Cortical sulci recognition and spatial normalization

Medical Image Analysis

Volumn 15, Issue 4, 2011, Pages 529-550

  Perrot, Matthieu ^a   Rivière, Denis ^a   Mangin, Jean François ^a  

^a DIF   (France)

Author keywords

Bayesian; Cortical folds labeling; Registration; Spam; Sulci

Indexed keywords

BAYESIAN; CORTICAL FOLDS LABELING; REGISTRATION; SPAM; SULCI;

INTERNET;

BRAIN;

ADULT; ARTICLE; BAYESIAN LEARNING; BRAIN CORTEX; COMPUTER PROGRAM; CONTROLLED STUDY; CORTICAL SULCI RECOGNITION; FEMALE; HEMISPHERE; HUMAN; HUMAN TISSUE; IMAGE ANALYSIS; MALE; NORMAL HUMAN; PRIORITY JOURNAL; RADIOLOGICAL PARAMETERS; RIGHT HANDEDNESS; SPATIAL NORMALIZATION;

ALGORITHMS; CEREBRAL CORTEX; DATA INTERPRETATION, STATISTICAL; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 79958768301     PISSN: 13618415     EISSN: 13618423     Source Type: Journal    
DOI: 10.1016/j.media.2011.02.008     Document Type: Article

References (79)

