Difference between revisions of "Projects:RegistrationLibrary:RegLib C02"
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==Slicer Registration Use Case Exampe: Intra-subject Brain MR FLAIR to MR T1== | ==Slicer Registration Use Case Exampe: Intra-subject Brain MR FLAIR to MR T1== | ||
{| style="color:#bbbbbb; background-color:#333333;" cellpadding="10" cellspacing="0" border="0" | {| style="color:#bbbbbb; background-color:#333333;" cellpadding="10" cellspacing="0" border="0" | ||
| − | |[[Image:RegUC_thumb_T1_SPGR_sag.png|150px|lleft|reference]] | + | |[[Image:RegUC_thumb_T1_SPGR_sag.png|150px|lleft|this is the fixed reference image. All images are aligned into this space]] |
|[[Image:Arrow_left_gray.jpg|100px|lleft]] | |[[Image:Arrow_left_gray.jpg|100px|lleft]] | ||
| − | |[[Image:RegUC_thumb_FLAIR_sag.png|150px|lleft|moving]] | + | |[[Image:RegUC_thumb_FLAIR_sag.png|150px|lleft|this is the moving image. The transform is calculated by matching this to the reference image]] |
| − | |[[Image:RegUC_thumb_FLAIR_sag_labelmap.jpg|150px|lleft| | + | |[[Image:RegUC_thumb_FLAIR_sag_labelmap.jpg|150px|lleft|this is a passive image to which the calculated transform is applied. It is a label-map in the same space as the moving FLAIR image]] |
|- | |- | ||
|[[Image:Button_red_fixed.jpg|40px|lleft]] T1 SPGR | |[[Image:Button_red_fixed.jpg|40px|lleft]] T1 SPGR | ||
Revision as of 17:23, 20 October 2009
Home < Projects:RegistrationLibrary:RegLib C02Contents
Slicer Registration Use Case Exampe: Intra-subject Brain MR FLAIR to MR T1
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 T1 SPGR
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 T2 FLAIR
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 LABEL-MAP
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| 1mm isotropic | 1.2mm isotropic | 1.2mm isotropic |
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, labelmap, segmentation
Input Data
- reference: T1 SPGR , 1x1x1 mm voxel size, sagittal, RAS orientation
- moving: T2 FLAIR 1.2x1.2x1.2 mm voxel size, sagittal, RAS orientation
- quick view JPEG of a lighbox. Does your data look like this?
- download dataset to load into slicer
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
- 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
Registration 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)
