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I am working on a project looking at changes over time in both white and grey matter in aging and neurodegeneration.
the available diffusion data have been acquired with low b-values (b values: 0; 1000; 64 directions; no blip-up/blip-down design) on a SIEMENS Trio scanner. Currently I have analyzed the data following a standard DTI pipeline (FSL + DTITK) and focused on white matter. I have to questions:
Regarding the analysis in white matter: would it make sense to use MRtrix3Tissue + FBA pipeline to generate fibre cross-section and (maybe) fiber density metrics with these data? I think I would focus more to FC but I am not sure how accurate the metric could be in this context (i.e., low b values).
Regarding the analysis in gray matter: I would like to perform an analysis similar to the one performed in Kelly et al 2022, Neuroimage (very nice paper!). I am in particular referring to use the tissue microstructural and free-water composition metrics. However, I am not sure to what extent my data would provide an adequate input for such approach.
Any consideration and suggestion would be very much appreciated!
All the best,
Nicola
The text was updated successfully, but these errors were encountered:
Dear experts,
I am working on a project looking at changes over time in both white and grey matter in aging and neurodegeneration.
the available diffusion data have been acquired with low b-values (b values: 0; 1000; 64 directions; no blip-up/blip-down design) on a SIEMENS Trio scanner. Currently I have analyzed the data following a standard DTI pipeline (FSL + DTITK) and focused on white matter. I have to questions:
Any consideration and suggestion would be very much appreciated!
All the best,
Nicola
The text was updated successfully, but these errors were encountered: