Difference between revisions of "Projects:RegistrationLibrary:RegLib C29"

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===Key Strategies===
 
===Key Strategies===
*'''Slicer 4 recommended modules:  [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BrainsFit]
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*'''Slicer 4 recommended modules:  [https://www.slicer.org/wiki/Modules:BRAINSFit BrainsFit]
 
*to align the DTI with the T1 we need 2 registration steps: 1.align the T2 with the T1 and 2. align the DTI with the T2. The DTI baseline scan has contrast most similar to the T2 and hence is best registered against the T2. However the structural reference scan with highest resolution and tissue contrast is the T1.
 
*to align the DTI with the T1 we need 2 registration steps: 1.align the T2 with the T1 and 2. align the DTI with the T2. The DTI baseline scan has contrast most similar to the T2 and hence is best registered against the T2. However the structural reference scan with highest resolution and tissue contrast is the T1.
 
*we therefore use the following approach: 1) we first co-register the T2 with the SPGR T1.  2) we register the DTI baseline to the  registered/resampled T2;  3) resample the DTI volume with the new transform
 
*we therefore use the following approach: 1) we first co-register the T2 with the SPGR T1.  2) we register the DTI baseline to the  registered/resampled T2;  3) resample the DTI volume with the new transform

Latest revision as of 17:40, 10 July 2017

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updated for v4.1 Slicer4 RegLibLogo.png
Slicer Registration Library Case #29: Intra-subject Brain DTI

Input

this is the fixed reference image. All images are aligned into this space lleft this is the T2 reference image, serves as target to the DTI baseline, but is itself aligned to the SPGR lleft this is the DTI Baseline scan, to be registered with the T2 this is the DTI tensor image, in the same orientation as the DTI Baseline
fixed image/target
T1 SPGR
moving image 1
T2
moving image 2a
DTI baseline
moving image 2b
DTI tensor

Slicer4 Modules used

Objective / Background

This is a classic case of a multi-sequence MRI exam we wish to spatially align to the anatomical reference scan (T1-SPGR). The scan of interest is the DTI image to be aligned for surgical planning/reference.

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Keywords

MRI, brain, head, intra-subject, DTI, T1, T2, non-rigid, tumor, surgical planning

Input Data

  • reference/fixed : T1 SPGR , 0.5x0.5x1 mm voxel size, 512 x 512 x 176
  • moving 1: T2 0.5x0.5x1.5 mm voxel size, 512 x 512 x 92
  • moving 2a: DTI baseline: 1 x 1 x 3 mm, 256 x 256 x 41
  • moving 2b: 1 x 1 x 3 mm, 256 x 256 x 41 x 9 (tensor), original: DWI 256 x 256 x 41 x 32 directions

Registration Challenges

  • The DWI sequence (EPI) contains strong distortions we seek to correct via non-rigid alignment
  • The DWI sequence also contains strong intensity inhomogeneity (coil bias)
  • the DTI baseline is similar in contrast to a T2, albeit at much lower resolution
  • we have different amounts of voxel-anisotropy
  • a direct registration of the DTI_baseline to the SPGR will fail, hence a 2-step approach is required

Key Strategies

  • Slicer 4 recommended modules: BrainsFit
  • to align the DTI with the T1 we need 2 registration steps: 1.align the T2 with the T1 and 2. align the DTI with the T2. The DTI baseline scan has contrast most similar to the T2 and hence is best registered against the T2. However the structural reference scan with highest resolution and tissue contrast is the T1.
  • we therefore use the following approach: 1) we first co-register the T2 with the SPGR T1. 2) we register the DTI baseline to the registered/resampled T2; 3) resample the DTI volume with the new transform
  • the DTI-T2 registration includes non-rigid deformation to correct for the strong distortions from the EPI acquisition. Because of the nonrigid component a mask of the brain parenchyma helps greatly in obtaining a meaningful transform.
  • The DTI estimation provides an automated mask for the DTI_baseline scan, but we have no mask for the T2. We can either obtain one through separate segmentation or by sending the DTI_mask through an additional registration step. In this example we show the latter.
  • thus the full pipeline is this:
  1. Affine align T2-T1, incl. resampled T2 volume = T2r
  2. Affine+BSpline align of DTI_baseline to T2r (unmasked)
  3. Resample DTI_mask with above BSpline -> mask for the T2r
  4. repeat Affine+BSpline align of DTI_base to T2r, WITH masks
  5. resample DTI with result Affine+BSpline transform

Procedures

  • Phase I: Preprocessing: Build DWI mask + baseline
  1. open the Modules:Diffusion:DiffusionWeightedImages:DiffusionWeightedVolumeMasking module
    1. Input DWI Volume: "DWI"
    2. Output Baseline Volume: Create New Volume, rename to "DWI_baseline"
    3. Output Threshold Mask: Create New Volume, rename to "DWI_mask"
    4. Leave other settings at default; click Apply
  • Phase II: Preprocessing: Convert DWI -> DTI
  1. open "Diffusion Tensor Estimation" module (menu: Diffusion:DiffusionWeightedImages: DiffusionTensorEstimation)
    1. Input DWI Volume: DWI_iso,
    2. Output DTI Volume: create new, rename to "DTI_iso"
    3. Output Baseline Volume: create new, rename to "DWI_iso_baseline"
  2. Click: Apply
  • Phase III: register T2 to T1
  1. open the General Registration (BRAINS) module
    1. Fixed Image Volume: T1
    2. Moving Image Volume: T2
    3. Output Settings:
      1. Slicer BSpline Transform": none
      2. Slicer Linear Transform: create new transform, rename to "Xf1_T2-T1"
      3. Output Image Volume: create new volume, rename to "T2_Xf1"
    4. Registration Phases: check boxes for Rigid and Affine
    5. Main Parameters:
      1. Number Of Samples: 200,000
    6. Leave all other settings at default
    7. click: Apply; runtime < 10 sec (MacPro QuadCore 2.4GHz)
  • Phase IV: Register DTI (masked)
  1. open the General Registration (BRAINS) module
    1. Fixed Image Volume: FLAIR_Xf1
    2. Moving Image Volume: DWI_iso_baseline
    3. Output Settings:
      1. Slicer BSpline Transform": create new transform, rename to "Xf2_DTI-T1"
      2. Slicer Linear Transform: none
      3. Output Image Volume: create new volume, rename to DWI_baseline_Xf2
    4. Regstration Phases: check boxes for Rigid, Affine and BSpline
    5. Main Parameters:
      1. Number Of Samples: 300,000
      2. B-Spline Grid Size: 7,7,5
    6. Mask Option: select ROIAUTO button
      1. (ROIAUTO) Output fixed mask: create new volume
      2. (ROIAUTO) Output moving mask: create new volume
    7. Leave all other settings at default
    8. click: Apply; runtime 1-2 min (MacPro QuadCore 2.4GHz)
  • Phase V: Resample DTI
  1. Open the Resample DTI Volume module (under All Modules menu; note this is distinct from the ResampleScalarVectorDWIVolume used above)
    1. Input Volume: DTI
    2. Output Volume: create new DTI Volume, rename to DTI_Xf2
    3. Reference Volume: T2_Xf1
    4. Transform Node: select "Xf2_DTI-T1 created above
    5. check box: displacement
  2. leave all other settings at defaults
  3. Click Apply; runtime ~ 3 min.
  4. set T1 or FLAIR as background and the new DTI_Xf2 volume as foreground
  5. Move fade slider to see DTI overlay onto the structural image

Registration Results

Registered DTI superimposed on SPGR and T2 registered (cycles show T1 and T2 and color DTI overlay)