Procrustes Analysis
Published:
Procrustes Analysis refers to the registration between two dataset via a transformation, where elements between datasets have known correspondence. In the context of computer-assisted surgery, Procrustes Analysis menifests as point-to-point, point-to-line, and point-to-surface registration.
For example, $x_i$ may refer to $i^{th}$ fiducial landmark in a CT volume and $y_i$ be the corresponding (annotating the same anatomical feature) fiducial in a MRI volume. Given sufficient number of these corresponding landmarks, these two 3D volumes can be aligned/registered.
In general terms, we assume $x_i$ are 3D points, but $y_i$ can be either 3D points, lines, or planes.
Point-to-Point
- Orthogonal Procrustes Analysis with isotropic scaling
- Orthogonal Procrustes Analysis with anisotropic scaling
- Orthogonal Procrustes Analysis with anisotropic weighting