Automated segmentation and classification of multispectral magnetic resonance images of brain using artificial neural networks

IEEE Transactions on Medical Imaging

Volumn 16, Issue 6, 1997, Pages 911-918

  Reddick, Wilburn E ^a   Glass, John O ^a   Cook, Edwin N ^a   David Elkin, T ^a   Deaton, Russell J ^a  

^a ST JUDE CHILDREN S RESEARCH HOSPITAL   (United States)

Author keywords

Image processing; Image segmentation and classification; MRI; Neural networks

Indexed keywords

ADULT; ARTICLE; ARTIFICIAL NEURAL NETWORK; BRAIN; FEMALE; HISTOLOGY; HUMAN; IMAGE PROCESSING; MALE; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY;

ADULT; BRAIN; FEMALE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MALE; NEURAL NETWORKS (COMPUTER); REPRODUCIBILITY OF RESULTS;

BACKPROPAGATION; BRAIN; IMAGE SEGMENTATION; MEDICAL IMAGING; NEURAL NETWORKS; NEUROPHYSIOLOGY;

CEREBROSPINAL FLUID (CSF); IMAGE CLASSIFICATION; KOHONEN SELF-ORGANIZING NEURAL NETWORKS;

MAGNETIC RESONANCE IMAGING;

EID: 0031283432     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/42.650887     Document Type: Article

References (42)