1. Allassonniére S., Amit Y., Trouvé A. Towards a coherent statistical framework for dense deformable template estimation. Journal of the Royal Statistical Society Series B 2007, 69(1):3-29.
2. Arsigny V., Pennec X., Ayache N. Polyrigid and polyaffine transformations: a novel geometrical tool to deal with non-rigid deformations - application to the registration of histological slices. Medical Image Analysis 2005, 9(6):507-523.
3. Ashburner J. A fast diffeomorphic image registration algorithm. NeuroImage 2007, 38(1):95-113.
4. Ashburner J., Friston K. Unified segmentation. NeuroImage 2005, 26:839-851.
5. Ashburner J., Neelin P., Collins D.L., Evans A., Friston K. Incorporating prior knowledge into image registration. NeuroImage 1997, 6(4):344-352.
6. Auzias G., Glaunés J., Colliot O., Perrot M., Mangin J.-F., Trouvé A., Baillet S. DISCO: A Coherent Diffeomorphic Framework for Brain Registration Under Exhaustive Sulcal Constraints 2009, Springer.
7. Avants B., Gee J. Geodesic estimation for large deformation anatomical shape averaging and interpolation. NeuroImage 2004, 23:S139-S150.
8. Bingham C. An antipodally symmetric distribution on the sphere. Annals of Statistics 1974, 2(6):1201-1225.
9. Boisvert J., Cheriet F., Pennec X., Labelle H., Ayache N. Geometric variability of the scoliotic spine using statistics on articulated shape models. IEEE Transactions on Medical Imaging 2008, 27(4):557-568.
10. Cachier P., Mangin J.-F., Pennec X., Rivière D., Papadopoulos-Orfanos D., Régis J., Ayache N. Multisubject non-rigid registration of brain mri using intensity and geometric features. MICCAI '01: Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention 2001, 734-742. Springer-Verlag, London, UK.
11. Caunce A., Taylor C.J. 3D point distribution models of the cortical sulci. ICCV '98: Proceedings of the Sixth International Conference on Computer Vision 1998, IEEE Computer Society, Washington, DC, USA, p. 402.
12. Chui H., Rangarajan A. A feature registration framework using mixture models. MMBIA '00: Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis 2000, 190-197. IEEE Computer Society, Washington, DC, USA.
13. Chui H., Rambo J., Duncan J.S., Schultz R., Rangarajan A. Registration of cortical anatomical structures via robust 3d point matching. IPMI '99: Proceedings of the 16th International Conference on Information Processing in Medical Imaging 1999, 168-181. Springer-Verlag, London, UK.
14. Collins L.D., Neelin P., Peters T.M., Evans A.C. Automatic 3d intersubject registration of mr volumetric data in standardized talairach space. Journal of Computer Assisted Tomography 1994, 18:192-205.
15. Collins D., Holmes C., Peters T., Evans A. Automatic 3d model-based neuroanatomical segmentation. Human Brain Mapping 1995, 3(3):190-208.
16. Collins D.L., Goualher G.L., Evans A.C. Non-linear cerebral registration with sulcal constraints. MICCAI '98: Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention 1998, 974-984. Springer-Verlag, London, UK.
17. De Craene, M., du Bois d'Aische, A., Macq, B., Warfield, S., September 2005. Multi-subject variational registration for probabilistic unbiased atlas generation. In: IEEE International Conference on Image Processing, 2005 (ICIP 2005), vol. 3, pp. 601-604.
18. Dempster A.P., Laird N.M., Rubin D.B. Maximum likelihood from incomplete data via the em algorithm. Journal of the Royal Statistical Society, Series B (Methodological) 1977, 39(1):1-38.
19. Dubois J., Benders M., Cachia A., Lazeyras F., Leuchter R.H.-V., Sizonenko S., Borradori-Tolsa C., Mangin J.-F., Hüppi P. Mapping the early cortical folding process in the preterm newborn brain. Cerebral Cortex 2008, 18(6):1444-1454.
20. Eckstein, I., Joshi, A.A., Kuo, C.C.J., Leahy, R.M., Desbrun, M., 2007. Generalized surface flows for deformable registration and cortical matching. In: MICCAI (1), pp. 692-700.
21. Evans A., Collins D., Mills S., Brown E., Kelly R., Peters T. 3D statistical neuroanatomical models from 305 mri volumes. IEEE Nuclear Science Symposium and Medical Imaging Conference 1993, 3:1813-1817.
22. Evans A., Collins D., Neelin P., Kamber M., Marrett T. Three-dimensional correlative imaging: applications in human brain mapping. Functional Neuroimaging 1994, 145-161. (Chapter 14).
23. Fischl B., Sereno M.I., Tootell R.B.H., Dale A.M. High-resolution intersubject averaging and a coordinate system for the cortical surface. Human Brain Mapping 1999, 8:272-284.
24. Fischl B., van der Kouwe A., Destrieux C., Halgren E., Ségonne F., Salat D.H., Busa E., Seidman L.J., Goldstein J., Kennedy D., Caviness V., Makris N., Rosen B., Dale A.M. Automatically parcellating the human cerebral cortex. Cerebral Cortex 2004, 14(1):11-22.
25. Gholipour A., Kehtarnavaz N.D., Briggs R., Devous M., Gopinath K.S. Brain functional localization: a survey of image registration techniques. IEEE Transactions on Medical Imaging 2007, 26(4):427-451.
26. Glaunés, J., Joshi, S., October 2006. Template estimation form unlabeled point set data and surfaces for computational anatomy. In: Pennec, X., Joshi, S. (Eds.), Proceedings of the International Workshop on the Mathematical Foundations of Computational Anatomy (MFCA-2006), pp. 29-39.
