Classification based on cortical folding patterns

IEEE Transactions on Medical Imaging

Volumn 26, Issue 4, 2007, Pages 553-565

  Duchesnay, Edouard ^a   Cachia, Arnaud ^a   Roche, Alexis ^b   Rivière, Denis ^b   Cointepas, Yann ^b   Papadopoulos Orfanos, Dimitri ^b   Zilbovicius, Monica ^a   Martinot, Jean Luc ^a   Régis, Jean ^c   Mangin, Jean François ^b  

^a SERVICE HOSPITALIER FRÉDÉRIC JOLIOT   (France)

^b DIF   (France)

^c TIMONE HOSPITAL   (France)

Author keywords

Feature selection; Pattern recognition; Sulcal morphometry

Indexed keywords

BRAIN MODELS; CLASSIFICATION (OF INFORMATION); DATA STRUCTURES; DISCRIMINANT ANALYSIS; PROBABILITY DISTRIBUTIONS;

MULTIVARIALE RECOGNITION MODELS; SULCAL MORPHOMETRY;

FEATURE EXTRACTION;

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: 34047099795     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMI.2007.892501     Document Type: Article

References (44)

1. E. A. Maguire, D. G. Gadian, I. S. Johnsrude, C. D. Good, J. Ashburner, R. S. Frackowiak, and C. D. Frith, "Navigation-related structural change in the hippocampi of taxi drivers," Proc. Nat. Acad. Sci. USA, vol. 97, no. 9, pp. 4414-4416, 2000.
2. B. Draganski, C. Gaser, V. Busch, G. Schuierer, U. Bogdahn, and A. May, "Neuroplasticity: Changes in grey matter induced by training," Nature, vol. 427, pp. 311-312, 2004.
3. C. Leonard, M. Eckert, and J. Kuldau, "Exploiting human anatomical variability as a link between genome and cognome," Genes Brain Behav., vol. 5, no. Suppl 1, pp. 64-77, 2006.
4. J. Ashburner and K. J. Friston, "Voxel-based morphometry - The methods," NeuroImage, vol. 11, pp. 805-821, 2000.
5. J. Ashburner, J. G. Csernansky, C. Davatzikos, N. C. Fox, G. B. Frisoni, and P. M. Thompson, "Computer-assisted imaging to assess brain structure in healthy and diseased brains," Lancet Neurol., vol. 2, pp. 79-88, 2003.
6. A. W. Toga and P. M. Thompson, "New approaches in brain morphometry," Amer J. Geriatr. Psychiatry, vol. 10, no. 1, pp. 13-23, 2002.
7. J.-F. Mangin, D. Rivière, A. Cachia, E. Duchesnay, Y. Cointepas, D. Papadopoulos-Orfanos, D. L. Collins, A. C. Evans, and J. Régis, "Object-based morphometry of the cerebral cortex," IEEE Trans. Med. Imag., vol. 23, no. 8, pp. 968-982, Aug. 2004.
8. K. Friston and J. Ashburner, "Generative and recognition models for neuroanatomy," NeuroImage, vol. 23, pp. 21-24, 2004.
9. C. Davatzikos, "Why voxel-based morphometric analysis should be used with great caution when characterizing group differences," NeuroImage, vol. 23, pp. 17-20, 2004.
10. B. Schölkopf and A. Smola, Learning With Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. Cambridge, MA: MIT Press, 2002.
11. E. Duchesnay, A. Roche, D. Rivière, D. Papadopoulos-Orfanos, Y. Cointepas, and J.-F. Mangin, "Population classification based on structural morphometry of cortical sulci," in Proc. 2nd. IEEE ISBI, Arlington, VA, Apr. 2004, pp. 1276-1279.
12. D. Rivière, J.-F. Mangin, D. Papadopoulos-Orfanos, J.-M. Martinez, V. Frouin, and J. Régis, "Automatic recognition of cortical sulci of the human brain using a congregation of neural networks," Med. Image Anal., vol. 6, no. 2, pp. 77-92, 2002.