1. R. L. Galloway, Jr., R. J. Maciunas, and A. L. Failinger, "Factors affecting perceived tumor volumes in magnetic resonance imaging," Ann. Biomed. Eng., vol. 21, pp. 367-375, 1993.
2. P. A. Narayana, E. F. Jackson, and J. S. Wolinsky, "Inter- and intraoperator variability in the quantitative volumetric measurements of multiple sclerosis lesions," J. Magn. Reson. Imag., (Supp.), vol. 3, pp. 111-112, 1993. (Abstract)
3. T. Taxt, A. Lundervold, B. Fuglaas, H. Lien, and V. Abeler, "Multispectral analysis of uterine corpus tumors in magnetic resonance imaging," Magn. Reson. in Med., vol. 23, pp. 55-76, 1992.
4. R. P. Velthuizen, L. P. Clarke, S. Phuphanich, L. O. Hall, A. M. Bensaid, J. A. Arrington, H. Greenberg, and M. L. Silbiger, "Unsupervised measurement of brain tumor volume on MR images," J. Magn. Reson. Imag., vol. 5, pp. 594-605, 1995.
5. S. C. Carpentieri, R. K. Mulhern, S. Douglas, S. Hanna, and D. L. Fairclough, "Behavioral resiliency among children surviving brain tumors: A longitudinal study," J. Clin. Child Psycho!., vol. 22, pp. 236-246, 1993.
6. E. H. Aylward, P. D. Brettschneider, J. C. McArthur, G. J. Harris, T. E. Schlaepfer, J. D. Henderer, P. E. Barta, A. Y. Tien, and G. D. Pearlson, "Magnetic resonance imaging measurements of gray matter volume reductions in HIV dementia," Amer. J. Psych., vol. 152, pp. 987-994, 1995.
7. M. W. Vannier, R. L. Butterfield, D. Jordan, W. A. Murphy, R. G. Levitt, and M. Gado, "Multispectral analysis of magnetic resonance images," Radial., vol. 154, pp. 221-224, 1985.
8. R. Bachus, H. Konig, G. Lenz, M. Deimling, and E. R. Reinhardt, "Tissue differentiation in MRI by means of pattern recognition," Comput. Assist. Radial, vol. pp. 496-501, 1985.
9. C. R. Meyer, G. S. Leichtman, J. A. Brunberg, R. L. Wahl, and L. E. Quint, "Simultaneous usage of homologous points, lines, and planes for optimal, 3-D, linear registration of multimodality imaging data," IEEE Trans. Med. Imag., vol. 14, pp. 1-11, 1995.
10. C. R. Meyer, P. H. Bland, and J. Pipe, "Retrospective correction of intensity inhomogeneities in MRI," IEEE Trans. Med. Imag., vol. 14, pp. 36-41, 1995.
11. B. M. Dawant, A. P. Zijdenbos, and R. A. Margolin, "Correction of intensity variations in MR images for computer-aided tissue classifica-tion," IEEE Trans. Med. Imag., vol. 12, pp. 770-781, 1993.
12. K. Ying, B. Clymer, and P. Schmalbrock, "Adaptive filtering processing for magnetic resonance images," in Proc. Soc. Magnetic Resonance, 2nd Meeting, pp. 803, 1994. (Abstract)
13. G. Gerig, O. Kubler, R. Kikinis, and F. A. Jolesz, "Nonlinear anisotropic filtering of MRI data," IEEE Trans. Med. Imag., vol. 11, pp. 221-232, 1992.
14. M. Tincher, C. R. Meyer, R. Gupta, and D. M. Williams, "Polynomial modeling and reduction of RF body coil spatial inhomogeneity in MRI," IEEE Trans. Med. Imag., vol. 12, pp. 361-365, 1993.
15. A. Simmons, S. R. Arridge, G. J. Barker, A. J. Cluckie, and P. S. Tofts, "Improvements to the quality of MRI cluster analysis," Magn. Reson. Imag., vol. 12, pp. 1191-1204, 1994.
16. L. P. Clarke, R. P. Velthuizen, M. A. Camacho, J. J. Heine, M. Vaidyanathan, L. O. Hall, R. W. Thatcher, and M. L. Silbiger, "MRI segmentation: Methods and applications," Magn. Reson. Imag., vol. 13, pp. 343-368, 1995.
17. J. C. Bezdek, L. O. Hall, and L. P. Clarke, "Review of MR image segmentation techniques using pattern recognition," Med. Phys., vol. 20, pp. 1033-1048, 1993.
18. H. E. Cline, W. E. Lorensen, S. P. Souza, F. A. Jolesz, R. Kikinis, G. Gerig, and T. E. Kennedy, "3-D surface rendered MR images of the brain and its vasculature," J. Comput. Assist. Tomogr., vol. 15, pp. 344-351, 1991.
19. M. I. Kohn, N. K. Tanna, G. T. Herman, S. M. Resnick, P. D. Mozley, R. E. Gur, A. Alavi, R. A. Zimmerman, and R. C. Gur, "Analysis of brain cerebrospinal fluid volumes with MR imaging," Radial., vol. 178, pp. 115-122, 1991.
20. K. J. McClain, Y. Zhu, and J. D. Hazle, "Selection of MR images for automated segmentation," J. Magn. Reson. Imag., vol. 5, pp. 485-4192, 1995.
