Projects:RegistrationLibrary:RegLib C08

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Slicer Registration Use Case Exampe #8: Intra-subject whole-body PET-CT

			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.
whole body CT + PET baseline		whole body CT + PET follow-up
CT: 512 x 512 x 267 0.97 x 0.97 x 3.27 mm PET: 128 x 128 x 267 4.7 x 4.7 x 3.3 mm		CT: 512 x 512 x 195 0.98 x 0.98 x 5.0 mm PET: 168 x 168 x 195 4.1 x 4.1 x 5 mm

Objective / Background

Change assessment.

Keywords

PET-CT, whole-body, change assessment

Input Data

• reference/fixed : baseline CT: 0.97 x 0.97 x 3.27 mm , PET: 4.7 x 4.7 x 3.3 mm
• moving: CT: 0.98 x 0.98 x 5; PET: 4.1 x 4.1 x 5 mm

Download

• download entire package (Data,Presets,Tutorial, Solution, zip file 135 MB)

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

Discussion: Registration Challenges

• 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.
• the two series have different voxel sizes
• because of the large FOV we have strong non-rigid deformations from differences in patient/limb positions etc.
• images are large volumes (>100 MB total)
• image content reaches border of image on two sides

Discussion: Key Strategies

• the two images have identical contrast, hence we consider "sharper" cost functions, such as NormCorr or MeanSqrd
• we have aliasing at the image margins that should be masked out
• the two images are far apart initially, we will need some form of initialization
• because accuracy is more important than speed here, we increase the sampling rate from the default 2% to 15%.
• we also expect minimal differences in scale & distortion: so we can either set the expected values to 0 or run a rigid registration
• 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.