Thank you for you reply. I had two more questions:
- For DTI modeling, the different b-values would be a problem (besides the perfusion effect)? As I only processed shell-like DWI data using FSL, and when fitting DTI model, I was told to use only the data with one b-value. For instance, when there two b-values like 1000 and 2000, use the b=1000 data for DTI fitting.
- The current dataset is suitable for tractography and connectivity analysis? For shell-like DWI data, I was told that at least 20 directions were needed using FSL’s bedpostx. For the current dataset, the b-value is generally low and each b-value corresponds to a different direction. I had a very very brief understanding of the physical and mathematical principles underlying DWI data modeling, but I had a feeling that this kind of data may have a bias related to anisotropy, because in each direction the sampling is different. This concern for anisotropy also relates to DTI modeling.