Difference between revisions of "Projects:RegistrationLibrary:RegLib C27"
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[[Projects:RegistrationDocumentation:UseCaseInventory|Back to Registration Use-case Inventory]] <br> | [[Projects:RegistrationDocumentation:UseCaseInventory|Back to Registration Use-case Inventory]] <br> | ||
| − | ==Slicer Registration Library Exampe #27: Diffusion Weighted Image Volume: align with structural reference MRI == | + | ==<small>v3.6.1</small> [[Image:Slicer3-6Announcement-v1.png|150px]] Slicer Registration Library Exampe #27: Diffusion Weighted Image Volume: align with structural reference MRI == |
| − | {| style="color:#bbbbbb | + | === Input === |
| − | |[[Image: | + | {| style="color:#bbbbbb; " cellpadding="10" cellspacing="0" border="0" |
| − | |[[Image: | + | |[[Image:RegLib27_T1c.pngl.png|150px|lleft|this is the fixed T2 reference image. All images are aligned into this space]] |
| − | |[[Image: | + | |[[Image:RegLib27_FLAIR.pngl.png|150px|lleft|this is the fixed T2 reference image. All images are aligned into this space]] |
| − | |[[Image:RegLib27_DTIbaseline.png|150px|lleft|this is the | + | |[[Image:RegArrow_NonRigid.png|100px|lleft]] |
| − | |[[Image:RegLib27_DTI.png|150px|lleft|this is | + | |[[Image:RegLib27_DTIbaseline.png|150px|lleft|this is the DTI Baseline scan, to be registered with the T2]] |
| − | + | |[[Image:RegLib27_DTI.png|150px|lleft|this is the DTI tensor image, in the same orientation as the DTI Baseline]] | |
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| − | | | + | |fixed image/target<br>T1 |
| − | + | |fixed image/target<br>FLAIR | |
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| − | | | + | |moving image 2a<br>DTI baseline |
| − | + | |moving image 2b<br>DTI tensor | |
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| + | === Modules === | ||
| + | *'''Slicer 3.6.1 recommended modules: [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BrainsFit]''' | ||
===Objective / Background === | ===Objective / Background === | ||
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===Input Data=== | ===Input Data=== | ||
| − | * | + | *reference/fixed : T1 axial, 0.98 x 0.98 x 1 , 192 x 256 x 176 |
| − | * | + | *reference/fixed : FLAIR axial, 0.4mm resolution in plane, 4mm slices, 448 x 512 x 30 |
| − | * | + | *moving: Baseline image of acquired DTI volume, corresponds to T2w MRI , 1.96 x 1.96 x 3 mm voxel size, oblique, 128 x 128 x 40 |
| + | *moving: Tensor data of DTI volume, oblique, same orientation as Baseline image. The result Xform will be applied to this volume. The original DWI has 64 directions, the extracted DTI volume has 9 scalars, i.e. 128 x 128 x 40 x 9 | ||
=== Registration Results=== | === Registration Results=== | ||
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[[Projects:RegistrationDocumentation:ParameterPresetsTutorial|Link to User Guide: How to Load/Save Registration Parameter Presets]] | [[Projects:RegistrationDocumentation:ParameterPresetsTutorial|Link to User Guide: How to Load/Save Registration Parameter Presets]] | ||
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=== Discussion: Registration Challenges === | === Discussion: Registration Challenges === | ||
*The DTI contains acquisition-related distortions (commonly EPI acquisitions) that can make automated registration difficult. | *The DTI contains acquisition-related distortions (commonly EPI acquisitions) that can make automated registration difficult. | ||
*the two images often have strong differences in voxel sizes and voxel anisotropy. If the orientation of the highest resolution is not the same in both images, finding a good match can be difficult. | *the two images often have strong differences in voxel sizes and voxel anisotropy. If the orientation of the highest resolution is not the same in both images, finding a good match can be difficult. | ||
| − | *there is widespread and extensive pathology in the right | + | *there is widespread and extensive pathology in the right hemisphere that might affect the registration if contrast is different between the baseline and structural reference scan. |
=== Discussion: Key Strategies === | === Discussion: Key Strategies === | ||
Revision as of 13:13, 22 September 2010
Home < Projects:RegistrationLibrary:RegLib C27Back to ARRA main page
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v3.6.1 
Slicer Registration Library Exampe #27: Diffusion Weighted Image Volume: align with structural reference MRI
Input
| this is the fixed T2 reference image. All images are aligned into this space | this is the fixed T2 reference image. All images are aligned into this space | 
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| fixed image/target T1 |
fixed image/target FLAIR |
moving image 2a DTI baseline |
moving image 2b DTI tensor |
Modules
- Slicer 3.6.1 recommended modules: BrainsFit
Objective / Background
This is a typical example of DTI processing. Goal is to align the DTI image with a structural scan that provides accuracte anatomical reference. The DTI contains acquisition-related distortion and insufficient contrast to discern anatomical detail. For treatment planning and evaluation, location of functionally critical fiber tracts relative to the pathology is sought.
Keywords
MRI, brain, head, intra-subject, DTI, DWI
Input Data
- reference/fixed : T1 axial, 0.98 x 0.98 x 1 , 192 x 256 x 176
- reference/fixed : FLAIR axial, 0.4mm resolution in plane, 4mm slices, 448 x 512 x 30
- moving: Baseline image of acquired DTI volume, corresponds to T2w MRI , 1.96 x 1.96 x 3 mm voxel size, oblique, 128 x 128 x 40
- moving: Tensor data of DTI volume, oblique, same orientation as Baseline image. The result Xform will be applied to this volume. The original DWI has 64 directions, the extracted DTI volume has 9 scalars, i.e. 128 x 128 x 40 x 9
Registration Results
Download
- download dataset (DTI estimate, baseline image FLAIR & T1) (NRRD files, zip file 15 MB)
- Presets
- Tutorial only
- Complete tutorial package
Link to User Guide: How to Load/Save Registration Parameter Presets
Discussion: Registration Challenges
- The DTI contains acquisition-related distortions (commonly EPI acquisitions) that can make automated registration difficult.
- the two images often have strong differences in voxel sizes and voxel anisotropy. If the orientation of the highest resolution is not the same in both images, finding a good match can be difficult.
- there is widespread and extensive pathology in the right hemisphere that might affect the registration if contrast is different between the baseline and structural reference scan.
Discussion: Key Strategies
- because the pathology appears similar in the FLAIR as in the DTI baseline, we choose the FLAIR as reference
- masking is likely necessary to obtain good results.
- in this example the initial alignment of the two scans is pretty good already. No initial affine alignment is needed.
- these two images are not too far apart initially, so we reduce the default of expected translational misalignment
- because speed is not that critical, we increase the sampling rate from the default 2% to 15%.
