Difference between revisions of "Projects:RegistrationLibrary:RegLib C03"

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[[Projects:RegistrationDocumentation:UseCaseInventory|Back to Registration Use-case Inventory]] <br>
 
[[Projects:RegistrationDocumentation:UseCaseInventory|Back to Registration Use-case Inventory]] <br>
  
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==Slicer Registration Library Exampe #3: Diffusion Weighted Image Volume: align with structural reference MRI==
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== <small>updated for '''v4.1'''</small> [[Image:Slicer4_RegLibLogo.png|150px]] <br>Slicer Registration Library Case #3: Diffusion Weighted Image Volume: align with structural reference MRI==
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=== Input ===
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==Slicer Registration Use Case Exampe: Intra-subject Brain MR FLAIR to MR T1==
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{| style="color:#bbbbbb; " cellpadding="10" cellspacing="0" border="0"
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{| style="color:#bbbbbb; background-color:#333333;" cellpadding="10" cellspacing="0" border="0"
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|[[Image:RegLib_C03_Reference_axial.png|150px|lleft|this is the fixed T2 reference image. All images are aligned into this space]]  
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|[[Image:RegLib_C03_Reference_axial.png|150px|lleft|this is the fixed reference image. All images are aligned into this space]]  
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|[[Image:RegArrow_NonRigid.png|100px|lleft]]  
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|[[Image:Arrow_left_gray.jpg|100px|lleft]]  
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|[[Image:RegLib_C03_Baseline_axial.png|150px|lleft|this is the DTI Baseline scan, to be registered with the T2]]
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|[[Image:RegLib_C03_Baseline_axial.png|150px|lleft|this is the moving image. The transform is calculated by matching this to the reference image]]
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|[[Image:RegLib_C03_DTIVol_axial.png|150px|lleft|this is the DTI tensor image, in the same orientation as the DTI Baseline]]
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|[[Image:RegLib_C03_DTIVol_axial.png|150px|lleft|this is a passive image to which the calculated transform is applied. It is a label-map in the same space as the moving FLAIR image]]
 
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|align="left"|LEGEND<br><small><small>
 
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[[Image:Button_red_fixed.jpg|20px|lleft]]  this indicates the reference image that is fixed and does not move. All other images are aligned into this space and resolution<br>
 
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[[Image:Button_green_moving.jpg|20px|lleft]]  this indicates the moving image that determines the registration transform.  <br>
 
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[[Image:Button_purple_mask.jpg|20px|lleft]] this indicates images that serve as masks, i.e. they focus the active registration onto a specific area.<br>
 
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[[Image:Button_blue_tag.jpg|20px|lleft]] this indicates images that passively move into the reference space, i.e. they have the transform applied but do not contribute to the calculation of the transform.
 
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</small></small>
 
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|-
 
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|[[Image:Button_red_fixed.jpg|40px|lleft]]  T2
 
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|[[Image:Button_purple_mask.jpg|40px|lleft]]  mask
 
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|
 
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|[[Image:Button_green_moving.jpg|40px|lleft]] DTI Baseline
 
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|[[Image:Button_blue_tag.jpg|40px|lleft]] DTI volume
 
 
|-
 
|-
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|1mm isotropic<br> 256 x 256 x 146<br>RAS
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|fixed image/target<br>T2
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|1mm isotropic<br> 256 x 256 x 146<br>RAS
 
 
|
 
|
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|1.2mm isotropic<br> 256 x 256 x 116<br>RAS
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|moving image 2a<br>DTI baseline
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|1.2mm isotropic<br> 256 x 256 x 116<br>RAS
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|moving image 2b<br>DTI tensor
 
|}
 
|}
  
 
===Objective / Background ===
 
===Objective / Background ===
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This is a typical example of DTI processing. Goal is to align the DTI image with a structural scan that provides accuracte anatomical reference. The DTI contains acquisition-related distortion and insufficient contrast to discern anatomical detail.
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Goal is to align the DTI image with the structural reference T2 scan that provides accuracte anatomical reference.  
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=== Keywords ===
 
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MRI, brain, head, intra-subject, DTI, DWI
 
