Image registration

Last revised by Daniel J Bell on 26 Aug 2022

Image registration is a process whereby images are brought into spatial correspondence with one another. By registering images into a single coordinate system, one can create fusion images and perform many quantitative analyzes.

Image registration is not restricted to aligning images of the same modality. Hybrid imaging requires image registration and is used to generate more informative images of pathology by combining complementary anatomical information across imaging modalities. 


Most image registration algorithms consist of an iterative process that consists of three main steps:

  1. transformation
  2. cost function
  3. optimization

In image registration, the image we want to register is known as the native image (in its native coordinate space, usually referred to as native space) and the image we want to register to is known as the template image (in template space).

To get an image from native space to template space, we need to apply a transformation. Examples of transformations include rotation, translation, shearing and scaling (or any combination of these). Image registrations restricted to rotation and translation are known as rigid body registrations, and registrations involving all four of these transformations are known as an affine registration. 

Registration of images can also be described in terms of degrees of freedom, which can be given by the number of unique transformations multiplied by the dimensions of the image. For example, a 3D magnetic resonance image registered to a template using only rotation and translation is an example of a rigid body registration. 

Once the transformation is applied, the quality of the registration is assessed using a cost function. The error in the iteration of the registration (quantified by the cost function) is then used to optimize transformation steps.

See also

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