Publication Type |
pre-print |
School or College |
<blank> |
Department |
<blank> |
Creator |
Gerig, Guido |
Other Author |
Sadeghi, Neda, Prastawa, Marcel W.; Fletcher, P. Thomas; Vachet, Clement; Wang, Bo.; Gilmore, John |
Title |
Multivariate Modeling of longitudinal MRI in early brain development with confidence measures |
Date |
2013-01-01 |
Description |
The human brain undergoes rapid organization and structuring early in life. Longitudinal imaging enables the study of these changes over a developmental period within individuals through estimation of population growth trajectory and its variability. In this paper, we focus on maturation of white and gray matter depicted in structural and diffusion MRI of healthy subjects with repeated scans. We provide a framework for joint analysis of both structural MRI and DTI (Diffusion Tensor Imaging) using multivariate nonlinear mixed effect modeling of temporal changes. Our framework constructs normative growth models for all the modalities, taking into account the correlation among the modalities and individuals, along with estimation of the variability of the population trends. We apply our method to study early brain development, and to our knowledge this is the first multimodel longitudinal modeling of diffusion and signal intensity changes for this growth stage. Results show the potential of our framework to study growth trajectories, as well as neurodevelopmental disorders through comparison against the constructed normative models of multimodal 4D MRI. |
Type |
Text |
Publisher |
Institute of Electrical and Electronics Engineers (IEEE) |
First Page |
1400 |
Last Page |
1403 |
Language |
eng |
Bibliographic Citation |
Sadeghi, N., Prastawa, M. W., Fletcher, P. T., Vachet, C., Wang, Bo., Gilmore, J., & Gerig, G. (2013). Multivariate Modeling of longitudinal MRI in early brain development with confidence measures. Proceedings of the 2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI), 1400-03. |
Rights Management |
(c) 2013 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 |
1,747,871 bytes |
Identifier |
uspace,19001 |
ARK |
ark:/87278/s6545xqx |
Setname |
ir_uspace |
ID |
712710 |
Reference URL |
https://collections.lib.utah.edu/ark:/87278/s6545xqx |