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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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{| style="color:#bbbbbb; background-color:#333333;" cellpadding="10" cellspacing="0" border="0"
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{| style="color:#bbbbbb; " cellpadding="10" cellspacing="0" border="0"
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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: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:Arrow_left_gray.jpg|100px|lleft]]  
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|[[Image:RegArrow_NonRigid.png|100px|lleft]]  
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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_Baseline_axial.png|150px|lleft|this is the DTI Baseline scan, to be registered with the T2]]
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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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|[[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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|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_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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|
 
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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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|0.46 x 0.46 x 3.0 mm axial <br> 512 x 512 x 46<br>RAS
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|fixed image/target<br>T2
 
|
 
|
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|1.0 x 1.0 x 3.3 mm <br> axial oblique<br> 256 x 256 x 36<br>RAS
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|moving image 2a<br>DTI baseline
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|1.0 x 1.0 x 3.3 mm <br> axial oblique<br> 256 x 256 x 36 x 9 <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 axial, 0.4mm resolution in plane, 3mm slices
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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_blue_tag_white.jpg|20px]] tag: Tensor data of DTI volume, oblique, same orientation as Baseline image. The result Xform will be applied to this volume. The original DWI has 26 directions, the extracted DTI volume has 9 scalars, i.e. 256 x 256 x 36 x 9
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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:RegLib_C03_AffineResult_AnimGif.gif|200px|left|after affine alignment]]  
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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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|-
 
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|baseline to T2 after affine alignment
 
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|}
 
  
 
===Download ===
 
===Download ===
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[[Image:under-construction_icon.jpg|right|100px|this case is still under active development. Comments and priority requests welcome to the slicer-users mailing list]]
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*Image Data:
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*'''[[Media:RegLib_03_DTIExample_full.zip‎|download entire package <small> (Data,Presets, Solution, zip file 24 MB) </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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*Presets
 
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*Tutorial only
 
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*Image Data only
 
  
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[[Projects:RegistrationDocumentation:ParameterPresetsTutorial|Link to User Guide: How to Load/Save Registration Parameter Presets]]
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=== 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  [https://www.slicer.org/wiki/Documentation/4.1/Modules/DiffusionTensorEstimation Diffusion Tensor Estimation module]).
 +
*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'':
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###''Slicer BSpline Transform'' (create new transform, rename to: "Xf1_DTbase-T2_BSpline")
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###''Slicer Linear Transform'' none
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###''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
 +
##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
 +
##Click Apply; runtime ~ 2 min.
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#set ''T2'' as background and new  ''DTI_Xf1'' volume as foreground
 +
#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]]
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|[[Image:RegLib_C03_DTI_registered.gif|400px|left]]
 +
|-
 +
|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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|}
  
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<!--
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=== Keywords ===
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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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MRI, brain, head, intra-subject, DTI, DWI
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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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comment
 
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-->
 
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=== Discussion: Registration Challenges ===
 
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*The DTI contains acquisition-related distortions (commonly EPI acquisitions) that can make automated registration difficult.
 
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*the two images often have strong differences in  voxel sizes and voxel anisotropy. If the orientation of the highest resolution is not the same in both images, finding a good match can be difficult.
 
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*there may be widespread and extensive pathology  (e.g stroke, tumor) that might affect the registration if its contrast is different in the baseline and structural reference scan
 
  
 
=== Discussion: Key Strategies ===
 
=== Discussion: Key Strategies ===
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*the two images have identical contrast, hence we could consider "sharper" cost functions, such as NormCorr or MeanSqrd. But because of the strong distortions and lower resolution of the moving image, Mutual Information is recommended as the most robust metric.
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*the strong EPI-based distortions of the DTI image make nonrigid registration necessary
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*often anatomical labels are available from the reference scan. It would be less work to align the anatomical reference with the DTI, since that would circumvent having to resample the complex tensor data into a new orientation. However the strong distortions are better addressed by registering the other direction, i.e. move the DTI into the anatomical reference space.
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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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*masking is likely necessary to obtain good results.
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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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*in this example the initial alignment of the two scans is very poor. The strongly oblique orientation of the DTI makes an initial manual alignment step necessary.
 
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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 speed is not that critical, we increase the sampling rate from the default 2% to 15%.
 
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*we also expect larger differences in scale & distortion than with regular structural scane: so we significantly  (2x-3x) increase the expected values for scale and skew from the defaults.
 
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*a good affine alignment is important before proceeding to non-rigid alignment to further correct for distortions.
 
  
 
=== Acknowledgments ===
 
=== Acknowledgments ===

Latest revision as of 17:29, 10 July 2017

Home < Projects:RegistrationLibrary:RegLib C03

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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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