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  1. Image Analysis
  2. Image QC
  3. Raw Data QC

T1/T2 QC

Last updated 10 months ago

For QCing structural images, we use a method developed by Dr. Lea Backhausen and her team at the University of Dresden. This method relies on assessing three features of structural images: image sharpness, ringing, contrast-to-noise ratio. Each of these features is classified on a three-level scale, similar in principle to assessing the level of ghosting in diffusion data.

This process is thoroughly documented by Dr. Backhausen and her team in this PDF.

After you have assessed each structural image, your QC notes should be documented in the appropriate module:

Note that this module outputs a final single number to indicate whether an image has passed QC or not, or whether further examination is necessary.

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676KB
Backhausen_Struc_QC.PDF
pdf