SPECT image classification based on NMSE feature correlation weighting and SVM

IEEE Nuclear Science Symposium Conference Record

Volumn , Issue , 2009, Pages 2715-2719

  Chaves, R ^a   Ramirez J ^a   Gorriz J M ^a   Lopez M ^a   Alvarez I ^a   Salas Gonzalez, D ^a   Segovia, F ^a   Padilla, P ^a  

^a UNIVERSITY OF GRANADA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

ALZHEIMER'S DISEASE; CLASSIFICATION ACCURACY; CORRELATION PARAMETERS; FEATURE CORRELATION; FEATURE SELECTION; IMAGE PARAMETERS; INNOVATIVE METHOD; INPUT SPACE; LINEAR KERNEL; NORMALIZED MEAN SQUARE ERROR; REGIONS OF INTEREST; SEMI-QUANTITATIVE ANALYSIS; SINGLE PHOTON EMISSION COMPUTED TOMOGRAPHY IMAGES; SPECT IMAGES; STANDARD DEVIATION; STATISTICAL LEARNING THEORY; TOMOGRAPHIC SLICES;

COMPUTER AIDED DIAGNOSIS; IMAGE ANALYSIS; IMAGE CLASSIFICATION; NUCLEAR PHYSICS; SINGLE PHOTON EMISSION COMPUTED TOMOGRAPHY; STATISTICAL TESTS; SUPPORT VECTOR MACHINES; TOMOGRAPHY;

FEATURE EXTRACTION;

EID: 77951146219     PISSN: 10957863     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/NSSMIC.2009.5401973     Document Type: Conference Paper

References (17)

1. R. Higdon, N. L. Foster, R. A. Koeppe, C. S. DeCarli, W. J. Jagust, C. M. Clark, N. R. Barbas, S. E. Arnold, R. S. Turner, J. L. Heidebrink, and S. Minoshima, "A comparison of classification methods for differentiating fronto-temporal dementia from Alzheimer's disease using FDG-PET imaging," Statistics in Medicine, vol. 23, pp. 315-326, 2004.
2. V. N. Vapnik, Estimation of Dependences Based on Empirical Data. Springer-Verlag, New York, 1982.
3. R. P. W. Duin, "Classifiers in almost empty spaces," in International Conference on Pattern Recognition (ICPR), vol. 2, no. 2, 2000, pp. 4392-4395.
4. I. Álvarez, J. M. Górriz, J. Ramírez, D. Salas-González, M. López, C. G.Puntonet, and F. Segovia., "Alzheimer's diagnosis using eigenbrains and support vector machines." IET Electronics Letters, vol. 45, no. 7, pp. 342-343, 2009.
5. J. RamÍrez, J. M. Górriz, D. Salas-Gonzalez, A. Romero, M. López, I. Álvarez, and M. Gómez-Río, "Computer-aided diagnosis of alzheimer's type dementia combining support vector machines and discriminant set of features information sciences," Information Sciences, In press., 2010.
6. P. P. Bruyant, "Analytic and iterative reconstruction algorithms in spect," The Journal of Nuclear Medicine, vol. 43, no. 10, pp. 1343-1358, 2002.
7. D. Salas-González, J. M. Górriz, J. Ramírez, A. Lassl, and C. G. Puntonet, "Improved Gauss-Newton optimization methods in affine registration of SPECT brain images," IET Electronics Letters, vol. 44, no. 22, pp. 1291-1292, 2008.
8. K. J. Friston, J. Ashburner, S. J. Kiebel, T. E. Nichols, and W. D. Penny, Statistical Parametric Mapping: The Analysis of Functional Brain Images. Academic Press, 2007.
9. R. P. Woods, "Spatial transformation models," in Handbook of Medical Imaging, I. N. Bankman, Ed. San Diego: Academic Press, 2000, ch. 29, pp. 465-490.
10. J. Ashburner and K. J. Friston, "Nonlinear spatial normalization using basis functions," Human Brain Mapping, vol. 7, no. 4, pp. 254-266, 1999.
11. M. López, J. Ramírez, J. M. Górriz, D. Salas-González, I. Álvarez, F. Segovia, and C. G. Puntonet, "Automatic tool for the Alzheimer's disease diagnosis using PCA and bayesian classification rules," IET Electronics Letters, vol. 45, no. 8, pp. 389-391, 2009.
12. P. Saxena, D. G. Pavel, J. C. Quintana, and B. Horwitz, "An automatic thresholdbased scaling method for enhancing the usefulness of Tc-HMPAO SPECT in the diagnosis of Alzheimers disease," in Medical Image Computing and Computer-Assisted Intervention - MICCAI, Lecture Notes in Computer Science, vol. 1496, 1998, pp. 623-630.
13. R. Chaves, J. Ramírez, J. M. Górriz, M. López, D. Salas-González, I. Álvarez, and F. Segovia, "Svm-based computer-aided diagnosis of the alzheimer's disease using t-test nmse feature selection with feature correlation weighting," Neuroscience Letters, vol. 461, no. 3, pp. 293-297, 2009.
14. J. Ramírez, J. M. Górriz, R. Chaves, D. Salas-González, I. Álvarez, M. López, and F. Segovia, "Classification of spect images using random forests," IET Electronics Letters, vol. 45, no. 12, pp. 604-605, 2009.
15. D. Kogure, H. Matsuda, T. Ohnishi, T. Asada, M. Uno, T. Kunihiro, S. Nakano, and M. Takasaki, "Longitudinal evaluation of early Alzheimer disease using brain perfusion SPECT," The Journal of Nuclear Medicine, vol. 41, no. 7, pp. 1155-1162, 2000.
16. B. Efron and R. Tibshirani, "Improvements on Cross-Validation: The .632+ Bootstrap Method," vol. 92, no. 438, pp. 548-560, 1997.
17. G. Fung and J. Stoeckel, "SVM feature selection for classification of SPECT images of Alzheimer's disease using spatial information," Knowledge and Information Systems, vol. 11, no. 2, pp. 243-258, 2007.