21. D. D. Blatter, E. D. Bigler, S. D. Gale, S. C. Johnson, C. V. Anderson, B. M. Burnett, N. Parker, S. Kurth, and S. D. Horn, "Quantitative volumetric analysis of brain MR: normative database spanning five decades of life," Amer. J. Neuroradiol., vol. 16, pp. 241-251, 1995.
22. L. M. Fletcher, J. B. Barsotti, and J. P. Hornak, "A multispectral analysis of brain tissues," Magn. Reson. in Med., vol. 29, pp. 623-630, 1993.
23. M. Kamber, R. Shinghal, D. L. Collins, G. S. Francis, and A. C. Evans, "Model-based 3-D segmentation of multiple sclerosis lesions in magnetic resonance brain images," IEEE Trans. Med. Imag., vol. 14, pp. 442-453, 1995.
24. T. Taxt and A. Lundervold, "Multispectral analysis of the brain using magnetic resonance imaging," IEEE Trans. Med. Imag., vol. 13, pp. 470-481, 1994.
25. M. C. Clark, L. O. Hall, D. B. Goldgof, L. P. Clarke, R. P. Velthuizen, and M. S. Silbiger, "MRI segmentation using fuzzy clustering techniques," IEEE Eng. Med., Biol, vol. 13, pp. 730-742, 1994.
26. C. Li, D. Goldgof, and L. Hall, "Knowledge-based classification and tissue labeling of MR images of human brain," IEEE Trans. Med. Imag., vol. 12, pp. 740-750, 1993.
27. A. Lundervold and G. Storvik, "Segmentation of brain parenchyma and cerebrospinal fluid in multispectral magnetic resonance images," IEEE Trans. Med. Imag., vol. 14, pp. 339-349, 1995.
28. Z. Liang, J. R. MacFall, and D. P. Harrington, "Parameter estimation and tissue segmentation from multispectral MR images," IEEE Trans. Med. Imag., vol. 13, pp. 441-449, 1994.
29. W. M. Wells.III, W. E. L. Crimson, R. Kikinis, and F. A. Jolesz, "Adaptive segmentation of MRI data," IEEE Trans. Med. Imag., vol. 15, pp. 429-4442, 1996.
30. M. Ozkan, B. M. Dawant, and R. J. Maciunas, "Neural-networkbased segmentation of multi-modal medical images: A comparative and prospective study," IEEE Trans. Med. Imag., vol. 12, pp. 534-544, 1993.
31. S. C. Amartur, D. Piraino, and Y. Takefuji, "Optimization neural networks for the segmentation of magnetic resonance images," IEEE Trans. Med. Imag., vol. 11, pp. 215-220, 1992.
32. U. Raff, A. L. Scherzinger, P. F. Vargas, and J. H. Simon, "Quantitation of gray matter, white matter, and cerebrospinal fluid from spin-echo magnetic resonance images using an artificial neural network technique," Med. Phys.. vol. 21, pp. 1933-1942, 1994.
33. N. R. Pal, J. C. Bezdek, and E. C.-K. Tsao, "Generalized clustering networks and Kohonen's self-organizing scheme," IEEE Trans. Neural Networks, vol. 4, pp. 549-557, 1993.
34. K. Cheng, J. Lin, and C. Mao, "The application of competitive Hopfield neural network to medical image segmentation," IEEE Trans. Med. Imag.. vol. 15, pp. 560-567, 1996.
35. T. Kohonen, Self-Organization and Associative Memory. New York: Springer-Verlag, 1989.
36. J. A. Freeman and D. M. Skapura, Neural Networks: Algorithms, Applications, and Programming Techniques. Reading, MA: AddisonWesley, 1991.
37. S. Haring, M. A. Viergever, and J. N. Kok, "Kohonen networks for multiscale image segmentation," Image, Vision Comput., vol. 12, pp. 339-344, 1994.
38. E. C. Evans, D. L. Collins, P. Neelin, D. MacDonald, M. Kamber, and T. S. Marrett, "Three-dimensional correlative imaging: Applications in human brain mapping," in Functional Neuroimaging: Technical Foundations. Orlando, FL: Academic, 1994, pp. 145-161.
39. E. F. Jackson, P. A. Narayana, J. S. Wolinsky, and T. J. Doyle, "Accuracy and reproducibility in volumetric analysis of multiple sclerosis lesions," J. Comput. Assist. Tomogr.. vol. 17, pp. 200-205, 1993.
40. G. Gerig, J. Martin, R. Kikinis, O. Kubler, M. Shenton, and F. A. Jolesz, "Unsupervised tissue type segmentation of 3D dual-echo MR head data," Image, Vision Comput.. vol. 10, pp. 349-360, 1992.
41. R. Kikinis, M. E. Shenton, and G. Gerig, J. Martin, M. Anderson, D. Metcalf, C. R. G. Guttman, R. W. McCarley, W. Lorensen, H. Cline, and F. A. Jolez, "Routine quantitative analysis of brain and cerebrospinal fluid spaces with MR imaging," J. Magn. Reson. Imag., vol. 2, pp. 619-629, 1992.
42. J. P. Guilford, Fundamental Statistics in Psychology and Education, 4th ed. New York: McGraw-Hill, 1965.