DocumentCode
2416839
Title
Retinal image registration based on salient feature regions
Author
Zheng, Jian ; Tian, Jie ; Dai, Yakang ; Deng, Kexin ; Chen, Jian
Author_Institution
Key Lab. of Complex Syst. & Intell. Sci., Chinese Acad. of Sci., Beijing, China
fYear
2009
fDate
3-6 Sept. 2009
Firstpage
102
Lastpage
105
Abstract
Retinal image registration is essential and crucial for ophthalmologists to diagnose various diseases. A great number of methods have been developed to solve this problem, however, fast and accurate retinal image registration is still a challenging problem since the great content complexity and low image quality of the unhealthy retina. This paper provides a new retinal image registration method based on salient feature regions (SFR). We first extract the SFR in each image based on a well defined region saliency metric. Next, SFR are matched by using an innovative local feature descriptor. Then we register those matched SFR using local rigid transformation. Finally, we register the two images adopting global second order polynomial transformation with locally rigid registered region centers as control points. Experimental results prove that our method is very fast and accurate, especially quite effective for the low quality retinal images registration.
Keywords
eye; feature extraction; image registration; medical image processing; global second order polynomial transformation; image registration; local feature descriptor; local rigid transformation; retina; salient feature region extraction; Algorithms; Artificial Intelligence; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Pattern Recognition, Automated; Reproducibility of Results; Retina; Retinoscopy; Sensitivity and Specificity; Subtraction Technique;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
Conference_Location
Minneapolis, MN
ISSN
1557-170X
Print_ISBN
978-1-4244-3296-7
Electronic_ISBN
1557-170X
Type
conf
DOI
10.1109/IEMBS.2009.5334778
Filename
5334778
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