Difference between revisions of "Projects:RegistrationLibrary:RegLib C04"

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|[[Image:Reglib_C04_Thumb_PD2.jpg|100px|lleft|this is the inter-subject moving image, but also the reference for exam 2]]
 
|[[Image:Reglib_C04_Thumb_PD2.jpg|100px|lleft|this is the inter-subject moving image, but also the reference for exam 2]]
 
|[[Image:Reglib_C04_Thumb_T22.jpg|100px|lleft|this is the inter-subject moving image, but also the reference for exam 2]]
 
|[[Image:Reglib_C04_Thumb_T22.jpg|100px|lleft|this is the inter-subject moving image, but also the reference for exam 2]]
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|[[Image:RegArrow_Affine.png|100px|lleft]]  
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|[[Image:RegArrow_Affine.png|70px|lleft]]  
 
|[[Image:Reglib_C04_Thumb_Gd2.jpg|100px|lleft|this is the moving image. ]]
 
|[[Image:Reglib_C04_Thumb_Gd2.jpg|100px|lleft|this is the moving image. ]]
 
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=== Procedure ===
 
=== Procedure ===
 
#Load example dataset via OpenScene...
 
#Load example dataset via OpenScene...
 +
#Go to the ''Data'' module. You should see 6 images (e1_PD, e1_T2 etc.) and 3 solution transforms (Xform_...)
 +
#Set background view to e1_PD and foreground to e2_PD. Toggle to see misalignment
 
#Align Exam 1:
 
#Align Exam 1:
−
##Open ''BrainsFit'' module
+
##Open ''Registration / BRAINSFit'' module
 +
##To set all parameters from presets, from the ''ParameterSet'' menu, select Gd1-PD1, else choose settings below:
 
##Fixed Image: e1_PD, moving image: e1_T1
 
##Fixed Image: e1_PD, moving image: e1_T1
−
##
+
##Registration Phases: select ''Include Rigid'' and ''Include Affine''
 +
##Output Settings: under SlicerLinear Transform, select "Create New Linear Transform'', then select ''Rename" and rename it to ''MyXform_Gd1-PD1''
 +
##Registration Parameters: change the ''Number of Samples'' field to 200,000
 +
##Leave all other settings at defaults
 +
##Click Apply. Registration should complete within ~ 10 seconds
 +
##Go back to the ''Data'' module: you should see the e1_T1Gd image moved under the newly created transform
 +
##Select ''e1_T1Gd'' as new foreground, toggle to see alignment
 +
#Align Exam 2:
 +
##repeat the above steps for ''e2_PD'' as fixed and ''e2_T1Gd'' as moving
 +
#Align Exam 2 with Exam 1:
 +
##Open ''Registration / BRAINSFit'' module
 +
##To set all parameters from presets, from the ''ParameterSet'' menu, select Gd1-PD1, else choose settings below:
 +
##Fixed Image: e1_PD, moving image: e1_T1
 +
##Registration Phases: select ''Include Rigid'' and ''Include Affine''
 +
##Output Settings: under SlicerLinear Transform, select "Create New Linear Transform'', then select ''Rename" and rename it to ''MyXform_Gd1-PD1''
 +
##Registration Parameters: change the ''Number of Samples'' field to 200,000
 +
##Leave all other settings at defaults
 +
##Click Apply. Registration should complete within ~ 10 seconds
 +
##Go back to the ''Data'' module: you should see the e1_T1Gd image moved under the newly created transform
 +
##Select ''e1_T1Gd'' as new foreground, toggle to see alignment
 +
 
 
=== Registration Results===
 
=== Registration Results===
 
[[Image:RegLib_C04_T1Gd-PD_unreg_AnimGif.gif||500px|Unregistered baseline data: PD vs. T1Gd]] Unregistered baseline data: PD vs. T1Gd<br>
 
[[Image:RegLib_C04_T1Gd-PD_unreg_AnimGif.gif||500px|Unregistered baseline data: PD vs. T1Gd]] Unregistered baseline data: PD vs. T1Gd<br>

Revision as of 14:52, 13 September 2010

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v3.6.1 Slicer3-6Announcement-v1.png Slicer Registration Library Case 04:
Intra-subject Brain MR of Multiple Sclerosis: Multi-contrast series for lesion change assessment

Input

this is the main fixed reference image. All images are ev. aligned into this space this is the main fixed reference image. All images are ev. aligned into this space lleft this is the intra-subject moving image.
exam 1: PD exam 1: T2 exam 1: T1-Gd
lleft
this is the inter-subject moving image, but also the reference for exam 2 this is the inter-subject moving image, but also the reference for exam 2 lleft this is the moving image.
exam 2: PD exam 2: T2 exam 2: T1-Gd

Modules

Objective / Background

This scenario occurs in many forms whenever we wish to assess change in a series of multi-contrast MRI. The follow-up scan(s) are to be aligned with the baseline, but also the different series within each exam need to be co-registered, since the subject may have moved between acquisitions. Hence we have a set of nested registrations. This particular exam features a dual echo scan (PD/T2), where the two structural scans are aligned by default. The post-contrast T1-GdDTPA scan however is not necessarily aligned with the dual echo. Also the post-contrast scan is taken with a clipped field of view (FOV) and a lower axial resolution, with 4mm slices and a 1mm gap (which we treat here as a de facto 5mm slice).

