Understanding scanner upgrade effects on brain integrity & connectivity measures

2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014

Volumn , Issue , 2014, Pages 234-237

  Zhan, L ^a,b   Jahanshad, N ^a,b   Jin, Y ^a,b   Nir, T M ^b   Leonardo, C D ^b   Bernstein, M A ^c   Borowski, B ^c   Jack, Clifford R ^c   Thompson, P M ^a,b,d  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

^c MAYO CLINIC   (United States)

^d UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Anisotropy; Brain network; Connectivity; Diffusion MRI; Scanner; SNR

Indexed keywords

ANISOTROPY; DIFFUSION; MAGNETIC RESONANCE IMAGING; NEURODEGENERATIVE DISEASES; NEUROIMAGING;

ACQUISITION PARAMETERS; BRAIN NETWORKS; CONNECTIVITY; DIFFUSION MRIS; DIFFUSION WEIGHTED IMAGES; MAGNETIC FIELD STRENGTHS; SCANNER; SCANNER MANUFACTURERS;

SCANNING;

EID: 84927935861     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (10)

1. Stein, J.L., et al., Identification of common variants associated with human hippocampal and intracranial volumes. Nat Genet, 44(5): p. 552-61.2012.
2. Mueller, S.G., et al., Ways toward an early diagnosis in Alzheimer's disease: the Alzheimer's Disease Neuroimaging Initiative (ADNI). Alzheimers Dement, 1(1): p. 55-66.2005.
3. Nir, T.M., et al., Effectiveness of regional DTI measures in distinguishing Alzheimer's disease, MCI, and normal aging. NeuroImage: Clinical, 3(0): p. 180-195. 2013.
4. Zhan, L., et al., Angular versus spatial resolution trade-offs for diffusion imaging under time constraints. Human Brain Mapping. doi:10.1002/hbm.22094. Epub 2012 Apr 21.
5. Oishi, K., et al., Atlas-based whole brain white matter analysis using large deformation diffeomorphic metric mapping: application to normal elderly and Alzheimer's disease participants. Neuroimage, 46(2): p. 486-99.2009.
6. Zhang, Y., et al., Atlas-guided tract reconstruction for automated and comprehensive examination of the white matter anatomy. Neuroimage, 52(4): p. 1289-301. 2010.
7. Aganj, I., et al., A Hough transform global probabilistic approach to multiple-subject diffusion MRI tractography. Med Image Anal, 15(4): p. 414-25.2011.
8. Desikan, R.S., et al., An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage, 31(3): p. 968-80. 2006.
9. Jahanshad, N., et al., Sex differences in the human connectome: 4-Tesla high angular resolution diffusion imaging (HARDI) tractography in 234 young adult twins in ISBI. 2011: Chicago, IL. p. 939-943.
10. Jahanshad, N., et al., Boosting Power to Associate Brain Connectivity Measures and Dementia Severity using Seemingly Unrelated Regressions (SUR). Neurobiology of Aging - Special Issue on Novel Imaging Biomarkers for Alzheimer's Disease and Related Disorders. In submission.