Difference between revisions of "Projects:DTINoiseStatistics"
| Line 3: | Line 3: | ||
Back to [[NA-MIC_Collaborations|NA-MIC_Collaborations]], [[Algorithm:UNC|UNC Algorithms]] | Back to [[NA-MIC_Collaborations|NA-MIC_Collaborations]], [[Algorithm:UNC|UNC Algorithms]] | ||
| − | ''' | + | '''Objectives''' |
Clinical time limitations on the acquisition of diffusion weighted volumes in DTI present several key challenges for quantitative 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. | Clinical time limitations on the acquisition of diffusion weighted volumes in DTI present several key challenges for quantitative 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. | ||
Revision as of 14:23, 4 September 2007
Home < Projects:DTINoiseStatisticsDTI Noise Statistics
Back to NA-MIC_Collaborations, UNC Algorithms
Objectives
Clinical time limitations on the acquisition of diffusion weighted volumes in DTI present several key challenges for quantitative 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.
Progress
References
Key Investigators
Links
Project Week Results: Jan 2006, Jun 2006, Jan 2007
