Added two commands to ImageMath:

FSLTensorToITK <input 4D tensor>
ITKTensorToFSL <input 3D tensor>

FSL requires radiological orientation of bvecs / tensors, regardless
of image orientation. This causes a problem for "NEUROLOGICAL" images
(positive determinant of direction matrix), because the tensors are then
not transformed to physical space by the direction matrix.

On import, we fix this by applying a reflection in x, and we do the same
on export back to FSL tensor format.

I think this PR may fix a longstanding issue #1137 - different behavior of ReorientTensorImage when given affine vs displacement fields. A few others have brought up similar issues, eg #1461.

I think the divergence between affine / displacement fields were that the affine transform was being corrected for the direction matrix, but the displacement field transform was not. I was confused by the GetLocalDeformation function, which does apply the image direction - this function was called in the filter, but then the results were not used. So in the end, displacement field reorientation was being applied to tensors still in the voxel orientation.

In this PR, I've tried to simplify things by rebasing the tensors to physical space (rather than modifying the transform), then applying the reorientation as before, then rebasing back to voxel space for output.

In short: reorientation with a displacement field was incorrect if the fixed image (into which the tensors are resampled by antsApplyTransforms) has a non-identity transform. The resampling itself is not affected; so tensor FA, MD etc are correct.

I think this is close to ready. There's still a systematic difference between mat and warp that is bigger than I'd like

this is "yawToYawRotated" in https://github.com/cookpa/antsDTOrientationTests.

The offset might be because the warp field is sampled coarsely (3mm). I'll investigate further.

Despite this, the major errors look to be resolved. I don't know how I didn't see these before. Lots of layers of confusion including the radiological / neurological display thing, and changing basis of the tensors (before #678), and limited scope of the bug. The three conditions for wrong results are:

1. There's a physical space rotation
2. The transform is a displacement field
3. The fixed image has a non-identity direction matrix.

Merely rebasing the tensors into another image space with antsApplyTransforms was fine after #678.

I did some more digging, example scripts here

https://github.com/cookpa/itkTensorReorientation

The Jacobian estimation in the displacement field transform systematically underestimates rotation if the angle is large. When tested using rotations converted with TransformToDisplacementField, the estimated rotation is pretty good in the range 0-15 degrees, but by 30 degrees, it is consistently 5-6 degrees off.

I'm going to update the code to use a composite transform - this way large rigid rotations can be more accurately preserved.