Open main menu
Home
Random
Recent changes
Special pages
Community portal
Preferences
About Wikipedia
Disclaimers
Incubator escapee wiki
Search
User menu
Talk
Dark mode
Contributions
Create account
Log in
Editing
Image registration
(section)
Warning:
You are not logged in. Your IP address will be publicly visible if you make any edits. If you
log in
or
create an account
, your edits will be attributed to your username, along with other benefits.
Anti-spam check. Do
not
fill this in!
=== Similarity measures for image registration === Image similarities are broadly used in [[medical imaging]]. An image [[similarity measure]] quantifies the degree of similarity between intensity patterns in two images.<ref name="AG"/> The choice of an image similarity measure depends on the modality of the images to be registered. Common examples of image similarity measures include [[cross-correlation]], [[mutual information]], sum of squared intensity differences, and ratio image uniformity. Mutual information and normalized mutual information are the most popular image similarity measures for registration of multimodality images. Cross-correlation, sum of squared intensity differences and ratio image uniformity are commonly used for registration of images in the same modality. Many new features have been derived for cost functions based on matching methods via [[Computational anatomy|large deformations]] have emerged in the field [[Computational anatomy|Computational Anatomy]] including [[Computational anatomy#Measure matching: unregistered landmarks|Measure matching]] which are pointsets or landmarks without correspondence, [[Computational anatomy#Curve matching|Curve matching]] and [[Computational anatomy#Surface matching|Surface matching]] via mathematical [[Current (mathematics)|currents]] and varifolds.
Edit summary
(Briefly describe your changes)
By publishing changes, you agree to the
Terms of Use
, and you irrevocably agree to release your contribution under the
CC BY-SA 4.0 License
and the
GFDL
. You agree that a hyperlink or URL is sufficient attribution under the Creative Commons license.
Cancel
Editing help
(opens in new window)