MRI brain lesion image detection based on color-converted K-means clustering segmentation

Measurement: Journal of the International Measurement Confederation

Volumn 43, Issue 7, 2010, Pages 941-949

  Juang, Li Hong ^a   Wu, Ming Ni ^b  

^a UNIVERSITI TEKNOLOGI MALAYSIA   (Malaysia)

^b NATIONAL TAICHUNG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

Author keywords

Color converted segmentation algorithm; K means clustering technique; Lesion; Tumor

Indexed keywords

BRAIN IMAGES; BRAIN LESIONS; COLOR SPACE; COLOR-BASED SEGMENTATION; GRAY LEVEL IMAGE; IMAGE-BASED; K-MEANS; K-MEANS CLUSTERING; K-MEANS CLUSTERING TECHNIQUES; LESION; LESION SIZE; MRI IMAGE; OBJECTS TRACKING; PRELIMINARY DESIGN; SEGMENTATION ALGORITHMS;

CLUSTER ANALYSIS; CLUSTERING ALGORITHMS; COLOR; IMAGE ENHANCEMENT; IMAGE SEGMENTATION; RESONANCE; TRACKING (POSITION); TUMORS; WATER SUPPLY SYSTEMS;

MAGNETIC RESONANCE IMAGING;

EID: 77955228044     PISSN: 02632241     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.measurement.2010.03.013     Document Type: Article

References (44)