  
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===Input Data===
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=== Slicer 4.1 Modules Used ===
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*[[Image:Button_red_fixed_white.jpg|20px]]reference/fixed : T2w FSE,
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*[https://www.slicer.org/wiki/Documentation/4.1/Modules/BRAINSFit BrainsFit]
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*[[Image:Button_green_moving_white.jpg|20px]] moving: Baseline image of acquired DTI volume, corresponds to T2w MRI , 0.9375 x 0.9375 x 1.4 mm voxel size, oblique
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*[https://www.slicer.org/wiki/Documentation/4.1/Modules/ResampleDTIVolume Resample DTI Volume]
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*[[Image:Button_green_moving_purple.jpg|20px]] moving: Tensor data of DTI volume, oblique, same orientation as Baseline image. The result Xform will be applied to this volume.
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*[https://www.slicer.org/wiki/Documentation/4.1/Modules/DiffusionTensorEstimation Diffusion Tensor Estimation]
  
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=== Registration Results===
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=== Alternate Versions ===
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{| style="color:#bbbbbb; background-color:#333333;" cellpadding="10" cellspacing="0" border="0"
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*this example covers the most basic form of directly registering a DTI + baseline to a T2. There is another (more advanced) version that show how to address additional issues of a strong initial rotation and strong voxel-anisotropy for the raw DWI image acquired.  [[Projects:RegistrationLibrary:RegLib_C03B|You will find the advanced version here]].
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|[[Image:RegLib01_GifAnim_reg.gif|200px|left|after orientation]]  
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*[[Projects:RegistrationLibrary:RegLib_C03_v3|for the Slicer 3.6.3 version of this case see here]]
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|[[Image:RegLib01_ColorAnim.gif|200px|left|before/after registration, indiv. images in red/cyan, match in gray]]
 
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|}
 
  
 
===Download ===
 
===Download ===
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*'''[[Media:RegLib_Case_01_TumorGrowth.zip‎|download entire package  <small> (Data,Presets,Tutorial, Solution, zip file 33.7 MB) </small>]]'''
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*Image Data:
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**[[Media:RegPreset_RegUC-001.txt|download registration parameter presets file  <small> (MRML file, import as scene) </small>]]
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**[[Media:RegLib_C03_Data.zip‎|'''RegLib_C03_Data''': main registration package: register DTI <small> (Data, Transforms, solutions, zip file 115 MB) </small>]]
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**[[Media:RegLib_C01_Data_TumorGrowth.zip|download image dataset only  <small>(NRRD, 10.7 MB, filename: RegLib_C01_Data_TumorGrowth.zip) </small>]]
 
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**[[Media:RegLib_Case_01_NRRD_TumorGrowth.zip|download image dataset only  <small>(NRRD, 10.7 MB, filename: RegLib_Case_01_NRRD_TumorGrowth.zip) </small> ]]
 
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**[[Media:RegLib_C01_DataNIFTI_TumorGrowth.zip|download image dataset in NIFTI format <small>(NIFTI / nii, 10.7 MB, filename: RegLib_C01_DataNIFTI_TumorGrowth.zip) </small> ]]
 
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**[[Media:RegXForm_RegUC-001.tfm.txt|result transform file <small>(ITK .tfm file, load into slicer and apply to the target volume)</small>]]
 
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**Tutorials (step-by -step walk through):
 
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***[[Media:RegLib_C01_VideoTutorial_TumorGrowth.mov|download/play video tutorial <small>(quicktime, 15.9 MB, filename: RegLib_C01_VideoTutorial_TumorGrowth.mov) </small>]]
 
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***[[Media:RegLib_C01_PPTTutorial_TumorGrowth.ppt.zip‎|download power point tutorial <small>(zip file, 2.8 MB, filename: RegLib_C01_PPTTutorial_TumorGrowth.ppt.zip) </small>]]
 
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***[[Media:RegInstr_RegUC-001.txt‎|download step-by step text instructions <small>(rtf text file) </small>]]
 
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*'''[[Media:RegLib_C01_TumorGrowth_MultiresSolution_Dec09.zip‎|Multiresolution testresult package <small> (Data,Xform, Solution, zip file 16.5 MB) </small>]]'''
 
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*'''[http://www.insight-journal.org/midas/item/bitstream/2332 Download package from MIDAS server<small> (Data,Xform) </small>]'''
 
