Cortical surface shape analysis based on spherical wavelets

IEEE Transactions on Medical Imaging

Volumn 26, Issue 4, 2007, Pages 582-597

  Yu, Peng ^a,b   Grant, P Ellen ^c   Qi, Yuan ^d   Han, Xiao ^c,e   Ségonne, Florent ^d,f   Pienaar, Rudolph ^c   Busa, Evelina ^c   Pacheco, Jenni ^c   Makris, Nikos ^c   Buckner, Randy L ^c,g,h   Golland, Polina ^d   Fischl, Bruce ^h  

^a IEEE   (United States)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^c MASSACHUSETTS GENERAL HOSPITAL   (United States)

^d MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^e CMS Inc   (United States)

^f UNIVERSITÉ PARIS EST   (France)

^g HARVARD UNIVERSITY   (United States)

^h HARVARD MEDICAL SCHOOL   (United States)

Author keywords

Folding; MRI; Multiscale; Neurodevelopment

Indexed keywords

BROYDEN-FLETCHER-GOLDFARB-SHANNON (BFGS) APPROXIMATION; CORTICAL SURFACE; GOMPERTZ MODELS; NEURODEVELOPMENT;

APPROXIMATION THEORY; MAGNETIC RESONANCE IMAGING; NEUROLOGY; PATHOLOGY; PRINCIPAL COMPONENT ANALYSIS; SET THEORY; WAVELET TRANSFORMS;

MEDICAL IMAGING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BRAIN CORTEX; COMPUTER ASSISTED DIAGNOSIS; EVALUATION; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; MATHEMATICAL COMPUTING; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CEREBRAL CORTEX; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; NUMERICAL ANALYSIS, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 34047180009     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMI.2007.892499     Document Type: Article

References (36)

