MIA_Registration

What is image registration? And how?

Establishing correspondence between features in sets of images, and using transformation models to infer correspondence away from those features Overlay of a two or a set of images Apply a given transformation until a given matching criteria is fulfilled à optimization process Goal is to find a transformation T, such we minimize a criteria to singularity

Image registration, what for?

Change detection à Look for differences in the same type of images (E.g., Mapping Pre and post contrast agent, Mapping structural changes due to function, disease/treatment progress) Image Fusion à MRI – CT, MRI-PET etc. à Correlation information across modalities Pre and post operative comparison Intra operative guided neurosurgery Atlas creation

Why is image registration needed?

If we want to fuse different image types or see a change between a period of time, we have to scan de patient multiple times à remove from scanner We cannot easily fix/know patient location and orientation with respect to different imaging systems Need to remove differences in patient positioning to relate information from different types of images

What means mono-modal?

When we have same image modalities of two images à CT – CT, MRI – MRI

What means multi-modal?

When we have different image modalities of two images à CT – MRI, CT – PET

What are the four types of transformations

Rigid à simple Similarity (poly-)affine, Non-rigid à complex

What are the different types of information?

Intensity-bases à pure intensity of pixels Non-intensity-based

What for different dimensionality we can have?

-       2D – 2D 3D – 3D 2D – 2D

How is the transformation from the grid space to the “real space” known? (three points)

Image Origin Image dimensions Voxel spacing (or voxel size)

What is the difference between a Eulerian frame and a Lagrangian frame?

Eulerian: Just object is transformed à grid not à flow of material over time Grid with object is transformed à material fix to grid

How many DoF has translation transformation?

3 DoF à x, y, z

How many DoF has anisotropic scaling?

3 DoF à Scaling in x, y, z

How many DoF has rigid transformation?

6 DoF à 3 translation, 3 rotations Preserves distances between points Preserves angels

How many DoF has similarity?

9 DoF à 3 translation, 3 rotation, 3x scaling Angles are preserved Distances changed by a fixed ratio Keeps shape

How many Dof has affine transformation

12 DoF A shearing (3 DoF) à Matrix U An isotropic scaling (3 DoF) à Matrix S A rotation (3 DoF) à Matrix R A translation (3 DoF) à Vector t

What is A and B describing?

-       A: describe rotations, shear, scaling B: describe translation

What is used to compute a translation which is feature-based?

Uses points, landmarks, curves, etc. to compute a transformation Intrinsic (part of the anatomy) or extrinsic (fiducial point) Similarity is based on an Euclidean distance

What is used to compute a translation which is intensity-based?

similarity constructed based on voxel intensity information

What is meant by Procrustes?

Optimal fitting problem of least square type: Given two sets of N corresponding points {xi} and {yi}, find the rigid-body transformation (rotation matrix R and translation vector t) that minimizes the mean squared distance between the points Closed-form solution for rigid case. Non-rigid registration requires iterative solution

What is the basic method of iterative closest point algorithm (ICP)?

Surface-to-point-cloud rigid alignment