Difference between revisions of "Projects:RegistrationLibrary:RegLib C02"

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This scenario occurs in many forms whenever we wish to align all the series from a single MRI exam/session into a common space. Alignment is necessary because the subject likely has moved in between series.  
 
This scenario occurs in many forms whenever we wish to align all the series from a single MRI exam/session into a common space. Alignment is necessary because the subject likely has moved in between series.  
 
=== Keywords ===
 
=== Keywords ===
MRI, brain, head, intra-subject, FLAIR, T1, defacing, masking
+
MRI, brain, head, intra-subject, FLAIR, T1, defacing, masking, labelmap, segmentation
 +
 
 
===Input Data===
 
===Input Data===
 
*reference: T1 SPGR , 1x1x1 mm voxel size, sagittal, RAS orientation
 
*reference: T1 SPGR , 1x1x1 mm voxel size, sagittal, RAS orientation

Revision as of 17:20, 20 October 2009

Home < Projects:RegistrationLibrary:RegLib C02

Slicer Registration Use Case Exampe: Intra-subject Brain MR FLAIR to MR T1

reference lleft moving apply
lleft T1 SPGR lleft T2 FLAIR lleft LABEL-MAP
1mm isotropic 1.2mm isotropic 1.2mm isotropic

Objective / Background

This scenario occurs in many forms whenever we wish to align all the series from a single MRI exam/session into a common space. Alignment is necessary because the subject likely has moved in between series.

Keywords

MRI, brain, head, intra-subject, FLAIR, T1, defacing, masking, labelmap, segmentation

Input Data

  • reference: T1 SPGR , 1x1x1 mm voxel size, sagittal, RAS orientation
  • moving: T2 FLAIR 1.2x1.2x1.2 mm voxel size, sagittal, RAS orientation
  • quick view JPEG of a lighbox. Does your data look like this?
  • download dataset to load into slicer

Registration Challenges

  • we expect the amount of misalignment to be small
  • we know the underlying structure/anatomy did not change, hence whatever residual misalignment remains is of technical origin.
  • the different series may have different FOV. The additional image data may distract the algorithm and require masking
  • the different series may have very different resolution and anisotropic voxel sizes
  • hi-resolution datasets may have defacing applied to one or both sets, and the defacing-masks may not be available
  • the different series may have different contrast.
  • individual series may contain motion or other artifacts

Procedure

  • step-by step text instruction
  • recommended parameter settings
  • guided video tutorial
  • power point tutorial

Registration Results

  • registration parameter presets file (load into slicer and run the registration)
  • result transform file (load into slicer and apply to the target volume)
  • result screenshots (compare with your results)
  • result evaluations (metrics)