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Registration

Volvicon provides two registration methods for aligning multiple datasets: Landmark Registration for manual point-based alignment and Global Registration for automatic alignment using surface or image features.

Which one applies depends on how you want to drive the alignment, and, inside Global Registration, on the types of the fixed and moving objects. Volvicon picks surface-based or image-based automatically from those types.

Landmark Registration​

Landmark Registration aligns datasets using corresponding points placed manually on the fixed (reference) and moving (to be aligned) objects.

Accessing the Tool​

  1. Navigate to the Image tab in the ribbon.
  2. Click Landmark Registration in the Transform section.

Concepts​

TermDescription
Fixed objectThe reference dataset that remains stationary
Moving object(s)Datasets that will be transformed to align with the fixed object
LandmarkA point placed on an identifiable anatomical or geometric feature

Requirements​

  • Minimum 3 landmark pairs are required for registration.
  • Landmarks must be placed on corresponding features in both datasets.
  • More landmarks generally improve registration accuracy.

Three landmark pairs placed in the same order on a fixed object and a moving object, and the moving object aligned onto the fixed one after registration

Workflow​

  1. Open the Landmark Registration tool.
  2. Select the fixed object (reference) and moving object(s).
  3. Place landmarks on the fixed object by clicking identifiable features.
  4. Place corresponding landmarks on the moving object in the same order.
  5. Verify that landmark pairs correspond correctly (same anatomical/geometric feature).
  6. Optionally enable Global registration fine-tuning for automatic refinement.
  7. Click Apply to perform the registration.

Landmark Table​

The tool displays a table with landmark coordinates:

ColumnDescription
#Landmark index
X, Y, Z (mm)World coordinates of the landmark point

Use the table toolbar to:

  • Add new landmarks
  • Remove selected landmarks
  • Clear all landmarks
  • Import/Export landmarks from/to files
  • Move Up/Down to reorder landmarks

Registration with Fine-Tuning​

Enable Perform global registration after landmark alignment to:

  1. Apply initial alignment from landmark correspondence.
  2. Automatically refine the alignment using surface or image features.
  3. Achieve higher accuracy than landmark-only registration.

Accuracy Assessment​

After registration, the tool displays:

MetricDescription
Landmark RMSERoot Mean Square Error of landmark positions after registration
Registration RMSEOverall alignment error (if global refinement is enabled)

Global Registration​

Global Registration automatically aligns datasets without manual landmark placement, using surface geometry or image intensity features.

Accessing the Tool​

  1. Navigate to the Image tab in the ribbon.
  2. Click Global Registration in the Transform section.

Registration Types​

The appropriate registration method is selected automatically based on object types:

Fixed ObjectMoving ObjectMethod Used
Surface/Mask/MeshSurface/Mask/MeshSurface-based registration
VolumeVolumeImage-based registration

Surface-Based Registration​

Aligns objects using surface geometry. Suitable for:

  • Surface meshes (STL, CAD models)
  • Mask objects (uses extracted surface)
  • Volume meshes

Algorithms​

AlgorithmDescription
Point matchingIterative closest point (ICP) algorithm that minimizes point-to-point distances
Feature matchingAligns based on geometric feature descriptors
Point + Feature matchingUses feature matching for initial alignment, then point matching for refinement

Point Matching Parameters​

ParameterDescription
ModeTransformation type: Rigid, Similarity, or Affine
Maximum landmarksMaximum number of landmarks sampled from the surface
Match centroidsIf enabled, align object centroids before registration

Feature Matching Parameters​

ParameterDescription
Global iterationsNumber of times the algorithm runs
Overlap radiusOptimization radius around each point
Curvature thresholdThreshold for feature detection (smaller = higher accuracy)

Point + Feature Matching Parameters​

Combines both parameter sets for a two-stage registration process.

Image-Based Registration​

Aligns volumes using voxel intensity information. Suitable for:

  • CT-to-CT alignment
  • MRI-to-MRI alignment
  • Multi-modal registration (with appropriate configuration)

Registration Methods​

MethodDescription
Rigid (6 DOF)6 degrees of freedom: 3 rotations + 3 translations
Affine (12 DOF)12 degrees of freedom: includes rotation, translation, scaling, and shearing

The same object under a rigid transform, which rotates and moves it, a similarity transform, which also scales it uniformly, and an affine transform, which also scales it per axis and shears it

Parameters​

ParameterDescription
Number of iterationsMaximum iterations for the optimization algorithm
Learning rateStep size for the optimization process
Relaxation factorControls convergence speed and stability

Workflow​

  1. Open the Global Registration tool.
  2. Select the fixed object (reference).
  3. Select moving object(s) to be aligned.
  4. Choose registration parameters (or use defaults).
  5. Optionally enable Calculate RMSE to assess registration quality.
  6. Click Apply to perform the registration.

Output​

After successful registration:

  • Moving objects are transformed to align with the fixed object.
  • The transformation matrix is applied to all selected moving objects.
  • RMSE values are displayed if enabled.

Best Practices​

Landmark Placement​

  • Choose features visible in both datasets.
  • Use anatomical landmarks (e.g., bone prominences, vessel bifurcations).
  • Distribute landmarks across the region of interest.
  • Avoid placing landmarks on noise or artifacts.

Pre-Processing​

  • Coarse manual alignment: Position datasets approximately before automatic registration.
  • Cropping: Remove irrelevant regions to improve registration speed and accuracy.
  • Smoothing: Reduce noise for better feature matching.

Validation​

  • Visually inspect alignment in orthogonal views.
  • Use overlay or checkerboard visualization to compare aligned datasets.
  • Check RMSE values; lower values indicate better alignment.
Medical Disclaimer

Registration results should be verified by qualified professionals before use in clinical decision-making. Automatic registration algorithms may produce suboptimal results in certain cases.

Scripting​

Registration operations are available via the Python scripting API using the RegistrationOperations class.

global_registration() performs the Global Registration and landmark_registration() performs the Landmark Registration, with the same settings as the tools. The first object in the movable objects list plays the role of the movable object selected in the tool: it is the object registered to the fixed object, and every movable object is transformed with the result.

A registration applied from either tool is listed in the Operation Log with its settings, including the landmark coordinates, and offers the matching Python call.

Under the registration, the Operation Log lists the transformation applied to the volumes, surfaces, volume meshes, measurements and primitives, and each offers its own Python call. When the fixed object is not a volume or mask, volumes keep their origin, spacing and dimensions, which the call repeats with transform() and keepImageGrid set to True. When the fixed object is a volume or mask, volumes are resampled onto its image grid, which the call repeats with transform_to_image_grid().

Requested fine-tuning still runs when the landmarks need no alignment. If fine-tuning needs no further transformation after landmark alignment, the registration remains successful and its Python call is available.

See the RegistrationOperations API Reference for the parameters and results of both methods.