Anatomical regularization on statistical manifolds for the classification of patients with Alzheimer's disease

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

Volumn 7009 LNCS, Issue , 2011, Pages 201-208

  Cuingnet, Rémi ^a,b   Glaunès, Joan Alexis ^a,c   Chupin, Marie ^a   Benali, Habib ^b   Colliot, Olivier ^a  

^a SORBONNE UNIVERSITÉ   (France)

^b INSERM   (France)

^c UNIVERSITÉ PARIS DESCARTES   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ALZHEIMER'S DISEASE; ANATOMICAL INFORMATION; CLASSIFICATION PERFORMANCE; CONCENTRATION MAPS; FEATURE MAP; GRAY MATTER; STATISTICAL MANIFOLDS;

COMPUTER AIDED ANALYSIS; COMPUTER AIDED INSTRUCTION; MAGNETIC RESONANCE; MEDICAL COMPUTING; NEURODEGENERATIVE DISEASES; PATIENT TREATMENT; SUPPORT VECTOR MACHINES;

MEDICAL IMAGING;

EID: 80053951505     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-24319-6_25     Document Type: Conference Paper

References (21)

1. Ashburner, J., Friston, K.J.: Voxel-based morphometry-the methods. NeuroImage 11(6), 805-821 (2000)
2. Davatzikos, C.: Why voxel-based morphometric analysis should be used with great caution when characterizing group differences. NeuroImage 23(1), 17-20 (2004)
3. Vapnik, V.N.: The Nature of Statistical Learning Theory. Springer, Heidelberg (1995)
4. Schölkopf, B., Smola, A.J.: Learning with Kernels. MIT Press, Cambridge (2001)
5. Davatzikos, C., et al.: Individual patient diagnosis of AD and FTD via high-dimensional pattern classification of MRI. NeuroImage 41(4), 1220-1227 (2008)
6. Klöppel, S., et al.: Automatic classification of MR scans in Alzheimer's disease. Brain 131(3), 681-689 (2008)
7. Vemuri, P., et al.: Alzheimer's disease diagnosis in individual subjects using structural mr images: Validation studies. NeuroImage 39(3), 1186-1197 (2008)
8. Gerardin, É., et al.: Multidimensional classification of hippocampal shape features discriminates Alzheimer's disease and mild cognitive impairment from normal aging. NeuroImage 47(4), 1476-1486 (2009)
9. Cuingnet, R., et al.: Automatic classification of patients with Alzheimer's disease from structural MRI: A comparison of ten methods using the ADNI database. NeuroImage 56(2), 766-781 (2011)
10. Fan, Y., et al.: COMPARE: classification of morphological patterns using adaptive regional elements. IEEE Transactions on Medical Imaging 26(1), 93-105 (2007)
11. Duchesne, S., et al.: Automated computer differential classification in Parkinsonian syndromes via pattern analysis on MRI. Academic Radiology 16(1), 61-70 (2009)
12. Cuingnet, R., Rosso, C., Lehéricy, S., Dormont, D., Benali, H., Samson, Y., Colliot, O.: Spatially regularized SVM for the detection of brain areas associated with stroke outcome. In: Jiang, T., Navab, N., Pluim, J.P.W., Viergever, M.A. (eds.) MICCAI 2010. LNCS, vol. 6361, pp. 316-323. Springer, Heidelberg (2010)
13. Querbes, O., et al.: Early diagnosis of Alzheimer's disease using cortical thickness: impact of cognitive reserve. Brain 132(8), 2036-2047 (2009)
14. Jost, J.: Riemannian geometry and geometric analysis. Springer, Heidelberg (2008)
15. Lafferty, J., Lebanon, G.: Diffusion kernels on statistical manifolds. JMLR 6, 129-163 (2005)
16. Hebey, E.: Sobolev spaces on Riemannian manifolds. Springer, Heidelberg (1996)
17. Amari, S.I., et al.: Differential Geometry in Statistical Inference, vol. 10. Institute of Mathematical Statistics (1987)
18. Druet, O., Hebey, E., Robert, F.: Blow-up theory for elliptic PDEs in Riemannian geometry. Princeton Univ. Press, Princeton (2004)
19. Jack, C.R., et al.: The Alzheimer's disease neuroimaging initiative (ADNI): MRI methods. Journal of Magnetic Resonance Imaging 27(4) (2008)
20. Ashburner, J., Friston, K.J.: Unified segmentation. NeuroImage 26(3), 839-851 (2005)
21. Ashburner, J.: A fast diffeomorphic image registration algorithm. NeuroImage 38(1), 95-113 (2007)