BUG: Jacobian determinants incorrect for non-identity direction matrices#1887
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BUG: Jacobian determinants incorrect for non-identity direction matrices#1887
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From cross-referencing with itkDisplacementFieldTransform, I believe the following issues were causing problems: 1. The displacement vectors were transformed by the direction matrix, but they are already in physical space 2. The jacobian matrix was transposed 3. A rotation was done to the final matrix to rebase to physical space, but I don't think that's right, ITK does a transform of the partial derivatives My tests for all this is can integration over the jacobians in the fixed space accurately predict the expansion / contraction of a label image, across multiple configurations of the image direction matrix. The "geometric" option for CreateJacobianDeterminantImage consistently has slightly larger prediction errors, but didn't have any of the massive discrepencies with non-identity direction matrices.
Removed some features because only one set of options are used in CreateJacobianDeterminantImage, and I don't have time to validate them all
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Tested on brain data https://upenn.box.com/s/xj5u142w1n634aob831o4f3pbi71yuds I'm convinced now that this fix is necessary for correct determinants on non-axial data. |
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Discussed in #1884
I added more examples with synthetic data at
https://github.com/cookpa/antsJacobianExample
I think the Jacobian matrix as well as the determinant were not properly computed in physical space. For some cases, these errors could cancel out leading to results that appear correct.
I've simplified the ANTs Jacobian filter to behave more like the itkDisplacementFieldTransform method, which works consistently well across different image orientations.
I would really like some validation on external real data, but don't have time to pursue that for a couple of weeks at least. Opening a draft PR for feedback