Hi Alexa,
I have not seen anyone reply to your post so let me have a stab.
In short, there is no universally accepted approach. Some have tried
establishing such a system (see, for example, Mortamet B, Bernstein MA,
Jack CR, Gunter JL, Ward C, Britson PJ, Meuli R, Thiran JP, Krueger G,
Alzheimer's Disease Neuroimaging Initiative, 2009. Automatic quality
assessment in structural brain magnetic resonance imaging. Magn Reson
Med 62: 365-372 and the references therein) but this has not taken hold
yet. Others have rated all images according to a more or less subjective
system (e.g., Wilke et al., HBM 2002). You could also include such a
rating in ensuing statistical analyses. Further, Christian Gaser's vbm
toolbox allows you to check sample homogeneity (or lack thereof :),
enabling you to identify scans that deviate most from the sample mean.
I hope this gives you some pointers.
Cheers,
Marko
Alexa Huber wrote:
> Dear all,
>
> I am doing my first VBM analysis to assess gray matter volume in patients compared to a control group. The quality of my T1 images varies, e.g. due to eye/head movement artefacts. As the patients tend to move more during the scan, compared to the controls, I am worried that image quality may influence my VBM results as a confound, and I would like to include an index of image quality as a regressor in my statistical group analysis to avoid this.
>
> Has anyone heard of a method or function to automatically estimate the quality of a T1 image?
>
> Many thanks for any help,
>
> Alexa
>
--
____________________________________________________
PD Dr. med. Marko Wilke
Facharzt für Kinder- und Jugendmedizin
Leiter, Experimentelle Pädiatrische Neurobildgebung
Universitäts-Kinderklinik
Abt. III (Neuropädiatrie)
Marko Wilke, MD, PhD
Pediatrician
Head, Experimental Pediatric Neuroimaging
University Children's Hospital
Dept. III (Pediatric Neurology)
Hoppe-Seyler-Str. 1
D - 72076 Tübingen, Germany
Tel. +49 7071 29-83416
Fax +49 7071 29-5473
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