DTI quality control assessment via error estimation from monte carlo simulations

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Publication Type pre-print
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Creator Gerig, Guido
Other Author Farzinfar, Mahshid; Li, Yin; Verde, Audrey R.; Oguz, Ipek; Styner, Martin A.
Title DTI quality control assessment via error estimation from monte carlo simulations
Date 2013-01-01
Description Diffusion Tensor Imaging (DTI) is currently the state of the art method for characterizing the microscopic tissue structure of white matter in normal or diseased brain in vivo. DTI is estimated from a series of Diffusion Weighted Imaging (DWI) volumes. DWIs suffer from a number of artifacts which mandate stringent Quality Control (QC) schemes to eliminate lower quality images for optimal tensor estimation. Conventionally, QC procedures exclude artifact-affected DWIs from subsequent computations leading to a cleaned, reduced set of DWIs, called DWI-QC. Often, a rejection threshold is heuristically/empirically chosen above which the entire DWI-QC data is rendered unacceptable and thus no DTI is computed. In this work, we have devised a more sophisticated, Monte-Carlo (MC) simulation based method for the assessment of resulting tensor properties. This allows for a consistent, error-based threshold definition in order to reject/accept the DWI-QC data. Specifically, we propose the estimation of two error metrics related to directional distribution bias of Fractional Anisotropy (FA) and the Principal Direction (PD). The bias is modeled from the DWI-QC gradient information and a Rician noise model incorporating the loss of signal due to the DWI exclusions. Our simulations further show that the estimated bias can be substantially different with respect to magnitude and directional distribution depending on the degree of spatial clustering of the excluded DWIs. Thus, determination of diffusion properties with minimal error requires an evenly distributed sampling of the gradient directions before and after QC.
Type Text
Publisher International Society for Optical Engineering (SPIE)
Volume 8669
First Page 86692C-1
Last Page 86692C-8
Language eng
Bibliographic Citation Farzinfar, M., Li, Y., Verde, A. R., Oguz, I., Gerig, G., & Styner, M. A. (2013). DTI quality control assessment via error estimation from monte carlo simulations. Proceedings of SPIE, 8669, 86692C-1-86692C-8.
Rights Management (c)Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic electronic or print reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. http://dx.doi.org/doi: 10.1117/12.2006925.
Format Medium application/pdf
Format Extent 2,062,789 bytes
Identifier uspace,18995
ARK ark:/87278/s6642zv9
Setname ir_uspace
Date Created 2014-10-17
Date Modified 2021-05-06
ID 712702
Reference URL https://collections.lib.utah.edu/ark:/87278/s6642zv9
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