Difference between revisions of "Algorithm:UNC:DTI:Noise Statistics"
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| + | Clinical time limitations on the acquisition of diffusion weighted volumes in DTI present several key challenges for quantiative statistics of diffusion tensors and tensor-derived measures. First, the signal to noise ratio (SNR) in each individual diffusion weighted volume is relatively low due to the need for quick acquisition. Secondly, the presence of Rician noise in MR imaging can introduce bias in the estimation of anisotropy and trace. Unlike structural MRI where intensities are primarily used to obtain contrast, the goal of DTI is to quantify the local diffusion properties in each voxel. Therefore, an understanding of the influence of imaging noise on the distribution of measured values is important to understand the results of statistical analysis and to design new imaging protocols. | ||
| − | + | =Publications= | |
| + | *Casey Goodlett, P. Thomas Fletcher, Weili Lin, and Guido Gerig. Noise-induced bias in low-direction diffusion tensor MRI: Replication of Monte-Carlo simulation with in-vivo scans. Accepted ISMRM 2007. | ||
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Latest revision as of 16:36, 3 April 2007
Home < Algorithm:UNC:DTI:Noise StatisticsDescription
Clinical time limitations on the acquisition of diffusion weighted volumes in DTI present several key challenges for quantiative statistics of diffusion tensors and tensor-derived measures. First, the signal to noise ratio (SNR) in each individual diffusion weighted volume is relatively low due to the need for quick acquisition. Secondly, the presence of Rician noise in MR imaging can introduce bias in the estimation of anisotropy and trace. Unlike structural MRI where intensities are primarily used to obtain contrast, the goal of DTI is to quantify the local diffusion properties in each voxel. Therefore, an understanding of the influence of imaging noise on the distribution of measured values is important to understand the results of statistical analysis and to design new imaging protocols.
Publications
- Casey Goodlett, P. Thomas Fletcher, Weili Lin, and Guido Gerig. Noise-induced bias in low-direction diffusion tensor MRI: Replication of Monte-Carlo simulation with in-vivo scans. Accepted ISMRM 2007.
