SVM feature selection for classification of SPECT images of Alzheimer's disease using spatial information

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn , Issue , 2005, Pages 410-417

  Stoeckel, Jonathan ^a   Fung, Glenn ^a  

^a SIEMENS CORPORATE RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN; DIAGNOSIS; DISEASES; IMAGE CLASSIFICATION; LINEAR PROGRAMMING; PATIENT TREATMENT;

ALZHEIMER'S DISEASE; SPATIAL INFORMATION;

MEDICAL IMAGING;

EID: 34548551168     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2005.141     Document Type: Conference Paper

References (23)

1. G. McKhann, D. Drachman, M. Folstein, R. Katzman, D. Price, and E.M. Stadlan. Mental and clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of the Department of Health and Human Services Task Force on Alzheimer's Disease. Neurology, 34(7):939-944, July 1984.
2. M.F. Folstein, S.E. Folstein, and P.R. McHugh. "Mini-Mental State": a practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12(3): 189-198, November 1975.
3. K.M. Gosche, J.A. Mortimer, C.D. Smith, W.R. Markesbery, and D.A. Snowdon. Hippocampal volume as an index of Alzheimer neuropathology: findings from the Nun Study. Neurology, 58(10): 1476-1482, May 2002.
4. I. Goethals, C. van de Wiele, D. Slosman, and R. Dierckx. Brain SPET perfusion in early Alzheimer's disease: where to look? European Journal of Nuclear Medicine, 29(8):975-978, August 2002.
5. W.A. Van Gool, G.J. Walstra, S. Teunisse, P.M. Van der Zant, H.C. Weinstein, and E.A. Van Royen. Diagnosing Alzheimer's disease in elderly, mildly demented patients: the impact of routine single photon emission computed tomography. Journal of Neurology, 242(6):401-405, June 1995.
6. D. Kogure, H. Matsuda, T. Ohnishi, T. Asada, M. Uno, T. Kunihiro, S. Nakano, and M. Takasaki. Longitudinal evaluation of early Alzheimer's disease using brain perfusion SPECT. Journal of Nuclear Medicine, 41(7):1155-1162, July 2000.
7. H. Braak and E. Braak. Diagnostic criteria for neuropathologic assessment of Alzheimer's disease. Neurobiology and Aging, 18(4):S85-S88, July 1997.
8. M.R. Dawson, A. Dobbs, H.R. Hooper, A.J. McEwan, J. Triscott, and J. Cooney. Artificial neural networks that use single-photon emission tomography to identify patients with probable Alzheimer's disease. European Journal of Nuclear Medicine, 21(12): 1303-1311, December 1994.
9. D. Hamilton, D. O'Mahony, J. Coffey, J. Murphy, N. O'Hare, P. Freyne, B. Walsh, and D. Coakley. Classification of mild Alzheimer's disease by artificial neural network analysis of SPET data. Nuclear Medicine Communications, 18(9):805-810, September 1997.
10. R.S.J. Frackowiak, K.J. Fristen, C.D. Frith, and R. Dolan. Human Brain Function. Academic Press, 1997.
11. J. Ashburner, K. Friston, A. Holmes, and J.-B. Poline. Statistical Parametric Mapping, SPM'99. The Welcome Department of Cognitive Neurology. Institute of Neurology, University College London, 1999. Freely available at http://www.fil.ion.ucl.ac.uk/spm.
12. J. Stoeckel, Malandain G., O. Migneco, P.M. Koulibaly, Robert P., N. Ayache, and J. Darcourt. Classification of SPECT images of normal subjects versus images of Alzheimer's disease patients. In W.J. Niessen and M.A. Viergever, editors, 4th Int. Conf. on Medical Image Computing and Computer-Assisted Intervention (MICCAI'01), volume 2208 of LNCS, pages 666-674, Utrecht, The Netherlands, October 2001.
13. A. Roche, G. Malandain, X. Pennec, and N. Ayache. The Correlation Ratio as a New Similarity Metric for Multimodal Image Registration. In W. M. Wells, A. C. F. Colchester, and S. Delp, editors, Medical Image Computing and Computer-Assisted Intervention (MICCAI'98), volume 1496 of Lecture Notes in Computer Science, pages 1115-1124, Boston, USA, October 1998.
14. W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery. Numerical Recipes. The Art of Scientific Computing. Cambridge University Press, 2nd edition, 1997.
15. S. Prima, S. Ourselin, and N. Ayache. Computation of the mid-sagittal plane in 3D brain images. IEEE Transaction on Medical Imaging, 21(2): 122-138, February 2002.
16. V. N. Vapnik. The Nature of Statistical Learning Theory. Springer, New York, 1995.
17. P. S. Bradley and O. L. Mangasarian. Feature selection via concave minimization and support vector machines. In J. Shavlik, editor, Machine Learning Proceedings of the Fifteenth International Conference(ICML '98), pages 82-90, San Francisco, California, 1998. Morgan Kaufmann. ftp://ftp.cs.wisc.edu/math-prog/tech-reports/98-03.ps.
18. O. L. Mangasarian. Arbitrary-norm separating plane. Operations Research Letters, 24:15-23, 1999. ftp://ftp.cs.wisc.edu/math-prog/tech- reports/97-07r.ps.
19. T. Evgeniou, M. Pontil, and T. Poggio. Regularization networks and support vector machines. Advances in Computational Mathematics, 13:1-50, 2000.
20. A. Smola, P. L. Bartlett, B. Schölkopf, and J. Schuurmann (editors). Advances in Large Margin Classifiers. MIT Press, Cambridge, MA, 2000.
21. D. Soonawala, T. Amin, K.P. Ebmeier, J.D. Steele, N.J. Dougall, J. Best, O. Migneco, F. Nobili, and K. Scheidhauer. Statistical parametric mapping of (99m)Tc-HMPAO-SPECT images for the diagnosis of Alzheimer's disease: normalizing to cerebellar tracer uptake. Neuroimage, 17(3): 1193-1202, November 2002.
22. Sebastian Mika, Gunnar Rätsch, and Klaus-Robert Müller. A mathematical programming approach to the kernel fisher algorithm. In NIPS, pages 591-597, 2000.
23. ILOG CPLEX Division, 889 Alder Avenue, Incline Village, Nevada. CPLEX Optimizer, 2004. http://www.cplex.com/.