13. J.-F. Mangin, D. Rivière, A. Cachia, E. Duchesnay, Y. Cointepas, D. Papadopoulos-Orfanos, P. Scifo, T. Ochiai, F. Brunelle, and J. Régis, "A framework to study the cortical folding patterns," Neuroimage, vol. 23, pp. S129-S138, 2004.
14. D. D. Cox and R. L. Savoy, "Functional magnetic resonance imaging (fmri) "brain reading:" Detecting and classifying distributed patterns of fmri activity in human visual cortex," NeuroImage, vol. 19, no. 2, pp. 261-270, Jun. 2003.
15. C. Davatzikos, K. Ruparel, Y. Fan, D. G. Shen, M. Acharyya, J. W. Loughead, R. C. Gur, and D. D. Langleben, "Classifying spatial patterns of brain activity with machine learning methods: Application to lie detection,"NeuroImage vol. 28, no. 3, pp. 663-668, Nov. 2005.
16. Y. Kamitani and F. Tong, "Decoding the visual and subjective contents of the human brain," Nat. Neurosci., vol. 8, pp. 679-685, May 2005.
17. J.-D. Haynes and G. Rees, "Predicting the orientation of invisible stimuli from activity in human primary visual cortex," Nat. Neurosci., vol. 8, pp. 686-691, April 2005.
18. B. Thirion, E. Duchesnay, J. Dubois, J.-B. Poline, and D. L. Bihan, "Reading in the subject's mind: The case of low-level vision," in Proc. 11th HBMCD-RomNeuroimage, Toronto, ON, Canada, Jun. 12-16, 2005, vol. 26, no. 1.
19. M. Martínez-Ramón, V. Koltchinskii, G. L. Heileman, and S. Posse, "fmri pattern classification using neuroanatomically constrained boosting," NeuroImage, vol. 31, no. 3, pp. 1129-1141, Jul. 2006.
20. P. Golland, W. E. L. Grimson, M. E. Shenton, and R. Kikinis, "Small sample size learning for shape analysis of anatomical structures," in MICCAI, 2000, pp. 72-82.
21. P. Yushkevich, S. Joshi, S. Pizer, J. Csernansky, and L. Wang, "Feature selection for shape-based classification of biological objects," in IPMI, C. Taylor and A. Noble, Eds.: Springer-Verlag, 2003, vol. 2732, pp. 114-125.
22. Z. Lao, D. Shen, Z. Xue, B. Karacali, S. Resnick, and C. Davatzikos, "Morphological classification of brains via high-dimensional shape transformations and machine learning methods," NeuroImage, vol. 21, pp. 46-57, 2004.
23. C. Davatzikos, D. Shen, R. C. Gur, X. Wu, D. Liu, Y. Fan, P. Hughett, B. I. Turetsky, and R. E. Gur, "Whole-brain morphometric study of schizophrenia reveals a spatially complex set of focal abnormalities," JAMA Arch. General Psychiatry, vol. 62, pp. 1218-1227, November 2005.
24. S. Duchesne, N. Bernasconi, A. Bernasconi, and D. Collins, "Mr-based neurological disease classification methodology: Application to lateralization of seizure focus in temporal lobe epilepsy," NeuroImage, vol. 29, no. 2, pp. 557-566, January 2006.
25. K. S. Pollard, M. D. Birkner, M. J. van der Laan, and S. Dudoit, Test statistics null distributions in multiple testing: Simulation studies and applications to genomics U.C. Berkeley Division of Biostatistics Working Paper Series, Jul. 2005 [Online], Available: http://www.bepress.com/ucbbiostat/ paper184, Tech. Rep.
26. I. Guyon and A. Elisseeff, "An introduction to variable and feature selection," J. Mach. Learning Res., vol. 3, pp. 1157-1182, Mar. 2003.
