Projects:RegistrationLibrary:RegLib C30

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v3.6.1 Slicer Registration Library Case #30: Intra-subject Brain DTI

Input

fixed image/target T1		moving image 2a DTI baseline	moving image 2b DTI tensor

Slicer4 Modules used

• Diffusion Tensor Estimation module
• General Registration (BRAINS) module
• Resample DTI Volume module

Objective / Background

This is a common case of a DTI exam with no T2 available as structural reference and a T1 that has strong field inhomogeneity. We wish to spatially align the DTI to the anatomical reference scan (T1-SPGR).

Download

• DATA
  • Registration Library Case 30 (registration set) (Data & Solution Xforms, incl. DTI, zip file 18 MB)
  • Registration Library Case 30 (DWI+resampled DTI set) (original DWI + resampled DTI only, zip file 53 MB)
• PRESETS:
  • Registration Library Case 30: Parameter Presets (presets for bias correction, mask generation, registration & resampling) 12kB, load via ImportScene..)
  • Link to User Guide: How to Load/Save Registration Parameter Presets
• Documentation:
  • See detailed pipeline with parameter settings below

Keywords

MRI, brain, head, intra-subject, DTI, T1, non-rigid,

Input Data

• reference/fixed : T1 , 1x1x1.1 mm voxel size, 256 x 256 x 193
• moving: DTI baseline: 2.5 x 2.5 x 2.5 mm, 128 x 112 x 44
• moving DTI tensor: : 2.5 x 2.5 x 2.5 mm, 128 x 112 x 44 x 9 (tensor), original: DWI 256 x 256 x 41 x 36 directions

Registration Challenges

• The DTI sequence (EPI) has a low resolution, a clipped FOV and distortions we seek to correct via non-rigid alignment
• the DTI baseline is similar in contrast to a T2, but we have only a T1 as structural reference

Key Strategies

• the DWI needs to be converted to a DTI and a mask and baseline obtained
• to align the DTI with the T1 we need 2 preprocessing steps: 1. reduce the bias field inhomogeneity in the reference T1 and 2. obtain a skull-stripping / brain mask for the T1
• The DWI is already isotropic and hence no resampling is required before obtaining the DTI
• 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 T1. We can either obtain one through separate segmentation or by sending the DTI_mask through an additional registration step. We use the former here.
• thus the full pipeline is this:

1. Bias Field Correction of T1 -> T1_bc
2. Skull Stripping of T1_bc
3. DWI -> DTI estimation (incl. DTI_base and DT_mask output)
4. Affine registration of DTI_baseline to T1_bc, unmasked
5. non-rigid (BSpline) registration of DTI_baseline to T1_bc, masked, using above affine as starting pose
6. 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
   2. Output DTI Volume: create new, rename to "DTI"
   3. Output Baseline Volume: create new, rename to "DWI_baseline"
2. Click: Apply

• Phase II: Bias Correction of T1

1. The T1 image has strong intensity inhomogeneity from coil sensitivity. We need to correct this first
   1. open the Filtering : N4ITK MRI Bias Field Correction module
   2. Input Image: T1
   3. Mask Image: none
   4. Output Volume: create new volume, rename to T1_n4
   5. leave rest at defaults
   6. Click: Apply

• Phase III: Affine pre-registration

1. open the General Registration (BRAINS) module
   1. Fixed Image Volume: T1_n4
   2. Moving Image Volume: DWI_baseline
   3. Output Settings:
      1. Slicer BSpline Transform": none
      2. Slicer Linear Transform: create new transform, rename to "Xf1_DWI-T1_Affine"
      3. Output Image Volume: create new volume, rename to "DWI_baseline_Xf1" (we use this for validation only)
   4. Registration Phases: check boxes for Rigid , Rigid+Scale and Affine
   5. Main Parameters:
      1. Number Of Samples: 200,000
   6. Mask Option: select ROIAUTO button
      1. (ROIAUTO) Output fixed mask: create new volume , rename to "T1_mask_ROIauto"
      2. (ROIAUTO) Output moving mask: create new volume, rename to "DWI_mask_ROIauto"
   7. Leave all other settings at default
   8. click: Apply; runtime < 1 min (MacPro QuadCore 2.4GHz)
   9. this should generate a first alignment and also 2 masks. We already have a DWI mask, so we care not about "DWI_mask_ROIauto", but we will use the T1_mask_ROIauto" output to edit/cleanup and use as mask in the subsequent nonrigid registration

• Phase IV: T1 mask

1. open the Editor module
2. select "T1_mask_ROIauto" as the volume to edit
3. select the Erosion tool and click Apply until all of the segmented skull areas are removed
4. select the Brush tool and manually fill in missing areas. Note that this need not be extremely accurate along the edges, since it will serve as a registration mask. To skip this step load the "T1_mask_edit.nrrd" file from the downloaded dataset.

• Phase V: Nonrigid Registration

1. open the General Registration (BRAINS) module
   1. Fixed Image Volume: T1_n4
   2. Moving Image Volume: DWI_baseline
   3. Output Settings:
      1. Slicer BSpline Transform": create new transform, rename to "Xf2_DWI-T1_BSpline"
      2. Slicer Linear Transform: none
      3. Output Image Volume: create new volume, rename to "DWI_baseline_Xf2"
   4. Registration Phases: check boxes for BSpline only
   5. Main Parameters:
      1. Number Of Samples: 200,000
      2. B-Spline Grid Size: 5,5,5
   6. Mask Option: select ROI button
      1. ROI Masking input fixed: select " "T1_mask_ROIauto" or "T1_mask_edit" edited in phase III above
      2. ROI Masking input moving: select "DWI_mask" created in phase I above
   7. Leave all other settings at default
   8. click: Apply

• Phase VI: Resample DTI

1. Open the Resample DTI Volume module (found under: All Modules)
   1. Input Volume: DTI
   2. Output Volume: select New DTI Volume, rename to DTI_Xf2
   3. Reference Volume: T1
   4. Transform Parameters:
      1. Transform Node: Xf2_DTI-T1
      2. check box: displacement
   5. Leave all other settings at defaults
   6. Click Apply; runtime 1-2 min.
2. set T1_n4 as background and new DTI_Xf2 volume as foreground
3. Set fade slider to see DTI overlay onto the T1 image. You should see something similar to the animated gif shown in the result section below.

Registration Results

registered