I have a data set consists of single-shell diffusion data with bvals corresponding to 0 and 1000. After surveying the landscape, it seems that the following two methods might be viable for analyzing such data set:
Use dwi2response dhollander to estimate wm.txt, gm.txt, and csf.txt. Then use ss3t_csd_beta1 to generate the FOD images for the different tissue types.
Use dwi2response dhollander to estimate wm.txt, gm.txt, and csf.txt. Then use dwi2fod msmt_csd to generate the white matter and CSF FOD images.
Based on the ss3t website, it seems that ss3t_csd_beta1 works better on high bval conditions, but is also okay on bval at 1000. Meanwhile, msmt_csd seems to be a very robust approach, but given single shell data, it will generate only 2 FOD images instead of 3. Should I use ss3t_csd_beta1 or msmt_csd in this situation?