Download

this case is still under active development. Comments and priority requests welcome to the slicer-users mailing list

Link to User Guide: How to Load/Save Registration Parameter Presets

Keywords

MRI, brain, head, intra-subject, multiple sclerosis, MS, multi-contrast, change assessment, dual echo, nested registration

Input Data

  • reference/fixed : PD.1 baseline exam , 0.9375 x 0.9375 x 3 mm voxel size, axial acquisition, RAS orientation.
  • fixed T2.1 baseline exam , 0.9375 x 0.9375 x 3 mm voxel size, axial acquisition, RAS orientation. -> (aligned with PD.1, not used for registering)
  • moving: T1.1 (GdDTPA contrast-enhanced scan) baseline exam 0.9375 x 0.9375 x 5 mm voxel size, axial acquisition.
  • moving: PD.2 follow-up exam 0.9375 x 0.9375 x 3 mm voxel size, axial acquisition.
  • moving: T2.2 follow-up exam 0.9375 x 0.9375 x 3 mm voxel size, axial acquisition. -> same orientation as PD2, will have same transform applied
  • moving:T1.2-GdDTPA follow-up exam0.9375 x 0.9375 x 5 mm voxel size, axial acquisition. -> undergoes 2 transforms: first to PD.2, then to PD.1

Registration Challenges

  • we have multiple nested transforms: each exam is co-registered within itself, and then the exams are aligned to eachother
  • potential pathology change can affect the registration
  • anisotropic voxel size causes difficulty in rotational alignment
  • clipped FOV and low tissue contrast of the post-contrast scan

Key Strategies

  • we first register the post-contrast scans within each exam to the PD
  • second we register the follow-up PD scan to the baseline PD
  • we also move the T2 exam within the same Xform
  • we then nest the first alignment within the second
  • because of the contrast differences and anisotropic resolution we use Mutual Information as cost function for better robustness

Procedure

  1. Load example dataset via OpenScene...
  2. Go to the Data module. You should see 6 images (e1_PD, e1_T2 etc.) and 3 solution transforms (Xform_...)
  3. Set background view to e1_PD and foreground to e2_PD. Toggle to see misalignment
  4. Align Exam 1:
    1. Open Registration / BRAINSFit module
    2. To set all parameters from presets, from the ParameterSet menu, select Gd1-PD1, else choose settings below:
    3. Fixed Image: e1_PD, moving image: e1_T1
    4. Registration Phases: select Include Rigid and Include Affine
    5. Output Settings: under SlicerLinear Transform, select "Create New Linear Transform, then select Rename" and rename it to MyXform_Gd1-PD1
    6. Registration Parameters: change the Number of Samples field to 200,000
    7. Leave all other settings at defaults
    8. Click Apply. Registration should complete within ~ 10 seconds
    9. Go back to the Data module: you should see the e1_T1Gd image moved under the newly created transform
    10. Select e1_T1Gd as new foreground, toggle to see alignment
  5. Align Exam 2:
    1. repeat the above steps for e2_PD as fixed and e2_T1Gd as moving
  6. Align Exam 2 with Exam 1:
    1. Open Registration / BRAINSFit module
    2. To set all parameters from presets, from the ParameterSet menu, select Gd1-PD1, else choose settings below:
    3. Fixed Image: e1_PD, moving image: e1_T1
    4. Registration Phases: select Include Rigid and Include Affine
    5. Output Settings: under SlicerLinear Transform, select "Create New Linear Transform, then select Rename" and rename it to MyXform_Gd1-PD1
    6. Registration Parameters: change the Number of Samples field to 200,000
    7. Leave all other settings at defaults
    8. Click Apply. Registration should complete within ~ 10 seconds
    9. Go back to the Data module: you should see the e1_T1Gd image moved under the newly created transform
    10. Select e1_T1Gd as new foreground, toggle to see alignment

Registration Results

Unregistered baseline data: PD vs. T1Gd Unregistered baseline data: PD vs. T1Gd
Unregistered followup data: PD exam 2 vs. exam 1 Unregistered followup data: PD exam 2 vs. exam 1
Registered baseline data Registered baseline data
Registered followup data Registered followup data
Lesion change visualization in 3DLesion change visualization in 3D
Lesion change via subtraction imaging of co-registered PDLesion change via subtraction imaging of co-registered PD

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