Paper Info
Title
Registration Of Oct Fundus Images With Color Fundus Images Based On Invariant Features
Abstract
Disease diagnosis and treatment are often supported by multiple images acquired from the same patient. Multimodal retinal fundus image registration techniques are fundamental to integrate the information gained from several fundus images for a comprehensive understanding. In this paper, we proposed an algorithm for registration of OCT fundus images (OFIs) with color fundus photographs (CFPs) based on invariant features. The local similarity function is defined based on the blood vessel ridges of retinal fundus images. According to the local maximum similarity function, we can extract effective image blocks and then acquire the feature matching points. We can finally achieve the registration by utilizing the quadratic surface model to calculate the transformation matrix parameters. The proposed algorithm was tested on a sample set containing 3 normal eyes and 18 eyes with age-related macular degeneration. The experiment demonstrates that the proposed method has high accuracy (root mean square error is 111.06 mu m) in different qualities for both of color fundus images and OCT fundus images.
Year
DOI
Venue
2017
10.1007/978-3-319-68542-7_40
CLOUD COMPUTING AND SECURITY, PT II
Keywords
Field
DocType
Multimodal retinal image registration, Color fundus images, OCT fundus images, Similarity function, Quadratic surface model
Computer vision,Computer science,Fundus (eye),Real-time computing,Feature matching,Invariant (mathematics),Artificial intelligence,Fundus image
Conference
Volume
ISSN
Citations 
10603
0302-9743
0
PageRank 
References 
Authors
0.34
7
4
Name
Order
Citations
PageRank
Ping Li17814.22
Qiang Chen260457.44
Wen Fan3258.84
Songtao Yuan4134.62