Sparse principal component analysis in medical shape modeling

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Volumn 6144 III, Issue , 2006, Pages

  Sjöstrand, Karl ^a   Stegmann, Mikkel B ^a   Larsen, Rasmus ^a  

^a TECHNICAL UNIVERSITY OF DENMARK   (Denmark)

Author keywords

Corpus Callosum; Evaluation of Principal Components; PCA; Shape Modeling; Sparse Principal Component Analysis

Indexed keywords

ALGORITHMS; DATA REDUCTION; DRUG PRODUCTS; MATHEMATICAL MODELS; MEDICAL IMAGING; SCANNING;

CORPUS CALLOSUM; EVALUATION OF PRINCIPAL COMPONENTS; SHAPE MODELING; SPARSE PRINCIPAL COMPONENT ANALYSIS;

PRINCIPAL COMPONENT ANALYSIS;

EID: 33745139146     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.651658     Document Type: Conference Paper

References (18)

1. J. N. R. Jeffers, "Two case studies in the application of principal component analysis," Applied Statistics 16(3), pp. 225-236, 1967.
2. J. Cadima and I. T. Jolliffe, "Loadings and correlations in the interpretation of principal components," Journal of Applied Statistics 22(2), pp. 203-214, 1995.
3. H. H. Harman, Modern Factor Analysis, The University of Chicago Press, 1967.
4. H. F. Kaiser, "The varimax criterion for analytic rotation in factor analysis." Psychometrika 23, pp. 187-200, 1958.
5. M. B. Stegmann and K. Sjöstrand, "Sparse modeling of landmark and texture variability using the orthomax criterion." International Symposium on Medical Imaging 2006. San Diego, CA (to appear), feb 2006.
6. C. Chenriubhotla and A. Jepson, "Sparse PCA extracting multi-scale structure from data," Proceedings of the. IEEE International Conference on Computer Vision 1, pp. 641-647, 2001.
7. S. Vines. "Simple principal components." Journal of the Royal Statistical Society: Series C (Applied Statiatics) 49(4), pp. 441-451, 2000.
8. R. Hausman, "Constrained multivariate analysis." in Optimization in Statistics, S. Zanakis arid J. Rustagi, eds., Studies in the management sciences(19), pp. 137-151, North-Holland, Amsterdam, 1982.
9. V. Rousson and T. Gasser, "Simple component analysis," Journal of the Royal Statistical Society: Series C (Applied Statistics) 53(4), pp. 539-555, 2004.
10. A. d'Aspremont, L. El Ghaoui, M. I. Jordan, and G. R. G. Lanckriet, "A direct formulation for sparse PCA using semidefinite programming,"
11. I. T. Jolliffe, N. T. Trendafilov, and M. Uddin, "A modified principal component technique based on the LASSO," Journal of Computational and Graphical Statistics 12(3), pp. 531-547, 2003.
12. R. Tibshirani, "Regression shrinkage and selection via the LASSO," Journal of the Royal Statistical Society Series B Methodological 58(1), pp. 267-288, 1996.
13. H. Zou, T. Hastie, and R. Tibshirani, "Sparse principal component analysis," tech. rep., Statistics Department, Stanford University, 2004.
14. B. Efron, T. Hastie, I. Johnstone, and R. Tibshirani. "Least angle regression," Annals of Statistics 32(2), pp. 407-451, 2004.
15. H. Zou and T. Hastie, "Regularizatiori and variable selection via the elastic net," Journal of the Royal Statistical Society: Series B (Statistical Methodology) 67(2), pp. 301-320, 2005.
16. I. T. Jolliffe, "Rotation of principal components: Choice of normalization constraints," Journal of Applied Statistics 22(1), pp. 29-36, 1995.
17. D. Gervini and V. Rousson, "Criteria for evaluating dimension-reducing components for multivariate data." American Statistician 58(1), pp. 72-76, 2004.
18. M. B. Stegmann, K. Skoglund, and C. Ryberg, "Mid-sagittal plane and mid-sagittal surface optimization in brain MRI using a local symmetry measure." in International Symposium, on Medical Imaging 2005, San Diego, CA, Proc. of SPIE vol. 5747, SPIE, feb 2005.