Medical Image Registration: Theory, Algorithm, and Case Studies in Surgical Simulation, Chest Cancer, and Multiple Sclerosis - Biomedical Image Analysis - page 4

[1] provided a good survey on different classification criteria. In this section we
will summarize seven basic classification criteria commonly used (for more
details and further reading see the Maintz and Viergever review).
The seven criteria are:

1. Dimensionality

2. Nature of registration basis

3. Nature of transformation

4. Interaction

5. Optimization procedure

6. Modalities involved

7. Subject

1.2.1 Dimensionality

The main division here is either the scope of the registration involves spatial
dimension only or is time series also involved. For spacial registration, there
are the (i) 3D/3D registration where two or more volumes of interest are to be
aligned together, the (ii) 2D/2D registration where two medical images are to be
aligned together. In general, 2D/2D registration is less complex than the 3D/3D
registration. A more complex one is the (iii) 2D/3D registration which involves
the direct alignment of spatial data to projective data (e.g., a preoperative CT
image to an intraoperative X-ray image), or the alignment of a single tomographic
slice to spatial data. Time can be another dimension involved when the patient's
images and volumes are to be tracked with time for analysis or monitoring.

1.2.2 Nature of Registration Basis

In this category registration can be divided into extrinsic , i.e., based on foreign
objects introduced into the imaged space, and intrinsic methods, i.e., based
on the image information as generated by the patient. Extrinsic methods rely
on artificial objects attached to the patient, objects which are designed to be
well visible and accurately detectable in all of the pertinent modalities. As such,