All posts in category DTI

Dealing with transforms in AFNI (Part 1)

AFNI’s main tool for dealing with transforms is cat_matvec, but in many cases you may not need to use it!  Everyone knows that transform matrices are confusing — I’ll do a post later on just covering them — but for now, I think we can all agree that it’s a relief anytime you don’t have to […]

TORTOISE Processing of DWI/DTI (Part 2)

Last time, we covered how to use TORTOISE’s DIFF_PREP tool to preprocess Diffusion Weighted Images (DWI) to correct for eddy currents, motion, rotate the b-vectors (alongside the motion correction), and optionally correct b-splines if we used a T2-weighted structural image.  The next step is to use DIFF_CALC to fit tensors, inspect the results, measure ROIs, […]

TORTOISE Processing of DWI/DTI (Part 1)

These instructions are for an older version of TORTOISE, if you would like to read new instructions checkout the updated tutorial HERE! There are many options when deciding how to process Diffusion Weighted Images (DWI) and turn them into Diffusion Tensor Images (DTI).  I’ve written before about preprocessing in FSL (Part 1, Part 2) and AFNI (Part […]

Year 1 Reflection

I really started investing in this blog in November 2012.  In the first month it received 12 hits.  In the second month, it also received 12 hits.  But as we’ve added more content over the past year, the number of hits has continued to go up.  And I’m very happy that today, we celebrate more […]

Rotating bvecs for DTI fitting

Update: While these methods continue to be useful, I now recommend using TORTOISE for preprocessing DTI.  The TORTOISE pipeline includes methods for (among other things) reducing distortions from EPI artifacts, eddy current correction, correcting for motion, rotating b-vecs, and co-registration to an anatomical image.  There are instructions for using the newest version here.   Most […]