Comments (4)
noticed that the prediction result from the registration model is the inverse, i.e. from fixed to moving.
Can you expand on what this mean? The deformation field has to be in the space of the fixed image indeed, because it has to pull the moving image to that space.
perhaps I am misunderstand what you mean, though
We also work with diffeomorphisms in certain models, and computing the inverse field is trivial in that scenario. A bit harder, but still possible. otherwise. Can you tell us exactly which model you are using?
pinging the HyperMorph author @ahoopes , but I know he's quite busy until the CVPR deadline :)
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thanks for the quick reply!
I am using the standard hypermorph model and not constraining it to be diffeomorphic.
I want to visualize how the points in the moving image are "pushed" towards the fixed image, this is why i am looking for the inverse.
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Okay, I wrote a quick (not well tested) tutorial here: https://colab.research.google.com/drive/1juAJRYhPPDNbO9yRtlc0VGhbIFSuhpJ2?usp=sharing
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Ah perfect, thanks a lot!! :)
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Related Issues (20)
- About the generation process of flow field/displacement field HOT 2
- affine transform from voxelmorph not compatible with ITK affine transform HOT 1
- SynthMorph shapes demo - change of loss functions HOT 3
- Need a tutorial for my own image HOT 6
- Train my own Voxelmorph model to align 3D images to mni152
- pytorch pre-train file HOT 8
- Any training tutorials? HOT 4
- Register cropped image to non-cropped image HOT 1
- Registration on large FOV difference cases: HOT 3
- Resulting VoxelMorph Atlas is Blurry and Lacks Detail HOT 6
- VoxelMorph Atlas is just a slightly blurred version of the fixed image HOT 23
- Mouse Brain Registration (rsfmri - MRI - T2w)
- Running configuration for other brain datasets with non-standard sizes
- The application of synthmorph to the problem of large deformation of lungs in ct-cbct HOT 1
- huge loss HOT 2
- How to specify input/output pairs in /images/list.txt for model training HOT 2
- How to apply the affine matrix from SynthMorph HOT 5
- How to deform annotated landmarks with the predict dense deformation field in the pytorch version
- Torch train.py problem HOT 2
- L smooth Loss not decreasing
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