A tensor-based morphometry study of genetic influences on brain structure using a new fluid registration method

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

Volumn 5242 LNCS, Issue PART 2, 2008, Pages 914-921

  Brun, Caroline ^a   Leporé, Natasha ^a   Pennec, Xavier ^b   Chou, Yi Yu ^a   Lee, Agatha D ^a   Barysheva, Marina ^a   De Zubicaray, Grieg ^c   Meredith, Matthew ^c   McMahon, Katie ^c   Wright, Margaret J ^d   Toga, Arthur W ^a   Thompson, Paul M ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b INRIA   (France)

^c UNIVERSITY OF QUEENSLAND   (Australia)

^d QIMR BERGHOFER MEDICAL RESEARCH INSTITUTE   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

DISTRIBUTION FUNCTIONS; MEDICAL COMPUTING; MEDICAL IMAGING; TENSORS;

BRAIN MORPHOLOGIES; CUMULATIVE DISTRIBUTION FUNCTION; FLUID REGISTRATION; INTRACLASS CORRELATIONS; JACOBIAN DETERMINANTS; POWER IMPROVEMENTS; REGISTRATION TECHNIQUES; TENSOR-BASED MORPHOMETRY;

MAGNETIC RESONANCE IMAGING;

ADULT; ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; BRAIN; COMPUTER ASSISTED DIAGNOSIS; DIFFUSION WEIGHTED IMAGING; DIZYGOTIC TWINS; FEMALE; GENETICS; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; MALE; METHODOLOGY; MONOZYGOTIC TWINS; PHYSIOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING;

ALGORITHMS; BRAIN; DIFFUSION MAGNETIC RESONANCE IMAGING; FEMALE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MALE; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE; TWINS, DIZYGOTIC; TWINS, MONOZYGOTIC; YOUNG ADULT;

EID: 79551688517     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-85990-1_110     Document Type: Conference Paper

References (27)

1. Arsigny, V., et al.: Log-Euclidean metrics for fast and simple calculus on diffusion tensors. Mag. Res. Med. 56, 411-421 (2006)
2. Ashburner, J., et al.: A fast diffeomorphic image registration algorithm. Neuro Image 38, 95-113 (2007)
3. Brun, C., et al.: Comparison of Standard and Riemannian fluid registration for Tensor-Based Morphometry in HIV/AIDS. In: Workshop on Statistical Registration, MICCAI, Brisbane, Australia (2007)
4. Brun, C., et al.: A new registration method based on Log-Euclidean tensor metrics and its application to genetic studies. In: ISBI, Paris, France (2008)
5. Cachier, P., et al.: Symmetrization of the Non-Rigid Registration Problem using Inversion-Invariant Energies: Application to Multiple Sclerosis. In: Delp, S.L., DiGoia, A.M., Jaramaz, B. (eds.) MICCAI 2000. LNCS, vol. 1935, pp. 472-481. Springer, Heidelberg (2000)
6. Chiang, M.C., et al.: pattern of brain atrophy in HIV/AIDS visualized using tensorbased morphometry. Neuro image 34, 44-60 (2007)
7. Chou, Y.Y., et al.: Lateral ventricular surface morphology and volume changes in twins. Neuro image (submitted, 2008)
8. Christensen, G.E., et al.: Deformable templates using large deformation kinematics. IEEE Trans. Image Process 5, 1435-1447 (1996)
9. Chung, M.K., et al.: A Unified Statistical Approach to Deformation-Based Morphometry. Neuro image 14, 595-606 (2006)
10. Collins, D.L., et al.: Design and construction of realistic digital brain phantom. IEEE-TMI 17, 463-468 (1998)
11. Davatzikos, C., et al.: A computerized approach for morphological analysis of the corpus callosum. JCAT 20, 88-97 (1996)
12. Gee, J., et al.: Elastic matching: continuum mechanical and probabilistic analysis. Brain Warping (1998)
13. Gramkow, C.: Registration of 2D and 3D medical images, Master's thesis, Danish Technical University, Copenhagen, Denmark (1996)
14. Grenander, U., et al.: Computational anatomy: An emerging discipline. Quart. of App. Maths. 56, 617-694 (1998)
15. Kochunov, P., et al.: Regional spatial normalization: toward an optimatl target. J. Comput. Assist. Tomogr. 25, 805-816 (2001)
16. Lee, A.D., et al.: 3D Pattern of Brain Abnormalities in Fragile X Syndrome Visualized using Tensor-Based Morphometry. Neuro image 34, 924-938 (2007)
17. Leporé, N., et al.: Generalized Tensor-Based Morphometry of HIV/AIDS using multivariate statistics on deformation tensors. IEEE-TMI 27, 129-141 (2008)
18. Leporé, N., et al.: Tensor based morphometry using fast fluid registration an application to deafness. In: SPIE, San Diego, California, USA (2008)
19. Leporé, N., et al.: Best individual template selection from deformation tensor minimization. In: ISBI, Paris, France (2008)
20. Neale, M.C., et al.: Mx: Statistical modeling. Richmond (1999)
21. Nichols, T.E., Holmes, A.P.: Non parametric permutation tests for functional neuroimaging: a primer with examples. Hum. Brain Map 15, 1-25 (2001)
22. Pennec, X., et al.: Riemannian elasticity: A statistical regularization framework for non-linear registration. In: Duncan, J.S., Gerig, G. (eds.) MICCAI 2005. LNCS, vol. 3750, pp. 943-950. Springer, Heidelberg (2005)
23. Scamvougeras, et al.: Size of the human corpus callosum is genetically determined: An MRI study in mono and dizygotic twins. Neurosci. Lett. 338, 91-94 (2003)
24. Scout, P.E., Fleiss, J.L.: Intraclass correlations: Uses in assessing rater reliability. Psychol. Bull. 2, 420-428 (1979)
25. Shattuck, D.W., Leahy, R.M.: BrainSuite: an automated cortical surface identification tool. Med. Image Anal. 8, 129-141 (2002)
26. Styner, M.: Morphometric analysis of lateral ventricles in schizophrenia and healthy controls, regarding genetic and disease-specific factors. PNAS, 4872-4877 (2005)
27. Thompson, P.M., et al.: Growth Patterns in the Developing Brain Detected By Using Continuum-Mechanical Tensor Maps. Nature 404, 190-193 (2000)