Brain fiber architecture, genetics, and intelligence: A high angular resolution diffusion imaging (HARDI) study

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

Volumn 5241 LNCS, Issue PART 1, 2008, Pages 1060-1067

  Chiang, Ming Chang ^a   Barysheva, Marina ^a   Lee, Agatha D ^a   Madsen, Sarah ^a   Klunder, Andrea D ^a   Toga, Arthur W ^a   McMahon, Katie L ^b   De Zubicaray, Greig I ^b   Meredith, Matthew ^b   Wright, Margaret J ^c   Srivastava, Anuj ^d   Balov, Nikolay ^d   Thompson, Paul M ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF QUEENSLAND   (Australia)

^c QIMR BERGHOFER MEDICAL RESEARCH INSTITUTE   (Australia)

^d FLORIDA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DIFFUSION PROFILES; ENVIRONMENTAL CONTROL; FIBER ANISOTROPY; FIBER ARCHITECTURE; FIBER CONNECTIVITY; FIBER INTEGRITY; FIBER ORIENTATION DISTRIBUTION; FLUID REGISTRATION; GENETIC CONTROL; HIGH ANGULAR RESOLUTION DIFFUSION IMAGING; HIGHLY-CORRELATED; JENSEN-SHANNON DIVERGENCE; RESAMPLING; RIEMANNIAN MANIFOLD; SPATIAL COHERENCE; STRUCTURAL EQUATION MODELS;

ANISOTROPY; ARCHITECTURAL DESIGN; CHROMOSOMES; COMPUTER SCIENCE; DISTRIBUTION FUNCTIONS; GENETIC ENGINEERING; MEDICAL COMPUTING; MEDICAL IMAGING; POPULATION STATISTICS; THREE DIMENSIONAL;

FIBERS;

ADULT; ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; BRAIN; COMPUTER ASSISTED DIAGNOSIS; DIFFUSION; FEMALE; GENETICS; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; INTELLIGENCE; MALE; METHODOLOGY; MYELINATED NERVE; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; TWINS; ULTRASTRUCTURE;

ALGORITHMS; BRAIN; DIFFUSION; FEMALE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INTELLIGENCE; MAGNETIC RESONANCE IMAGING; MALE; NERVE FIBERS, MYELINATED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; TWINS; YOUNG ADULT;

EID: 70450163050     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-85988-8_126     Document Type: Conference Paper

References (17)

1. Tuch, D.S.: Q-ball imaging. Magn. Reson. Med. 52(6). 1358-1372 (2004)
2. Jones. D.K., Horsfield. M.A., Simmons, A.: Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging. Magn. Reson. Med. 42(3), 515-525 (1999)
3. Jenkinson. M., Smith, S.: A global optimisation method for robust affine registration of brain images. Med. Image Anal. 5(2), 143-156 (2001)
4. Alexander, D.C., et al.: Spatial transformations of diffusion tensor magnetic resonance. IEEE Transactions on Medical Imaging 20, 1131-1139 (2001)
5. Arsigny, V., et al.: Fast and simple calculus on tensors in the log-Euclidean framework. In: Duncan, J.S., Gerig, G. (eds.) MICCAI 2005. LNCS, vol.3749, pp. 115-122. Springer, Heidelberg (2005)
6. Chiang, M.C., et al.: Fluid Registration of Diffusion Tensor Images Using Information Theory. IEEE Transactions on Medical Imaging 27, 442-456 (2008)
7. Descoteaux, M., et al.: Regularized, fast. and robust analytical Q-ball imaging. Magn. Reson. Med. 58(3), 497-510 (2007)
8. Chiang, M.-C. et al.: Information-theoretic analysis of brain white matter fiber orientation distribution functions. In: Karssemeijer, N., Lelieveldt, B. (eds.) IPMI 2007. LNCS, vol. 4584, pp. 172-182. Springer, Heidelberg (2007)
9. Srivastava, A., Jermyn. I., Joshi, S.H.: Riemannian Analysis of Probability Density Functions with applications in Vision. In: CVPR 2007, Minneapolis. Minnesota, USA (2007)
10. Lin, J.: Divergence measures based on the Shannon entropy. IEEE Trans. Information Theory 37(1), 145-151 (1991)
11. Neale, M.C., Cardon, L.R.: The NATO Scientific Affairs Division. Methodology for genetic studies of twins and families, vol. xxv. 496 p. Kluwer Academic Publishers, Dordrecht (1992)
12. Schmitt, J.E., et al.: A multivariate analysis of neuroanatomic relationships in a genetically informative pediatric sample. Neuroimage 35(1), 70-82 (2007)
13. Bollen, K.A., Stine, R.A.: Bootstrapping goodness-of-fit measures in structural equation models. Sociological Methods Research 21(2), 205-229 (1992)
14. Press, W.H., et al.: Numerical recipes in C++, 2nd edn., vol. viii, 318 p. Cambridge Univ. Press, Cambridge (2002)
15. Hedeker, D., Gibbons. R.D., Flay, B.R.: Random-effects regression models for clustered data with an example from smoking prevention research. J. Consult. Clin. Psych. 62(4). 757-765 (1994)
16. Rencher, A.C.: Methods of multivariate analysis. 2nd edn. J. Wiley, New York (2002)
17. Storey. J.D.: A direct approach to false discovery rates. J. Roy. Stat. Soc. B 64(3), 479-498 (2002)