27. J. Kittler, "Feature set search algorithms," Pattern Recognition Signal Processing, pp. 41-60, 1978.
28. J. Pudil, N. J., and J. K. J., "Floating search methods in feature selection," Pattern Recognition Lett., vol. 15, pp. 1119-1125, 1994.
29. D. Hand and C. Taylor, "Multivariate analysis of variance and repeated measures: A practical guide for behavioural scientists," in London, U.K.: Chapman & Hall, 1987.
30. A. Rakotomamonjy, "Variable selection using svm-based criteria," J. Mach. Learning Res., vol. 3, pp. 1357-1370, Mar. 2003.
31. V. Vapnik and A. Chervonenkis, "On the uniform convergence of relative frequencies of events to their probabilities," Theory Prob. Appl., vol. 16, no. 2, pp. 264-280, 1971.
32. V. N. Vapnik, The Nature of Statistical Learning Theory. New York: Springer-Verlag, 1995.
33. D. L. Collins, P. Neelin, T. M. Peters, and A. C. Evans, "Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space," J. Comput. Assist. Tomogr., vol. 18, no. 2, pp. 192-205, Mar. 1994.
34. C. Ambroise and G. J. McLachlan, "Selection bias in gene extraction on the basis of microarray gene-expression data," Proc. Nat. Acad. Sci. USA, vol. 99, no. 10, pp. 6562-6566, May 2002.
35. T. Hastie, R. Tibshirani, and J. Friedman, Eds., The Elements of Statistical Learning, ser. Statistics. New York: Springer, 2001.
36. I. Guyon, J. Weston, S. Barnhill, and V. Vapnik, "Gene selection for cancer classification using support vector machines," Mach. Learn., vol. 46, pp. 389-422, 2002.
37. D. C. Van Essen, "A tension-based theory of morphogenesis and compact wiring in the central nervous system," Nature, vol. 385, no. 23, pp. 313-318, January 1997.
38. J. Régis, J.-F. Mangin, T. Ochiai, V. Frouin, D. Rivière, A. Cachia, M. Tamura, and Y. Samson, ""Sulcal root" generic model: A hypothesis to overcome the variability of the human cortex folding patterns," Neurol. Med. Chir. (Tokyo), vol. 45, pp. 1-17, 2005.
39. C. D. Good, I. Johnsrude, J. Ashburner, R. N. A. Henson, K. J. Friston, and R. S. J. Frackowiak, "Cerebral asymmetry and the effects of sex and handedness on brain structure: A voxel-based morphometric analysis of 465 normal adult human brains," NeuroImage, vol. 14, no. 3, pp. 685-700, 2001.
40. K. Watkins, T. Paus, J. Lerch, A. Zijdenbos, D. L. Collins, P. Neelin, J. Taylor, K. J. Worsley, and A. C. Evans, "Structural asymmetries in the human brain: A voxel-based statistical analysis of 142 mri scans," Cerebral Cortex, vol. 11, no. 9, pp. 868-877, 2001.
41. E. Luders, K. Narr, P. Thompson, R. Woods, D. Rex, L. Jancke, H. Steinmetz, and A. Toga, "Mapping cortical gray matter in the young adult brain: Effects of gender," NeuroImage, vol. 26, no. 2, pp. 493-501, 2005.
42. E. Luders, K. Narr, P. Thompson, D. Rex, R. Woods, H. DeLuca, L. Jancke, and A. Toga, "Gender effects on cortical thickness and the influence of scaling," Human Brain Mapp., vol. 27, pp. 314-324, 2005.
43. A. Toga and P. Thompson, "Mapping brain asymmetry," Nature Neurosci., vol. 4, no. 1, pp. 37-48, 2003.
44. V. Vapnik and O. Chapelle, "Bounds on error expectation for support vector machines," Neural Computation, vol. 12, no. 9, pp. 2013-2036, 2000.