volume model Neuroimage 13 2001 2001 856 876
51. S.N. Sivanandam, and S.N. Deepa Introduction to Genetic Algorithms 2008 Springer-Verlag
52. S. Smith, M. Brady, and Y. Zhang Segmentation of brain images through a hidden Markov Random Field Model and the Expectation-Maximization Algorithm IEEE Transactions on Medical Imaging 20 1 2001 45 57
53. M.O. Stitson, J.A.E. Weston, A. Gammerman, V. Vork, V. Vapnik, Theory of Support Vector Machines, Technical Report CSD-TR-96-17, Department of Computer Science, Royal Holloway College, University of London, 1996.
54. S. Spitalnic Test properties 2 likelihood ratios, Bayes' formula, and receiver operating characteristic curves Hospital Physician. Primer in Literature Interpretation Series 2004 Turner-White 53 58
55. C.T. Su, and H.C. Lin Applying electromagnetism-like mechanism for feature selection Information Sciences 181 5 2011 972 986
56. W. Sun Segmentation method of MRI using fuzzy Gaussian basis neural network Neural Information Processing 8 2 2005 19 24
57. K. Tan, E. Khor, and T. Lee Evolutionary and Applications 2005 Springer
58. K. Tasdemir, and E. Merényi Exploiting data topology in visualization and clustering of self-organizing maps IEEE Transactions on Neural Networks 20 4 2009 549 562
59. T. Tasdizen, S. Awate, R. Whitaker, N. Foster, MRI tissue classification with neighborhood statistics a nonparametric, entropy-minimizing approach, in: Paper in process at International Conference on Medical Image Computing and Computer Assisted Intervention, Palm Springs, CA, USA, 2005.
60. The Mathworks, Matlab Genetic Algorithm and Direct Search Toolbox User's Guide, The Mathworks, Massachusetts, 2005.
61. S. Theodoridis, and K. Koutroumbas Pattern Recognition forth ed. 2009 Academic Press (Elsevier)
62. Y. Tsai, I. Chiang, Y. Lee, C. Liao, and K. Wang Automatic MRI meningioma segmentation using estimation maximization Proceedings of the 27th IEEE Engineering in Medicine and Biology Annual Conference 3 2005 3074 3077 Shanghai, China
63. I. Usman, and A. Khan BCH coding and intelligent watermark embedding employing both frequency and strength selection Applied Soft Computing 10 1 2010 332 343
64. Y. Wang, and T. Adali Quantification and segmentation of brain tissues from MR images a probabilistic neural network approach IEEE Transactions on Image Processing 7 8 1998 1165 1180
65. W. Wells, W. Grimson, R. Kikinis, and F. Jolesz Adaptive segmentation of MRI data IEEE Transactions on Medical Imaging 15 4 1996 429 442
66. J. Xie, and H. Tsui Image segmentation based on maximum-likelihood estimation and optimum entropy distribution (MLE-OED) Pattern Recognition Letters 25 2005 1133 1141
67. Z. Yang, J. Laaksonen, Interactive retrieval in facial image database using self-organizing maps, in: Proceedings of the 9th IAPR Conference on MachineVision Applications (MVA 2005), Tsukuba Science City, Japan, 2005, pp. 112-115.
68. J. Zhang, J. Zhuang, H. Du, and S. Wang Self-organizing genetic algorithm based tuning of PID controllers Information Sciences 179 7 2009 1007 1018