Difference between revisions of "Projects:RegistrationLibrary:RegLib C20"

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===Download ===
 
===Download ===
*[[Media:RegLib_C20_Data.zip‎‎|'''RegLib C20 example data set; incl. solutions <small> (zip file 116 MB) </small>]]
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*[[Media:RegLib_C20_Data.zip‎‎|'''RegLib C20 example data set; incl. solutions <small> (zip file 86 MB) </small>]]
 
 
  
 
=== Procedures===
 
=== Procedures===

Revision as of 22:06, 8 June 2012

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updated for v4.1 Slicer4 RegLibLogo.png
Slicer Registration Library Case #20: Intra-subject whole-body PET-CT

Input

this is the fixed PET/CT 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
fixed image/target moving image

Versions

For the Slicer 3.6 version of this case see here

Modules

Objective / Background

Change assessment.

Keywords

PET-CT, whole-body, change assessment

Input Data

  • reference/fixed : baseline CT: 0.98 x 0.98 x 5 mm , 512 x 512 x 149; PET: 4.1 x 4.1 x 5 mm , 168 x 168 x 149
  • moving: CT: 0.98 x 0.98 x 5 mm , 512 x 512 x 149; PET: 4.1 x 4.1 x 5 mm , 168 x 168 x 149

Download

Procedures

  • Phase 1: Load & Display
  1. drag & drop (or load via File menu): CT_1, CT_2, PET_1, PET_2
    1. in the load Dialog, select Show Options and for each volume, select Center.
    2. click OK
  2. go to Volumes module
    1. Active Volume: PET_1
    2. in the Display tab, click on the PET icon for window & level preset
    3. ditto for PET_2
  3. place CT_1 in background and PET_1 in foreground an pan between. You should see them aligned.
  • Phase 2: Co-register CT
  1. open the General Registration (BRAINS) module
    1. Fixed Image Volume: CT_1
    2. Moving Image Volume: CT_2
    3. Output Settings:
      1. Slicer BSpline Transform": create new & rename: "Xf2_CT21"
      2. Slicer Linear Transform: none
      3. Output Image Volume: create new & rename: "CT_2_Xf2"
    4. Regstration Phases: check boxes for Rigid, "Rigid+Scale" , Affine and "BSpline"
    5. Main Parameters:
      1. Number Of Samples: 400,000
      2. B-Spline Grid Size: 11,11,7
    6. Leave all other settings at default
    7. click: Apply; runtime ~ 5 min (MacPro QuadCore 2.4GHz) for faster performance, reduce sample points to 200,000
  • Phase 3: Resample PET
  1. open the BRAINSResample module (Registration menu)
    1. Image To Warp: PET_2
    2. Reference Image: PET_1
    3. Output Image: create new & rename: "PET_2_Xf2"
    4. Warping Parameters
      1. Warp By Transform: Xf2_CT21 created in Phase 2 above
    5. leave rest at defaults
    6. Apply
  2. go to Volumes module
    1. Active Volume: PET_2_Xf2
    2. in the Display tab, click on the PET icon for window & level preset

Registration Results

rigidrigid
BSpline registration of full volumes. 11 x 11 x 7 gridBSpline registration of full volumes. 11 x 11 x 7 grid
PET overlay ; BSpline registration of full volumes. 11 x 11 x 7 gridPET overlay ; BSpline registration of full volumes. 11 x 11 x 7 grid grid overlay showing BSpline deformation grid overlay showing BSpline deformation


Discussion: Registration Challenges

  • accuracy is the critical criterion here. We need the registration error (residual misalignment) to be smaller than the change we want to measure/detect. Agreement on what constitutes good alignment can therefore vary greatly.
  • because of the large FOV we have strong non-rigid deformations from differences in patient/limb positions etc.
  • images are large volumes (>100 MB total)
  • 2 images pairs have to be aligned, i.e. the calculated transform must be applied to the second (PET) image.

Discussion: Key Strategies

  • to calculate the transform, we use the images with the most accurate geometric representation and the smallest expected change, i.e. we align the follow-up CT to the baseline CT and then apply the transforms to the PET image.
  • because of the non-rigid differences due to posture and breathing we will need to apply a 2-step registration with an affine alignment followed by a BSpline.