Voxel-wise group analysis of DTI

Update Item Information
Publication Type pre-print
School or College <blank>
Department <blank>
Creator Gerig, Guido
Other Author Liu, Zhexing; Zhu, Hongtu; Marks, Bonita L.; Katz, Laurence M.; Goodlett, Casey B.; Styner, Martin
Title Voxel-wise group analysis of DTI
Date 2009-01-01
Description Diffusion tensor MRI (DTI) is now a widely used modality to investigate the fiber tissues in vivo, especially the white matter in brain. An automatic pipeline is described in this paper to conduct a localized voxel-wise multiple-subject group comparison study of DTI. The pipeline consists of 3 steps: 1) Preprocessing, including image format converting, image quality check, eddy-current and motion artifact correction, skull stripping and tensor image estimation, 2) study-specific unbiased DTI atlas computation via affine followed by fluid nonlinear registration and warping of all individual DTI images into the common atlas space to achieve voxel-wise correspondence, 3) voxel-wise statistical analysis via heterogeneous linear regression and wild bootstrap technique for correcting for multiple comparisons. This pipeline was applied to process data from a fitness and aging study and preliminary results are presented. The results show that this fully automatic pipeline is suitable for voxel-wise group DTI analysis.
Type Text
Publisher Institute of Electrical and Electronics Engineers (IEEE)
First Page 807
Last Page 810
Language eng
Bibliographic Citation Liu, Z., Zhu, H., Marks, B. L., Katz, L. M., Goodlett, C. B., Gerig, G., & Styner, M. (2009). Voxel-wise group analysis of DTI. Proceedings of the IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 807-10.
Rights Management (c) 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Format Medium application/pdf
Format Extent 344,582 bytes
Identifier uspace,19221
ARK ark:/87278/s69d06j3
Setname ir_uspace
ID 712794
Reference URL https://collections.lib.utah.edu/ark:/87278/s69d06j3
Back to Search Results