27. Glaunés J., Trouvé A., Younes L. Diffeomorphic matching of distributions: a new approach for unlabelled point-sets and sub-manifolds matching. CVPR 2004, 02:712-718.
28. Goualher G.L., Barillot C., Bizais Y. Modeling cortical sulci with active ribbons. IJPRAI 1997, 11(8):1295-1315.
29. Hellier P., Barillot C., Corouge I., Gibaud B., Goualher G.L., Collins L., Evans A., Mal G., Ayache N. Retrospective evaluation of inter-subject brain registration. IEEE Transactions on Medical Imaging 2003, 22:1120-1130.
30. Hurdal M.K., Gutierrez J.B., Laing C., Smith D.A. Shape analysis for automated sulcal classification and parcellation of mri data. Journal of Combinatorial Optimization 2008, 15(3):257-275.
31. Joshi S., Davis B., Jomier B.M., Gerig G. Unbiased diffeomorphic atlas construction for computational anatomy. Neuroimage 2004, 23:151-160.
32. Joshi, A.A., Shattuck, D.W., Thompson, P.M., Leahy, R.M., 2005. A framework for registration, statistical characterization and classification of cortically constrained functional imaging data. In: IPMI, pp. 186-196.
33. Kao C.-Y., Hofer M., Sapiro G., Stern J., Rehm K., Rottenberg D.A. A geometric method for automatic extraction of sulcal fundi. IEEE Transactions on Medical Imaging 2007, 26(4):530-540.
34. Klein A., Hirsch J. Mindboggle: a scatterbrained approach to automate brain labeling. NeuroImage 2005, 24(2):261-280.
35. Le Goualher, G., Collins, D., Barillot, C., Evans, A., 1998. Automatic identification of cortical sulci using a 3d probabilistic atlas. In: MICCAI '98: Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention, vol. 1496, pp. 509-518.
36. Lohmann G. Extracting line representations of sulcal and gyral patterns in mr images of the human brain. IEEE Transactions on Medical Imaging 1998, 17(6).
37. Lohmann G., von Cramon D.Y. Automatic labelling of the human cortical surface using sulcal basins. Medical Image Analysis 2000, 4(3):179-188.
38. Lohmann G., von Cramon D., Colchester A. Deep sulcal landmarks provide an organizing framework for human cortical folding. Cerebral Cortex 2008, 18(6):1415-1420.
39. Lui L.M., Wang Y., Chan T.F., Thompson P. Landmark constrained genus zero surface conformal mapping and its application to brain mapping research. Applied Numerical Mathematics 2007, 57(5-7):847-858.
40. Lyttelton O., Boucher M., Robbins S., Evans A. An unbiased iterative group registration template for cortical surface analysis. NeuroImage 2007, 34(4):1535-1544.
41. Maintz J.B., Viergever M.A. A survey of medical image registration. Medical Image Analysis 1998, 2(1):1-36.
42. Mangin J.-F., Frouin V., Bloch I., Règis J., Lopez-Krahe J. From 3D magnetic resonance images to structural representations of the cortex topography using topology preserving deformations. Journal of Mathematical Imaging and Vision 1995, 5:297-318.
43. Mangin J.-F., Riviére D., Cachia A., Duchesnay E., Cointepas Y., Papadopoulos-Orfanos D., Scifo P., Ochiai T., Brunelle F., Règis J. A framework to study the cortical folding patterns. NeuroImage 2004, 23:S129-S138.
44. Mardia K.V., Jupp P.E. Directional Statistics 2000, Wiley. second ed.
45. Mazziotta J.C., Toga A.W., Evans A., Fox P., Lancaster J. A probabilistic atlas of the human brain: theory and rationale for its development: the international consortium for brain mapping (icbm). NeuroImage 1995, 2, Part 1(2):89-101.
46. Mazziotta J., Toga A., Evans A., Fox P., Lancaster J., Zilles K., Woods R., Paus T., Simpson G., Pike B., Holmes C., Collins L., Thompson P., MacDonald D., Iacoboni M., Schormann T., Amunts K., Palomero-Gallagher N., Geyer S., Parsons L., Narr K., Kabani N., Le Goualher G., Boomsma D., Cannon T., Kawashima R., Mazoyer B. A probabilistic atlas and reference system for the human brain: international consortium for brain mapping (icbm). Philosophical Transactions of the Royal Society London Sereis B: Biological Sciences 2001, 356(1412):1293-1322.
47. Ono M., Kubik S., Abarnathey C.D. Atlas of the Cerebral Sulci 1990, Thieme Medical Publishers.
48. Ourselin S., Roche A., Prima S., Ayache N. Block matching: a general framework to improve robustness of rigid registration of medical images. Lecture Notes in Computer Science 2000, vol. 1935:557-566. Springer, Pittsburgh, USA. S. Delp, A. DiGioia, B. Jaramaz (Eds.).
49. Parzen E. On estimation of a probability density function and mode. The Annals of Mathematical Statistics 1962, 33(3):1065-1076.
50. Pennec X., Thirion J.-P. A framework for uncertainty and validation of 3D registration methods based on points and frames. International Journal of Computer Vision 1997, 25(3):203-229.
51. Perrot, M., Rivière, D., Mangin, J.-F., 2008. Identifying cortical sulci from localization, shape and local organization. In: ISBI, pp. 420-423.
52. Pinel P., Thirion B., Mèriaux S., Jobert A., Serres J., Le Bihan D., Poline J.-B., Dehaene S. Fast reproducible identification and large-scale databasing of individual functional cognitive networks. BMC Neuroscience 2007, 8(1):91.
