Projects:RegistrationLibrary:RegLib C14

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Slicer Registration Use Case Exampe #14: Intra-subject Brain PET-MRI with MRI orientation adjustment

			LEGEND this indicates the reference image that is fixed and does not move. All other images are aligned into this space and resolution this indicates the moving image that determines the registration transform.
MRI		PET
MRI: coronal T1w 256 x 256 x 79 0.86 x 0.86 x 2.5 mm		PET: axial, fluorodeoxyglucose 128 x 128 x 35 4.29 x 4.29 x 4.25 mm

Objective / Background

Image fusion.

Keywords

PET-MRI, brain, intra-subject, image fusion

Input Data

• reference/fixed : baseline MRI: 0.97 x 0.97 x 3.27 mm , PET: 4.7 x 4.7 x 3.3 mm
• moving: PET: 4.1 x 4.1 x 5 mm

Registration Results

• 

  uncorrected MRI as read from DICOM.

• 

  unregistered MRI & PET images.

• 

  registered MRI & PET images.

Download

• download full tutorial set (Data+intermediate results+presets+tutorial, zip file 17 MB)
• download example data set (Data only, zip file 16 MB)
• download step-by-step tutorial (PowerPoint 1.2 MB)

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

Discussion: Registration Challenges

• the original DICOM files of the MRI have image orientation data stripped. Hence the volume does not load in correct orientation and needs to be adjusted
• the two series have different voxel sizes
• image content and resolution in PET is low

Discussion: Key Strategies

• we use the Volumes module to adjust the MRI voxel size based on the info in the DICOM header
• we use the Transforms module to reorient the MRI along the proper axes
  • the aspect ratio we correct via the "Volumes" module. The correct slice thickness we obtain from the DICOM header via the browser displayed when selecting "Add Volume"
  • the "Transforms" module is used to correct orientation. We enter manual rotations of 90 and 180 degrees around the LR (left-right) and IS (inferior-superior) axes, respectively
  • the corrected MRI volume is resampled in the Data module via "harden transforms"
• Register Images is used to automatically align the PET with the MRI. We choose mutual information ("MI") as the criterion and a 5% sampling rate. We request an affine transform to correct for small distortion differences between the PET and the MRI

Acknowledgments

Our thanks to the University of Western Ontario for providing this example case.