Projects:RegistrationLibrary:RegLib C02

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Slicer Registration Use Case Exampe: Intra-subject Brain MR FLAIR to MR T1

this is the fixed reference image. All images are aligned into this space 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 label-map in the same space as the moving FLAIR image
lleft T1 SPGR lleft T2 FLAIR lleft LABEL-MAP
1mm isotropic
256 x 256 x 146
1.2mm isotropic
256 x 256 x 116
1.2mm isotropic
256 x 256 x 116

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

Media:Example.ogg===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
  • Content preview: SPGR Lighbox , FLAIR Lighbox Does your data look like this? SPGR Lighbox preview
  • 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)