Projects:RegistrationLibrary:RegLib C13

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v3.6.3these cases are not yet registered / under developmentSlicer Registration Library Case #13: Liver Tumor Cryoablation 2

Input

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 the moving image. The transform is calculated by matching this to the reference image this is the moving image. The transform is calculated by matching this to the reference image
fixed image/target moving image moving image moving image

Objective / Background

We seek to align the pre-operative CT&MRI with the post-operative CT.

Keywords

MRI, CT, IGT, intra-operative, liver, cryoablation, change detection, non-rigid registration

Input Data

  • reference/fixed : 0.57 x 0.57 x 5 , 512 x 512 x 37 voxels
  • moving: 0.57 x 0.57 x 5 mm, 512 x 512 x 33 voxels
  • moving: 1.56 x 1.56 x 2.5 mm, 256 x 256 x 88
  • moving: 1.56 x 1.56 x 6 mm, 256 x 256 x 36

Registration Results

This case is currently unsolved with standard Slicer 3.6 technology. Special/custom modifications to registration modules (SlicerIGT Registration) are under way and will be incorporated into future releases. Also expected upgrades to ITK4 present in Slicer4 will likely improve performance.

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Procedure

  • Phase I: register CTpre - CTpost
  1. open the General Registration (BRAINS) module
    1. Fixed Image Volume: CTpost
    2. Moving Image Volume: CTpre
    3. Output Settings:
      1. Slicer BSpline Transform": create new transform, rename to "Xf1_Ctpre-CTpost_BSpline"
      2. Slicer Linear Transform: none
      3. Output Image Volume: create new volume, rename to "CTpre_Xf1"
    4. Registration Phases: check boxes for Rigid , Rigid+Scale , Affine and "BSpline"
    5. Main Parameters:
      1. B-Spline Grid Size: 7,7,3
    6. Leave all other settings at default
    7. click: Apply; runtime ~ 1 min (MacPro QuadCore 2.4GHz)


Discussion: Registration Challenges

  • large differences in FOV
  • strong differences in image contrast between MRI & CT
  • contrast enhancement and pathology and treatment changes cause additional differences in image content
  • we have strongly anisotropic voxel sizes with much less through-plane resolution