1. A. Rangarajan, I.T. Hsiao, and G. Gindi A Bayesian joint mixture framework for the integration of anatomical in functional image reconstruction J. Math. Imaging Vis. 12 2000 199 217
2. F.M. Enzinger, and S.W. Weiss Malignant vascular tumors F.M. Enzinger, S.W. Weiss, Soft Tissue Tumors third ed. 1995 Mosby St. Louis, MO 655 677
3. L.V.D. Hauwe, F. Ramon, Lymphatic tumors, in: A.M. De Schepper (Ed.), Imaging of Soft Tumors, second ed., Springer, Heidelberg, 2001, pp. 246-254.
4. K.Y. Tu, T.B. Chen, H.H.S. Lu, R.S. Liu, K.L. Chen, C.M. Chen, and J.C. Chen Empirical studies of cross-reference maximum likelihood estimate reconstruction for positron emission tomography Biomed. Eng. - Appl. Basis Commun. 13 1 2001 1 7
5. C.M. Kao, X. Pan, C.T. Chen, and W.H. Wong Image restoration and reconstruction with a Bayesian approach Med. Phys. 25 5 1998 600 613
6. G.N. Hounsfield Computerized transverse axial scanning tomography: Part 1, description of the system Br. J. Radiol. 46 1973 1016 1022
7. B. Lipinski, H. Herzog, E.R. Kops, W. Oberschelp, and H.W. Muller-Gartner Expectation maximization reconstruction of positron emission tomography images using anatomical magnetic resonance information IEEE Trans. Med. Imaging 16 2 1997 129 136
8. A. Bazille, M.A. Guttman, E.R. Mcveigh, and E.A. Zerhouni Impact of semiautomated versus manual image segmentation errors on myocardial strain calculation by magnetic resonance tagging Invest. Radiol. 29 4 1994 427 433
9. H. Anger Use of gamma-ray pinhole camera for vivo studies Nature 170 1952 200 204
10. X. Ouyang, W.H. Wang, V.E. Johnson, X. Hu, and C.T. Chen Incorporation of correlated structural images in PET image reconstruction IEEE Trans. Med. Imaging 13 2 1994 627 640
11. Y.S. Akgul, C. Kambhamettu, M. Stone, Extraction and tracking of the tongue surface from ultrasound image sequences, in: Proceedings of the IEEE Computer Vision Pattern Recognition, Santa Barbara, CA, 1998, pp. 298-303.
12. U.R. Abeyratne, A.P. Petropulu, and J.M. Reid On modeling the tissue response from ultrasonic B-scan images IEEE Trans. Med. Imaging 1 2 1996 479 490
13. T.L. Faber, and E.M. Stokely Orientation of 3D structures in medical images IEEE Trans. Pattern Anal. Mach. Intell. 2 2 1980 127 135
14. G.J. Grewera, and J.K. Udupa Shape based interpolation of multidimensional grey-level images IEEE Trans. Med. Imaging 15 6 1996 881 892
15. F.S. Cohen, G. Georgiou, and E. Halpern WOLD decomposition of the backscatter echo in ultrasound images of soft tissue organs IEEE Trans. Ultrason., Ferroelect. Freq. Contr. 1 2 1997 460 472
16. K.D. Donohue, F. Forsberg, C.W. Piccoli, and B.B. Goldberg Classification of breast masses with ultrasonic scattering structure templates IEEE Trans. Ultrason., Ferroelect. Freq. Contr. 1 2 1999 300 310
17. G. Georgiou, and F.S. Cohen Statistical characterization of diffuse scattering in ultrasound images IEEE Trans. Ultrason., Ferroelect. Freq. Contr. 1 2 1998 57 64
18. T. Taxt, and A. Lundervold Multispectral analysis of the brain using magnetic resonance imaging IEEE Trans. Med. Imaging 13 1994 440 470
19. L. Liberman, E.A. Morris, C.L. Benton, A.F. Abramson, and D.D. Dershaw Probably benign lesions at breast magnetic resonance imaging: preliminary experience in high-risk women Cancer 98 2 2003 377 388
20. M.N. Ahmed, S.M.N. Mohamed, A.A. Farag, and T. Moriarty A modified fuzzy c -means algorithm for bias field estimation and segmentation of MRI data IEEE Trans. Med. Imaging 21 2002 193 199
21. R.T. Constable, and R.M. Henkelman Contrast, resolution and detectability in MR imaging J. Comput. Assist. Tomogr. 15 1991 297 303
22. I. Bloch, H. Maître, and M. Anvari Fuzzy adjacency between image objects Int. J. Uncertainty Fuzziness Knowledge-Based Syst. 5 6 1997 615 653
23. I. Bloch On fuzzy distances and their use in image processing under imprecision Pattern Recognit. 32 11 1999 1873 1895
24. I. Bloch Fuzzy relative position between objects in image processing: a morphological approach IEEE Trans. Pattern Anal. Mach. Intell. 21 7 1999 657 664
25. M.N. Ahmed, S.M.N. Mohamed, A.A. Farag, and T. Moriarty A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data IEEE Trans. Med. Imaging 21 2002 193 199
26. S. Ardekani, H. Kangarloo, U. Sinha, Region based fuzzy clustering for automated brain segmentation, in: EMBS/BMES Conference Proceedings of the Second Joint 2, 2002, pp. 1041-1042.
27. X. Wang, J. Keller, P. Gader, Using spatial relationships as features in object recognition, in: Proceedings of the Annual Meeting of the North American Fuzzy Information Processing Society NAFIPS 1997, Syracuse, NY, USA, 1997, pp. 160-165.
28. T. Géraud, I. Bloch, H. Maître, Atlas-guided recognition of cerebral structures in MRI using fusion of fuzzy structural information, in: CIMAF'99 Symposium on Artificial Intelligence, La Havana, Cuba, 1999, pp. 99-106.
29. I. Bloch, T. Géraud, and H. Maître Representation and fusion of heterogeneous fuzzy information in the 3D space for model-based structural recognition - application to 3D brain imaging Artif. Intell. 148 2003 141 175
30. V. Barra, and J.-Y. Boire Automatic segmentation of subcortical brain structures in MR images using information fusion IEEE Trans. Med. Imaging 20 7 2001 549 558
31. D. Collins, C. Holmes, T. Peters, and A. Evans Automatic 3D model-based neuroanatomical segmentation Hum. Brain Mapp. 3 3 1995 190 208
32. B. Dawant, S. Hartmann, J.-P. Thirion, F. Maes, D. Vandermeulen, and P. Demaerel Automatic segmentation of internal structures of the head using a combination of similarity and free-form transformations: part I, methodology and validation on normal subjects IEEE Trans. Med. Imaging 18 10 1999 909 916 (Pubitemid 32211106)
33. G. Gerig, O. Kübler, and R. Kikinis Nonlinear anisotropic filtering of MRI data IEEE Trans. Med. Imaging 11 1992 221 232
34. A. Lundervold, T. Taxt, L. Ersland, and A.M. Fenstadt Volume distribution of cerebrospinal fluid using multispectral MR imaging Med. Image Anal. 4 2000 123 136
35. R. Mäntylä, T. Erkinjuntti, and O. Salonen Variable agreement between visual rating scales for white matter hyperintensities on MRI: comparison of 13 rating scales in a poststroke cohort Stroke 28 1997 1614 1623
36. O. Salonen, T. Autti, and R. Raininko MRI of the brain in neurologically healthy middle-aged and elderly individuals Neuroradiology 39 1997 537 545
37. A. Stocker, O. Sipilä, and A. Visa Stability study of some neural networks applied to tissue characterization of brain magnetic resonance images Proc. Int. Conf. Pattern Recognit. 4 1996 472 477
38. K. Van Leemput, F. Maes, D. Vandermeulen, and P. Suetens Automated model-based bias field correction of MR images of the brain IEEE Trans. Med. Imaging 18 1999 885 896 (Pubitemid 32211104)
39. B.H. Brinkmann, A. Manduca, and R.A. Robb Optimized homomorphic unsharp masking for MR grayscale inhomogeneity correction IEEE Trans. Med. Imaging 17 1998 161 171
40. M.N. Wu, C.C. Lin, C.C. Chang, Brain tumor detection using color-based k-means clustering segmentation. Intelligent information hiding and multimedia signal processing, 2007. IIHMSP 2007. Third International Conference on Volume 2, Issue 26-28 November 2007, pp. 245-250.
41. R.C. Gonzalez, and R.E. Woods Digital Image Processing second ed. 2002 Prentice-Hall Englewood Cliffs, NJ (Competitive)
42. A.P. Dhawan, and L. Arata Segmentation of medical images through competitive learning Comput. Methods Programs Biomed. 40 2 1993 203 215 (Pubitemid 23272839)
43. R.O. Duda, and P.E. Hart Pattern Classification and Scene Analysis 1973 Wiley New York
44. P.A. Juang, M.N. Wu, J.Y. Shiu, H.Y. Yan, Brain tumor segmentation based on Otsu clustering with multi-threshold ing method, in: Computer and Version Conference Taiwan, December 2007, pp. 472-478.