Difference between revisions of "Projects:RegistrationLibrary:RegLib C02"
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*we know the underlying structure/anatomy did not change, hence whatever residual misalignment remains is of technical origin. | *we know the underlying structure/anatomy did not change, hence whatever residual misalignment remains is of technical origin. | ||
*the different series may have different FOV. The additional image data may distract the algorithm and require masking | *the different series may have different FOV. The additional image data may distract the algorithm and require masking | ||
− | *the different series may have different contrast. | + | *the different series may have very different resolution and anisotropic voxel sizes |
+ | *hi-resolution datasets may have defacing applied to one or both sets, and the defacing-masks may not be available | ||
+ | that*the different series may have different contrast. | ||
*individual series may contain motion or other artifacts | *individual series may contain motion or other artifacts | ||
Revision as of 15:52, 20 October 2009
Home < Projects:RegistrationLibrary:RegLib C02Contents
Slicer Registration Use Case Exampe: Intra-subject Brain MR FLAIR to MR T1
Objective / Background
This scenario occurs in many forms whenever we wish to align all the series from a single MRI exam/session into a common space. Alignment is necessary because the subject likely has moved in between series.
Keywords
MRI, brain, head, intra-subject, FLAIR, T1, defacing, masking
Input Data
Registration Challenges
- we expect the amount of misalignment to be small
- we know the underlying structure/anatomy did not change, hence whatever residual misalignment remains is of technical origin.
- the different series may have different FOV. The additional image data may distract the algorithm and require masking
- the different series may have very different resolution and anisotropic voxel sizes
- hi-resolution datasets may have defacing applied to one or both sets, and the defacing-masks may not be available
that*the different series may have different contrast.
- individual series may contain motion or other artifacts
Procedure
- step-by step text instruction
- recommended parameter settings
- guided video tutorial
- power point tutorial
Results
- registration parameter presets file (load into slicer and run the registration)
- result transform file (load into slicer and apply to the target volume)
- result screenshots (compare with your results)
- result evaluations (metrics)