Difference between revisions of "Projects:RegistrationLibrary:RegLib C27"

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=== Discussion: Key Strategies ===
 
=== Discussion: Key Strategies ===
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*the two images have identical contrast, hence we could consider "sharper" cost functions, such as NormCorr or MeanSqrd. But because of the strong distortions and lower resolution of the moving image, Mutual Information is recommended as the most robust metric.
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*because the pathology appears similar in the FLAIR as in the DTI baseline, we choose the FLAIR as reference
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*often anatomical labels are available from the reference scan. It would be less work to align the anatomical reference with the DTI, since that would circumvent having to resample the complex tensor data into a new orientation. However the strong distortions are better addressed by registering the other direction, i.e. move the DTI into the anatomical reference space.
 
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*because we seek to assess/quantify regional size change, we must use a rigid (6DOF) scheme, i.e. we must exclude scaling.
 
 
*masking is likely necessary to obtain good results.  
 
*masking is likely necessary to obtain good results.  
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*in this example the initial alignment of the two scans is very poor. The strongly oblique orientation of the DTI makes an initial manual alignment step necessary.
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*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
 
*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%.
 
*because speed is not that critical, we increase the sampling rate from the default 2% to 15%.
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*we also expect larger differences in scale & distortion than with regular structural scane: so we significantly  (2x-3x) increase the expected values for scale and skew from the defaults.
 
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*a good affine alignment is important before proceeding to non-rigid alignment to further correct for distortions.
 
  
 
=== Acknowledgments ===
 
=== Acknowledgments ===

Revision as of 14:28, 20 May 2010

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Slicer Registration Library Exampe #27: Diffusion Weighted Image Volume: align with structural reference MRI

this is the fixed reference image. All images are aligned into this space this is an alternative reference image, aligned with FLAIR lleft this is the moving image. The transform is calculated by matching this to the reference image this is a passive image to which the calculated transform is applied. It is a tensor-map (DTI) in the same orientation as the moving baseline image LEGEND

lleft this indicates the reference image that is fixed and does not move. All other images are aligned into this space and resolution
lleft this indicates the moving image that determines the registration transform.
lleft this indicates images that passively move into the reference space, i.e. they have the transform applied but do not contribute to the calculation of the transform.

lleft T2 FLAIR lleft T1 post-contrast lleft DTI Baseline lleft DTI volume
0.45 x 0.45 x 3.9 mm axial
448 x 512 x 30
RAS 		0.98 x 0.98 x 1 mm axial
192 x 256 x 176
RAS 		1.96 x 1.96 x 3 mm
axial
128 x 128 x 40
RAS 		1.96 x 1.96 x 3 mm
axial
128 x 128 x 40
RAS

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

  • Button red fixed white.jpgreference/fixed : FLAIR axial, 0.4mm resolution in plane, 4mm slices
  • Button green moving white.jpg moving: Baseline image of acquired DTI volume, corresponds to T2w MRI , 1.96 x 1.96 x 3 mm voxel size, oblique
  • Button blue tag white.jpg tag: 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

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 cortex that might affect the registration if its contrast is different in 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%.

Acknowledgments

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