Skip to content

Image Registration Module

Ryan Yan edited this page Feb 22, 2022 · 4 revisions

The Image Registration module performs a longitudinal registration of a baseline and a follow-up image. The algorithm will determine a transform that minimilizes differences between the two images, so they are aligned by features on the bone. The visualization tool can then be used to create a subtraction of the images, showing changes in the bone over the time period.

Step 1: Register Images

Parameters:

  • Baseline: Baseline (initial) image
  • Follow-up: Follow-up image
  • Similarity Metric: Method used to calculating difference between images
  • Metric Sampling Percentage: Percentage of image used for similarity calculation
  • Output: Output volume

Upload the baseline and follow-up image into slicer and select them in the appropriate dropdown. Select a similarity metric to use in the registration algorithm. Each metric uses a different method to determine the difference between images at each iteration. The chosen metric can significantly affect the results of registration, so choose carefully.

  • Mean Squares: Computes the mean squared difference between pixel values. Requires intensity values to be within the same thresholds for images.

  • Correlation: Computes the normal correlation between pixel values. Requires images in the same modality, but can be in any intensity range.

  • Mattes Mutual Information: Computes the mutual information (ability to determine intensity of the second image based on the first) of the images. Can be used with multiple modalities (i.e. CT scan and MRI).

  • ANTS Neighborhood: Computes the correlation of a small neighbourhood for each pixel. Ideal for images that are very close already since this method is slower.

The Metric Sampling Percentage will determine what percentage of the image is analyzed per iteration. Points on the image will be randomly selected for calculations. Increasing the sampling percentage will improve the final results, but will significantly increase the time required.

Recommended percentages:

  • Small Image (<50 MB): 0.1
  • Medium Image (50-200 MB): 0.01
  • Large Image (200 MB - 1 GB): 0.001
  • X-Large Image (>1 GB): 0.0001

Click Apply to begin registration. This will take a few minutes.

Step 2: Visualize Images

Parameters:

  • Baseline: Baseline (initial) image
  • Follow-up: Registered follow-up image
  • Output: Output volume
  • Lower Threshold: Lower threshold of bone
  • Upper Threshold: Upper threshold of bone
  • Gaussian Sigma: Sigma for Gaussian filter

Select the baseline image and the registred image from step 1 to create a subtraction of the images. This is a visualization of the registration results that shows how the two images differ.

Color code:

  • White: Present in both images
  • Peach: In baseline only
  • Blue: In follow-up only

Go to the Data module, find the subtraction image and right click on the eye symbol. Select "Show in 3d views as volume rendering" to create an interactive 3d render of the subtraction.

Clone this wiki locally