  
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<!--
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=== Procedure ===
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comment
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This assumes you have the following: 1) a T2 reference image, 2) a DTI baseline image and  3) the DTI volume (both obtained from the  [https://www.slicer.org/wiki/Documentation/4.1/Modules/DiffusionTensorEstimation Diffusion Tensor Estimation module]).
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-->
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*Image Data:
 +
*'''Overview''':
 +
::#Using  [https://www.slicer.org/wiki/Documentation/4.1/Modules/BRAINSFit General Registraion (BRAINS)]''', register DTI_baseline to T2 (affine+nonrigid) w/o masking
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:#Resample the DTI with above transform with the  [https://www.slicer.org/wiki/Documentation/4.1/Modules/ResampleDTIVolume Resample DTI Volume] module
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#open  [https://www.slicer.org/wiki/Modules:BRAINSFit Registration : ''General Registration (BRAINS)'']  module
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##''Input Images'': fixed = T2 , moving = DTI_base
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##''Output Settings'':
 +
###''Slicer BSpline Transform'' (create new transform, rename to: "Xf1_DTbase-T2_BSpline")
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###''Slicer Linear Transform'' none
 +
###''Output Image Volume'' (create new volume, rename to: "DTIbaseline_Xf1"
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##''Registration Phases'':  select/check ''Rigid'' , ''Rigid+Scale'', ''Affine'', ''BSpline''
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##''Main Parameters'':
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###increase ''Number Of Samples'' to 200,000
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###set  ''B-Spline Grid Size'' to 5,5,5
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##Leave all other settings at default
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##click: ''Apply''; runtime < 1 min.
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#Resample DTI
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#Open the  [https://www.slicer.org/wiki/Documentation/4.1/Modules/ResampleDTIVolume Resample DTI Volume] module (found under: All Modules)
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##Input Volume: select DTI
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##Output Volume: select ''create new Diffusion Tensor Volume'',and rename it to ''DTI_Xf1''
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##Reference Volume: select ''T2''
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##Transform Parameters: select transform node "Xf1_DTI-T2_BSpline", for  ''Deformation Field'': none ; '''check the ''displacement'' checkbox'''
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##Leave all other settings at defaults
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##Click Apply; runtime ~ 2 min.
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#set ''T2'' as background and new  ''DTI_Xf1'' volume as foreground
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#fade between back- and foreground to see DTI overlay onto the T2 image. Note that you can also fade via holding the OPTION+CMD keys (mac) + dragging left mouse.
  
 +
=== Registration Results  (click to enlarge) ===
 +
{| style="color:#bbbbbb; background-color:#333333;" cellpadding="10" cellspacing="0" border="0"
 +
|[[Image:RegLib_C03_baseline_unregistered.gif|400px|left]]
 +
|[[Image:RegLib_C03_baseline_registered.gif|400px|left]]
 +
|[[Image:RegLib_C03_DTI_registered.gif|400px|left]]
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|-
 +
|baseline & T2 before registration
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|baseline to T2 after affine+nonrigid alignment
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|DTI and T2 before & after registration
 +
|}
  
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=== Discussion: Registration Challenges ===
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=== Keywords ===
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*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.
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MRI, brain, head, intra-subject, DTI, DWI
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*the two images have strong differences in coil inhomogeneity. This affects less the registration quality but hampers evaluation. Most of the difference does not become apparent until after registration in direct juxtaposition. Bias field correction beforehand is recommended.
 
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*we have slightly different voxel sizes
 
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*if the pathology change is substantial it might affect the registration.
 
  
 
=== Discussion: Key Strategies ===
 
=== Discussion: Key Strategies ===
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*the two images have identical contrast, hence we consider "sharper" cost functions, such as NormCorr or MeanSqrd
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*the strong EPI-based distortions of the DTI image make nonrigid registration necessary
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*general practice is to register the follow-up to the baseline. However here the follow-up has slightly higher resolution. From an image quality/data perspective it would be better to use the highest resolution image as your fixed/reference. But here follow the most common convention, i.e. fixed image is the baseline.
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*initial alignment & overlap is sufficient so that no "initialization" methods are necessary and registration can succeed without.
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*because we seek to assess/quantify regional size change, we must use a rigid (6DOF) scheme, i.e. we must exclude scaling.
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*contrast & initial pose are similar enough for registration to succeed without any masking. However the DTI estimation procedure '''does''' provide an optional mask that is usually very helpful in registering cases with more "distracting" image content.   [[Projects:RegistrationLibrary:RegLib_C03_2| For an example see the extended version of this case here.]]
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*if the pathology change is soo large that it might affect the registration, we should mask it out. The simplest way to do this is to build a box ROI from the ROItool and feed it as input to the registration. Remember that masking does not mean that masked areas aren't matched, they just do not contribute to the cost function driving the registration, but move along passively. Next more involved level would be to outline the tumor. If a segmentation is available, you can use that.
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*the DTI in this example is isotropic and hence can be resampled directly. If the DTI contains strong anisotropy of ratios 1:3 or greater, reorienting the DTI can lead to strong artifacts (e.g. in axial direction appear as blue cast in the color orientation view). In that case it is necessary to resample the DWI in the original orientation to an isotropic size before reorienting. It may also be advisable to first reorient the DWI and perform the DTI estimation afterwards.
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*these two images are not too far apart initially, so we reduce the default of expected translational misalignment
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*because accuracy is more important than speed here, we increase the sampling rate from the default 2% to 15%.
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=== Acknowledgments ===
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*we also expect minimal differences in scale & distortion: so we can either set the expected values to 0 or run a rigid registration
 