1. F. L. Bookstein, Morphometric Tools for Landmark Data: Geometiy and Biology. Cambridge, U.K.: Cambridge Univ. Press, 1991.
2. I. Dryden and K. Mardia, "Multivariate shape analysis," Sankhya, vol. 55, pp. 460-480, 1993.
3. T. Cootes, C. Taylor, D. Cooper, and J. Graham, "Active shape models - Their training and application," Comput. Vis. Image Understanding, vol. 61, pp. 38-59, 1995.
4. C. Brechbüler, G. Gerig, and O. Kubler, "Parametrization of closed surfaces for 3-D shape description," Comput. Vis. Image Understanding, vol. 61, pp. 154-170, 1995.
5. A. Kelemen, G. Székely, and G. Gerig, "Elastic model-based segmentation of 3D neuroradiological data sets," IEEE Trans. Med. Imag., vol. 18, pp. 828-839, 1999.
6. M. Styner, G. Gerig, J. Lieberman, D. Jones, and D. Weinberger, "Statistical shape analysis of neuroanatomical structures based on medial models," Med. Image Anal., vol. 7, pp. 207-220, 2003.
7. L. Shen, J. Ford, F. Makedon, and A. Saykin, "Hippocampal shape analysis surface-based representation and classification," Proc. SPIE Medical Imaging, 2003.
8. M. K. Chung, S. Wang, K. M. Dalton, R. J. Davidson, S. Robbins, and A. C. Evans, "Tensor-based cortical morphometry via weighted spherical harmonic representation," presented at the MMBIA Conf, 2006, unpublished.
9. G. Christensen, R. Rabbitt, and M. Miller, "3D brain mapping using a deformable neuroanatomy," Physics in Medicine and Biology, vol. 39, pp. 609-618, 1994.
10. C. Davatzikos, M. Vaillant, S. Resnick, J. Prince, S. Letovsky, and R. Bryan, "A computerized method for morphological analysis of the corpus callosum," J. Comput. Assist. Tomogr., vol. 20, pp. 88-97, 1996.
11. S. C. Joshi, M. I. Miller, and U. Grenander, "On the geometry and shape of brain sub-manifolds," Int. J. Pattern Recognit. Artif. Intell. (Special Issue Process. MR Images Hum. Brain), vol. 11, no. 8, pp. 1317-1343, 1997.
12. P. Thompson, J. Giedd, R. Woods, D. MacDonald, A. Evans, and A. Toga, "Growth patterns in the developing brain detected by using continuum machanical tensor maps," Nature, pp. 190-193, 2000.
13. T. Blum, "A transformation for extracting new descriptors of shape," in Models for the Perception of Speech and Visual Form. Cambridge: MIT Press, 1967, pp. 362-380.
14. S. Pizer, D. Fritsch, P. Yushkevich, V. Johnson, and E. Chaney, "Segmentation, registration, and measurement of shape variation via image object shape," IEEE Trans. Med. Imag., vol. 18, no. 10, pp. 851-865, Oct. 1999.
15. P. Golland, W. Grimson, and R. Kikinis, "Statistical shape analysis using fixed topology skeletons: Corpus callosum study," in Proc. Inf. Process. Med. Imag., 1999, pp. 382-388.
16. C. Davatzikos, X. Tao, and D. Shen, "Hierarchical active shape models, using the wavelet transform," IEEE Trans. Med. Imag., vol. 22, no. 3, pp. 414-423, Mar. 2003.
17. D. Nain, S. Haker, A. Bobick, and A. Tannenbaum, "Multiscale 3D shape analysis using spherical wavelets," in Proc. MICCAI, Oct. 2005, pp. 459-467.
18. D. Nain, S. Haker, A. Bobbick, and A. Tannenbaum, "Shape-driven surface segmentation using spherical wavelets," in Proc. MICCAI, 2006, pp. 17-24.
19. C. G. Broyden, "An alternative derivation of simplex method," J. Inst. Math. Appl., vol. 6, pp. 76-90, 1970.
20. A. M. Dale, B. Fischl, and M. I. Sereno, "Cortical surface-based analysis 1: Segmentation and surface reconstruction," Neuroimage, vol. 9, pp. 179-194, 1999.
21. B. Fischl, M. I. Sereno, and A. M. Dale, "Cortical surface-based analysis II: Inflation, flattening, and a surface-based coordinate system," Neuroimage, vol. 9, pp. 195-207, 1999.
22. B. Fischl, A. M. Dale, M. I. Sereno, R. B. H. Tootell, and B. R. Rosen, "A coordinate system for the cortical surface," NeuroImage, vol. 7, p. S740, 1998.
23. L. Shen and M. K. Chung, "Large-scale modeling of parametric surfaces using spherical harmonics," presented at the 3rd Int. Symp. 3D Data Processing, Visualization and Transmission (IEEE 3DPVT), Chapel Hill, NC, Jun. 14-16, 2006, unpublished.
24. I. Daubechies, Ten lectures on wavelets, ser. Appl. Math. Philadelphia, PA: SIAM, 1992, vol. 61.
25. P. Schröder and W. Sweldens, "Spherical wavelets: Efficiently representing functions on a sphere," in Proc. SIGGRAPH '95, 1995, pp. 161-172.
26. A. Cohen, I. Daubechies, and J. Faveau, "Biorthogonal bases of compactly supported wavelets," Commun. Pure Appl. Math., vol. 45, pp. 485-560, 1992.
27. E. J. Stollnitz, T. D. DeRose, and D. H. Salesin, Wavelets for Computer Graphics: Theory and Applications. San Francisco, CA: Morgan Kaufmann, 1996.
28. T. F. Cootes, C. J. Taylor, D. H. Cooper, and J. Graham, "Training models of shape from sets of examples," in Proc. Br. Machine Vision Conf., 1992, pp. 9-18, Springer-Verlag.
29. G. Székely et al., "Segmentation of 2D and 3D objects from MRI volume data using constrained elastic deformations of flexible Fourier contour and surface models," Med. Image Anal., vol. 1, pp. 19-34, 1996.
30. M. E. Leventon, W. E. L. Grimson, and O. Faugeras, "Statistical shape influence in geodesic active contours," in Proc. CVPR'2000, 2000, pp. 316-323.
31. D. Shen and C. Davatzikos, "An adaptive-focus deformable model using statistical and geometric information," IEEE Trans. Pattern Anal. Mach. Intell., vol. 22, pp. 906-913, 2000.
32. V. S. J. Caviness, "Mechanical model of brain convolutional development," Science, vol. 189, pp. 18-21, 1975.
33. D. C. V. Essen, "A tension-based theory of morphogenesis and compact wiring in the central nervous system," Nature, vol. 385, pp. 313-318, 1997.
34. E. P. Virene, "Reliability growth and its upper limit," in Proc. 1968 Annu. Symp. Reliability, 1968, pp. 265-270.
35. C. M. Bishop, Neural Networks for Pattern Recognition. Oxford, U.K.: Oxford Umiv. Press, 1995.
36. T. P. Minka, Using Lower Bounds to Approximate Integrals Carnegie Mellon Univ., Pittsburgh, PA, Tech Rep., Jul. 2001.