Abstract #3213

Comparison of Image Quality Control Tools for Diffusion Tensor Images

Bilan Liu¹, Tong Zhu², Jianhui Zhong²

¹Electrical and Computer Engineering , University of Rochester , Rochester , NY, United States; ²Imaging Sciences, University of Rochester, Rochester, NY, United States

Diffusion tensor imaging (DTI) is susceptible to numerous artifacts. Therefore the Quality control (QC) of the Diffusion tensor images is critical for image interpretation and diagnostic accuracy. The goal of this study is to develop an experimental protocol to help choose between existing QC tools by analyzing the precision and accuracy of fractional anisotropy (FA), mean diffusivity (MD) calculated by those tools in the presence of major DTI-specific artifacts. Both simulation data obtained using Monte Carlo simulation and human in vivo data were used to help assess the effectiveness of those QC tools.