Disease classification and prediction via semi-supervised dimensionality reduction

Proceedings - International Symposium on Biomedical Imaging

Volumn , Issue , 2011, Pages 1086-1090

  Batmanghelich, Kayhan N ^a   Ye, Dong H ^a   Pohl, Kilian M ^a   Taskar, Ben ^b   Davatzikos, Christos ^a  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

Alzheimer's disease; Basis Learning; Matrix factorization; Mild Cognitive Impairment (MCI); Optimization; Semi supervised Learning

Indexed keywords

ALZHEIMER'S DISEASE; BASIS LEARNING; COGNITIVE IMPAIRMENT; MATRIX FACTORIZATIONS; SEMI-SUPERVISED LEARNING;

DIAGNOSIS; SUPERVISED LEARNING;

MEDICAL IMAGING;

EID: 80055037586     PISSN: 19457928     EISSN: 19458452     Source Type: Conference Proceeding    
DOI: 10.1109/ISBI.2011.5872590     Document Type: Conference Paper

References (15)

1. Nematollah Batmanghelich, Ben Taskar, and Christos Davatzikos, "A general and unifying framework for feature construction, in image-based pattern classification.," Inf Process Med Imaging, vol. 21, pp. 423-434, 2009.
2. J. Ashburner and K. J. Friston, "Voxel-based morphometry- the methods.," Neuroimage, vol. 11, no. 6 Pt 1, pp. 805-821, Jun 2000.
3. Melissa K Carroll, Guillermo A Cecchi, Irina Rish, Rahul Garg, and A. Ravishankar Rao, "Prediction and interpretation of distributed neural activity with sparse models.," Neuroimage, vol. 44, no. 1, pp. 112-122, Jan 2009.
4. Yong Fan, Dinggang Shen, Ruben C Gur, Raquel E Gur, and Christos Davatzikos, "Compare: classification of morphological patterns using adaptive regional elements.," IEEE Trans Med Imaging, vol. 26, no. 1, pp. 93-105, Jan 2007.
5. Polina Golland, W. Eric L. Grimson, Martha E. Shenton, and Ron Kikinis, "Deformation analysis for shape based classification," in In IPMI, 2001, vol. 2082, pp. 517-530.
6. Jihun Hamm, Dong Hye Ye, Ragini Verma, and Christos Davatzikos, "Gram: A framework for geodesic registration on anatomical manifolds.," Med Image Anal, vol. 14, no. 5, pp. 633-642, Oct 2010.
7. Belkin, Mikhail, Niyogi, Partha, and Sindhwani, Vikas, "Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples," Journal of Machine Learning Research, vol. 7, pp. 2399-2434, November 2006.
8. D. D. Lee and H. S. Seung, "Learning the parts of objects by non-negative matrix factorization.," Nature, vol. 401, no. 6755, pp. 788-791, Oct 1999.
9. D. Donoho and V. Stodden, "When does non-negative matrix factorization give a correct decomposition into parts," 2003.
10. Sindhwani, Vikas and Niyogi, Partha, "Linear manifold regularization for large scale semi-supervised learning," in Proc. of the 22nd ICML Workshop on Learning with Partially Classified Training Data, 2005.
11. Tom Vercauteren, Xavier Pennec, Aymeric Perchant, and Nicholas Ayache, "Diffeomorphic demons: efficient non-parametric image registration.," Neuroimage, vol. 45, no. 1 Suppl, pp. S61-S72, Mar 2009.
12. FanR. K. Chung, Spectral Graph Theory.
13. Ernesto G. Birgin, José Mario Martínez, and Marcos Raydan, "Nonmonotone spectral projected gradient methods on convex sets," Philadelphia, PA, USA, 2000, vol. 10, pp. 1196-1211, Society for Industrial and Applied Mathematics.
14. C. Davatzikos, A. Genc, D. Xu, and S. M. Resnick, "Voxel-based morphometry using the ravens maps: methods and validation using simulated longitudinal atrophy," Neuroimage, vol. 14, no. 6, pp. 1361-1369, Dec 2001.
15. Gael Chetelat, Beatrice Desgranges, Vincent De La Sayette, Fausto Viader, Francis Eustache, and Jean-Claude Baron, "Mapping gray matter loss with voxel-based morphometry in mild cognitive impairment.," Neuroreport, vol. 13, no. 15, pp. 1939-1943, Oct 2002.