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*we test the result in areas with good anatomical detail and contrast, far away from the pathology. With rigid body motion a local measure of registration accuracy is representative and can give us a valid limit of detectable change.
 

Latest revision as of 17:29, 10 July 2017

Home < Projects:RegistrationLibrary:RegLib C03

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Back to Registration main page
Back to Registration Use-case Inventory

updated for v4.1 Slicer4 RegLibLogo.png
Slicer Registration Library Case #3: Diffusion Weighted Image Volume: align with structural reference MRI

Input

this is the fixed T2 reference image. All images are aligned into this space 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
T2 		moving image 2a
DTI baseline 		moving image 2b
DTI tensor

Objective / Background

Goal is to align the DTI image with the structural reference T2 scan that provides accuracte anatomical reference.

Slicer 4.1 Modules Used

Alternate Versions

Download

Procedure

This assumes you have the following: 1) a T2 reference image, 2) a DTI baseline image and 3) the DTI volume (both obtained from the Diffusion Tensor Estimation module).

  • Image Data:
  • Overview:
  1. Using General Registraion (BRAINS), register DTI_baseline to T2 (affine+nonrigid) w/o masking
  1. Resample the DTI with above transform with the Resample DTI Volume module
  1. open Registration : General Registration (BRAINS) module
    1. Input Images: fixed = T2 , moving = DTI_base
    2. Output Settings:
      1. Slicer BSpline Transform (create new transform, rename to: "Xf1_DTbase-T2_BSpline")
      2. Slicer Linear Transform none
      3. Output Image Volume (create new volume, rename to: "DTIbaseline_Xf1"
    3. Registration Phases: select/check Rigid , Rigid+Scale, Affine, BSpline
    4. Main Parameters:
      1. increase Number Of Samples to 200,000
      2. set B-Spline Grid Size to 5,5,5
    5. Leave all other settings at default
    6. click: Apply; runtime < 1 min.
  2. Resample DTI
  3. Open the Resample DTI Volume module (found under: All Modules)
    1. Input Volume: select DTI
    2. Output Volume: select create new Diffusion Tensor Volume,and rename it to DTI_Xf1
    3. Reference Volume: select T2
    4. Transform Parameters: select transform node "Xf1_DTI-T2_BSpline", for Deformation Field: none ; check the displacement checkbox
    5. Leave all other settings at defaults
    6. Click Apply; runtime ~ 2 min.
  4. set T2 as background and new DTI_Xf1 volume as foreground
  5. fade between back- and foreground to see DTI overlay onto the T2 image. Note that you can also fade via holding the OPTION+CMD keys (mac) + dragging left mouse.

Registration Results (click to enlarge)

RegLib C03 baseline unregistered.gif
RegLib C03 baseline registered.gif
RegLib C03 DTI registered.gif
baseline & T2 before registration baseline to T2 after affine+nonrigid alignment DTI and T2 before & after registration

Keywords

MRI, brain, head, intra-subject, DTI, DWI

Discussion: Key Strategies

  • the strong EPI-based distortions of the DTI image make nonrigid registration necessary
  • initial alignment & overlap is sufficient so that no "initialization" methods are necessary and registration can succeed without.
  • contrast & initial pose are similar enough for registration to succeed without any masking. However the DTI estimation procedure does provide an optional mask that is usually very helpful in registering cases with more "distracting" image content. For an example see the extended version of this case here.
  • the DTI in this example is isotropic and hence can be resampled directly. If the DTI contains strong anisotropy of ratios 1:3 or greater, reorienting the DTI can lead to strong artifacts (e.g. in axial direction appear as blue cast in the color orientation view). In that case it is necessary to resample the DWI in the original orientation to an isotropic size before reorienting. It may also be advisable to first reorient the DWI and perform the DTI estimation afterwards.

Acknowledgments

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