Localized maximum entropy shape modelling

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4584 LNCS, Issue , 2007, Pages 619-629

  Loog, Marco ^a  

^a UNIVERSITY OF COPENHAGEN   (Denmark)

Author keywords

[No Author keywords available]

Indexed keywords

COVARIANCE MATRIX; DATA ACQUISITION; IMAGE SEGMENTATION; PRINCIPAL COMPONENT ANALYSIS;

MATRIX COMPLETION; MAXIMUM ENTROPY; POINT DISTRIBUTION MODEL; SHAPE COMPLEXITY;

MEDICAL IMAGING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; HUMAN; IMAGE QUALITY; LUNG; METHODOLOGY; RADIOGRAPHY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THORAX RADIOGRAPHY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; HUMANS; LUNG; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; RADIOGRAPHY, THORACIC; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 38149111189     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-73273-0_51     Document Type: Conference Paper

References (23)

1. Cootes, T.F., Taylor, C.J., Cooper, D., Graham, J.: Active shape models-their training and application. Computer Vision and Image Understanding 61, 38-59 (1995)
2. Cover, T.M., Thomas, J.A.: Elements of Information Theory. Wiley Interscience, New York (1991)
3. Jaynes, E.T.: On the rationale of maximum-entropy methods. In: Proceedings of the IEEE, vol. 70, pp. 939-952 (1982)
4. Cootes, T.F., Taylor, C.J.: Combining point distribution models with shape models based on finite-element analysis. Image and Vision Computing 13, 403-409 (1995)
5. de Bruijne, M., van Ginneken, B., Viergever, M., Niessen, W.: Adapting active shape models for 3D segmentation of tubular structures in medical images. In: Taylor, C.J., Noble, J.A. (eds.) IPMI 2003. LNCS, vol. 2732, pp. 136-147. Springer, Heidelberg (2003)
6. Wang, Y., Staib, L.H.: Elastic model based non-rigid registration incorporating statistical shape information. In: Wells, W.M., Colchester, A.C.F., Delp, S.L. (eds.) MICCAI 1998. LNCS, vol. 1496, pp. 1162-1173. Springer, Heidelberg (1998)
7. Wang, Y., Staib, L.H.: Boundary finding with prior shape and smoothness models. IEEE Transactions on Pattern Analysis and Machine Intelligence 22, 738-743 (2000)
8. Shen, D., Davatzikos, C.: An adaptive-focus statistical shape model for segmentation and shape modeling of 3-D brain structures. IEEE Transactions on Medical Imaging 20, 257-270 (2001)
9. Lötjönen, J., Antila, K., Lamminmäki, E., Koikkalainen, J., Lilja, M., Cootes, T.: Artificial enlargement of a training set for statistical shape models: Application to cardiac images. In: Frangi, A.F., Radeva, P.I., Santos, A., Hernandez, M. (eds.) FIMH 2005. LNCS, vol. 3504, pp. 92-101. Springer, Heidelberg (2005)
10. Davatzikos, C., Tao, X., Shen, D.: Hierarchical active shape models using the wavelet transform. IEEE Transactions on Medical Imaging 22, 414-423 (2003)
11. Mohamed, A., Davatzikosh, C.: Shape representation via best orthogonal basis selection. In: Barillot, C., Haynor, D.R., Hellier, P. (eds.) MICCAI 2004. LNCS, vol. 3216, pp. 225-233. Springer, Heidelberg (2004)
12. Nain, D., Haker, S., Bobick, A., Tannenbaum, A.R.: Multiscale 3D shape analysis using spherical wavelets. In: Duncan, J.S., Gerig, G. (eds.) MICCAI 2005. LNCS, vol. 3750, pp. 459-467. Springer, Heidelberg (2005)
13. Zhao, Z., Aylward, S.R., Teoh, E.K.: A novel 3D partitioned active shape model for segmentation of brain MR images. In: Duncan, J.S., Gerig, G. (eds.) MICCAI 2005. LNCS, vol. 3749, pp. 221-228. Springer, Heidelberg (2005)
14. Johnson, C.R.: Matrix completion problems: A survey. In: Proceedings of Symposia in Applied Mathematics. Providence, Rhode Island, American Mathematical Society 1990, vol. 40, pp. 171-198 (1990)
15. Laurent, M.: In: Matrix completion problems. (Interior-M) of The Encyclopedia of Optimization, vol.III, pp. 221-229. Kluwer Academic Publishers, Dordrecht (2001)
16. Boyd, S., Vandenberghe, L.: Convex Optimization. Cambridge University Press, Cambridge (2004)
17. Glunt, W., Hayden, T.L., Johnson, C.R., Tarazaga, P.: Positive definite completions and determinant maximization. Linear Algebra and its Applications 288, 1-10 (1999)
18. van Ginneken, B., Stegmann, M., Loog, M.: Segmentation of anatomical structures in chest radiographs using supervised methods: a comparative study on a public database. Medical Image Analysis 10, 19-40 (2006)
19. Davies, R.H.: Learning Shape: Optimal Models for Analysing Natural Variability. Ph.D. Thesis, Division of Imaging Science and Biomedical Engineering, University of Manchester, UK (2002)
20. Styner, M.A., Rajamani, K.T., Nolte, L.P., Zsemlye, G., Székely, G., Taylor, C.J., Davies, R.H.: Evaluation of 3D correspondence methods for model building. In: Taylor, C.J., Noble, J.A. (eds.) IPMI 2003. LNCS, vol. 2732, pp. 63-75. Springer, Heidelberg (2003)
21. Romdhani, S., Gong, S., Psarrou, A.: A multi-view non-linear active shape model using kernel PCA. In: Proceedings of the 10th British Machine Vison Conference, Nottingham, UK, vol. 2, pp. 483-492. BMVA Press (1999)
22. Sozou, P., Cootes, T.F., Taylor, C.J., Mauro, E.D.: A non-linear generalisation of point distribution models using polynomial regression. Image and Vision Computing 13, 451-457 (1995)
23. Larsen, R., Eiriksson, H., Stegmann, M.B.: Q-MAF shape decomposition. In: Niessen, W.J., Viergever, M.A. (eds.) MICCAI 2001. LNCS, vol. 2208, pp. 837-844. Springer, Heidelberg (2001)