Difference between revisions of "Projects:DTI DWI QualityControl"

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= Description =
 
= Description =
  
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[[Image:Screenshot.png|200px|thumb|left|alt Diffusion Weighted Imaging and Diffusion Tensor Imaging Quality Control_DTIPrep]]
  
 
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|3D view of gradients before and after Quality Control procedures
[[Image:753361684_3.png|3D view of gradients before and after Quality Control procedures
 
  
 
= Publications =
 
= Publications =

Revision as of 19:22, 30 May 2011

Home < Projects:DTI DWI QualityControl
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Diffusion Tensor and Diffusion Weighted Imaging Quality Control

DWI data suffers from inherent low SNR, overall long scanning time of multiple directional encoding with correspondingly large risk to encounter several kinds of artifacts. These artifacts can be too severe for a correct and stable estimation of the diffusion tensor. Thus, a quality control (QC) procedure is absolutely necessary for DTI studies. We are developing a framework for automatic DWI and DTI quality assessment and correction. We developed a tool called DTIPrep which pipelines the QC steps with designated protocol use and report generation.

Description

alt Diffusion Weighted Imaging and Diffusion Tensor Imaging Quality Control_DTIPrep

753361684 3.png |3D view of gradients before and after Quality Control procedures

Publications

Key Investigators

  • UNC Algorithms: Mahshid Farzinfar, Zhexing Liu, Martin Styner, Clement Vachet
  • Utah Algorithms: Tom Fletcher, Ross Whitaker, Guido Gerig, Sylvain Gouttard

Links