53. Pohl K.M., Fisher J., Grimson, Kikinis R., Wells W.M. A bayesian model for joint segmentation and registration. NeuroImage 2006, 31(1):228-239.
54. Poupon, C., Poupon, F., Allirol, L., Mangin, J.-F., 2006. A database dedicated to anatomo-functional study of human brain connectivity. In: 12th HBM Neuroimage, No. 646, Florence, Italie.
55. Powell M.J.D. An efficient method for finding the minimum of a function of several variables without calculating derivatives. The Computer Journal 1964, 7(2):155-162.
56. Régis J., Mangin J.-F., Ochiai T., Frouin V., Rivière D., Cachia A., Tamura M., Samson Y. sulcal root generic model: a hypothesis to overcome the variability of the human cortex folding patterns. Neurologia Medico-Chirurgica (Tokyo) 2005, 45:1-17.
57. Rivière D., Mangin J.-F., Papadopoulos-Orfanos D., Martinez J.-M., Frouin V., Régis J. Automatic recognition of cortical sulci of the human brain using a congregation of neural networks. Medical Image Analysis 2002, 6(2):77-92.
58. Riviére, D., Geffroy, D., Denghien, I., Souedet, N., Cointepas, Y., 2009. BrainVISA: an extensible software environment for sharing multimodal neuroimaging data and processing tools. In: Proceedings of the 15th HBM. http://www.brainvisa.info.
59. Seong J., Im K., Yoo S., Seo S., Na D., Lee J. Automatic extraction of sulcal lines on cortical surfaces based on anisotropic geodesic distance. NeuroImage 2010, 49(1):293-302.
60. Shattuck D.W., Mirza M., Adisetiyo V., Hojatkashani C., Salamon G., Narr K.L., Poldrack R.A., Bilder R.M., Toga A.W. Construction of a 3d probabilistic atlas of human cortical structures. NeuroImage 2008, 39(3):1064-1080.
61. Shattuck D., Joshi A., Pantazis D., Kan E., Dutton R., Sowell E., Thompson P., Toga A., Leahy R. Semi-automated method for delineation of landmarks on models of the cerebral cortex. Journal of Neuroscience Methods 2009, 178(2):385-392.
62. Shi Y., Thompson P., Dinov I., Toga A. Hamilton-Jacobi skeleton on cortical surfaces. MedImg 2008, 27(5):664-673.
63. Shi Y., Tu Z., Reiss A., Dutton R., Lee A., Galaburda A., Dinov I., Thompson P., Toga A. Joint sulcal detection on cortical surfaces with graphical models and boosted priors. IEEE Transactions on Medical Imaging 2009, 28(3):361-373.
64. Talairach, J., Tournoux, P., 1988. Co-planar Stereotaxic Atlas of the Human Brain.
65. Tao X., Prince J.L., Davatzikos C. Using a statistical shape model to extract sulcal curves on the outer cortex of the human brain. IEEE Transactions on Medical Imaging 2002, 21(5):513-524.
66. Thompson P.M., Toga A.W. Detection, visualization and animation of abnormal anatomic structure with a deformable probabilistic brain atlas based on random vector field transformations. Medical Image Analysis 1997, 1:271-294.
67. Thompson P.M., Woods R.P., Mega M.S., Toga A.W. Mathematical/computational challenges in creating deformable and probabilistic atlases of the human brain. Human Brain Mapping 2000, 9(2):81-92.
68. Tosun D., Prince J. A geometry-driven optical flow warping for spatial normalization of cortical surfaces. IEEE Transactions on Medical Imaging 2008, 27(12):1739-1753.
69. Tosun D., Rettmann M.E., Prince J.L. Mapping techniques for aligning sulci across multiple brains. Lecture Notes in Computer Science 2003, vol. 2879:862-869. Springer. R.E. Ellis, T.M. Peters (Eds.).
70. Tu Z., Zheng S., Yuille A.L., Reiss A.L., Dutton R.A., Lee A.D., Galaburda A.M., Dinov I.D., Thompson P.M., Toga A.W. Automated extraction of the cortical sulci based on a supervised learning approach. IEEE Transactions on Medical Imaging 2007, 26(4):541-552.
71. Vaillant M., Davatzikos C. Finding parametric representations of the cortical sulci using an active contour model. Medical Image Analysis 1997, 1:295-315.
72. Vaillant M., Davatzikos C. Hierarchical matching of cortical features for deformable brain image registration. IPMI 1999, 182-195. Springer-Verlag.
73. Van Essen D.C. A population-average, landmark- and surface-based (pals) atlas of human cerebral cortex. NeuroImage 2005, 28(3):635-662.
74. Vivodtzev, F., Linsen, L., Hamann, B., Joy, K.I., Olshausen, B.A., 2005. Brain mapping using topology graphs obtained by surface segmentation.
75. Yang, F., Kruggel, F., 2007. Optimization algorithms for labeling brain sulci based on graph matching. In: ICCV, pp. 1-7.
76. Yang F., Kruggel F. A graph matching approach for labeling brain sulci using location, orientation, and shape. Neurocomputing 2009, in print.
77. Yeo B., Sabuncu M., Desikan R., Fischl B., Golland P. Effects of registration regularization and atlas sharpness on segmentation accuracy. Medical Image Analysis 2008, 12:603-615.
78. Yeo B., Sabuncu M., Vercauteren T., Ayache N., Fischl B., Golland P. Spherical demons: fast diffeomorphic landmark-free surface registration. IEEE Transactions on Medical Imaging 2010, 29(3):650-668.
79. Zhou Y., Thompson P.M., Toga A.W. Extracting and representing the cortical sulci. IEEE Computer Graphics and Applications 1999, 19(3):49-55.