Hi DIPY Experts,
I had a few questions regarding the Manjon localpca implementation using DIPY.
1) In the case of multiple b=0 volumes, is the noise estimated from just the b=0 volumes? In the case of only one b=0 volume is the noise then estimated from the diffusion weighted images instead?
2) Are the images registered using an affine transform so that the images are roughly aligned prior to noise estimation and localPCA? If so, are the affine transforms just stored as part of the header and not applied to create a new image in order to preserve the uncorrelated nature of the noise?
3) Some data such as those from GE scanners sometimes upsample the data during reconstruction. If this is true, then the assumption of spatial independence of noise is not held true and when running the localPCA (Matlab version) the results did not look much more different than the inputs. In this situation, is there another denoising technique you recommend that could handle this situation?
Thanks,
Ajay