A supervised multiview spectral embedding method for neuroimaging classification

2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings

Volumn , Issue , 2013, Pages 601-605

  Liu, Sidong ^a   Zhang, Lelin ^a   Cai, Weidong ^a   Song, Yang ^a   Wang, Zhiyong ^a   Wen, Lingfeng ^b   Feng, David Dagan ^a  

^a UNIVERSITY OF SYDNEY   (Australia)

^b ROYAL PRINCE ALFRED HOSPITAL   (Australia)

Author keywords

multi view spectral embedding; neuroimaging classification; supervised learning

Indexed keywords

EMBEDDINGS; NEUROIMAGING; SUPERVISED LEARNING;

CLASSIFICATION PERFORMANCE; FEATURE SPACE; HIGH-DIMENSIONAL; LOW DIMENSIONAL; MULTI-MODAL; RICH FEATURES; SPECTRAL EMBEDDING; STATE OF THE ART;

CLASSIFICATION (OF INFORMATION);

EID: 84897728315     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIP.2013.6738124     Document Type: Conference Paper

References (25)

1. S. Batty, J. Clark, T. Fryer and X. Gao, "Prototype system for semantic retrieval of neurological PET images," The International Conference on Medical Imaging and Informatics (MIMI 2007), Aug 14-16, 2007, Beijing, LNCS 4987, pp.179-188, 2008.
2. S. Liu, W. Cai, L. Wen, S. Eberl, M. Fulham and D. Feng, "Localized Functional Neuroimaging Retrieval using 3D Discrete Curvelet Transform," IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2011), pp. 1877-1880, 2011.
3. S. Liu, W. Cai, L. Wen and D. Feng, "Volumetric Congruent Local Binary Patterns for 3D Neurological Image Retrieval," IEEE International Conference on Image and Vision Computing New Zealand (IVCNZ 2011), 2011.
4. D. Unay, A. Ekin and R. S. Jasinschi, "Local Structure-based Region of Interest Retrieval in Brain MR Images," IEEE Trans. on Inf. Tech. in Biomed., vol. 14, issue. 4, pp.897-903, 2010.
5. S. Liu, W. Cai, L. Wen, S. Eberl, M. J. Fulham and D. Feng, "A Robust Volumetric Feature Extraction Approach for 3D Neuroimaging Retrieval," 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2010), 2010.
6. S. Liu, W. Cai, L. Wen and D. Feng, "Neuroimaging Biomarker based Prediction of Alzheimer's Disease Severity with Optimized Graph Construction," IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2013), 2013.
7. W. Cai, D. Feng and R. Fulton, "Content-Based Retrieval of Dynamic PET Functional Images," IEEE Trans. on Information Tech. in Biomedicine, vol. 4, no. 2, pp.152-158, 2000.
8. W. Cai, S. Liu, L. Wen, S. Eberl, M. Fulham and D. Feng, "3D Neurological Image Retrieval with Localized Pathology-Centric CMRGLC Patterns," The IEEE 17th International Conference on Image Processing (ICIP 2010), pp. 3201-3204, 2010.
9. R. C. Petersen, G.E. Smith, S. C. Waring, R. J. Ivnik, E. G. Tangalos and E. Kokmen, "Mild Cognitive Impairment: Clinical Characterization and Outcome," Arch. Neurol., vol. 56, pp. 303-308, 1999.
10. L. Shannon, A. J. Saykin, J. D. West, L. Shen, H. A. Firpi, B. C. McDonald and ADNI, "Baseline MRI Predictors for Conversion from MCI to Probable AD in the ADNI Cohort," Current Alzheimer Research, vol. 6, pp. 347-361, 2009.
11. J. Ye, M. Farnum, E. Yang, R. Verbeeck, V. Lobanov, N. Raghavan, G. Novak, A. DiBernardo, V. A. Narayan and ADNI, "Sparse Learning and Stability Selection for Predicting MCI to AD Conversion using Baseline ADNI Data," BioMed Central Neurology, vol. 12, no. 46, 2012.
12. D. Zhang and D. Shen, "Multi-Modal Multi-Task Learning for Joint Prediction of Clinical Scores in Alzheimer's Disease," MBIA 2011, Nice, France, Oct. 1, 2012.
13. M.Belkin and P.Niyogi, "Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering," Proc. Adv. Neural Inf. Process. Syst., pp. 585-591, 2002.
14. J. Tenenbaum, V. de Silva and J. Langford, "A Global Geomatric Framework for Nonlinear Dimensionality Reduction," Science, vol. 290, no. 5500, pp. 2319-2323, Dec, 2000.
15. B. Long, P. S. Yu and Z. Zhang, "A General Model For Multiple View Unsupervised Learning," Proc. 8th SIAM Int. Conf. Data Mining, pp. 822-833, 2008.
16. T. Xia, D. Tao, T. Mei and Y. Zhang, "Multiview Spectral Embedding," IEEE Tran. Syst. Man. Cybernetics, vol. 40, no. 6, pp. 1438-1446, 2010.
17. C. R. Jack, M. A. Bernstein, N. C. Fox, P. Thompson, G. Alexander, D. Harvey, et al., "The Alzheimer's Disease Neuroimaging Initiative (ADNI): MRI Methods," J. Magnetic Resonance Imaging, vol. 27, issue 4, pp. 685-691, 2008.
18. W. J. Jagust, D. Bandy, K. Chen, N. L. Foster, S. M. Landau, C. A. Mathis, et al., "The Alzheimer's Disease Neuroimaging Initiative Positron Emission Tomography Core," Alzheimer's &Dementia, vol. 6, pp. 221-229, 2010.
19. M. Jenkinson, P. Bannister, J. M. Brady and S. M. Smith, "Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images," NeuroImage, vol. 17, no. 2, pp. 825-841, 2002.
20. J. Mazziotta, A. Toga, A. Evans, P. Fox, J. Lancaster, K. Zilles, et al., "A Probabilistic Atlas and Reference System for the Human Brain: International Consortium for Brain Mapping (ICBM)," Phil. Trans. Royal Soc. B Biol. Sci., vol. 356, no. 1412, pp. 1293-1322, 2001.
21. J. A. Schnabel, D. Rueckert, M. Quist, J. M. Blackall, A. D. Castellano-Smith, T. Harkens, et al., "A Generic Framework for Non-rigid Registration based on Non-uniform Multi-level Freeform Deformations," MICCAI2001, pp. 573-581, 2001.
22. R. A. Heckemann, S. Keihaninejad, P. Aljabar, K. R. Gray, C. Nielsen, D. Rueckert, J. V. Hajnal, A. Hammers and ADNI, "Automatic Morphometry in Alzheimer's Disease and Mild Cognitive Impairment," Neuroimage, vol. 56, pp. 2024-2037, 2011.
23. C. C. Chang and C. J. Lin, "LIBSVM: A Library for Support Vector Machines," ACM Trans. Intel. Sys. Tech, vol.2, no.27, pp. 1-27, 2011.
24. B. Schölkopf, A. Smola and K. R. Müller, "Nonlinear Component Analysis As A Kernel Eigenvalue Problem" Neural Computation, vol. 10, no. 5, pp. 1299-1319, 1998.
25. S. T. Roweis and L. K. Saul, "Nonlinear Dimensionality Reduction By Locally Linearly Embedding," Science, vol. 290, no. 5500, pp. 2323-2326, Dec. 2000.