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 μm) in different qualities for both of color fundus images and OCT fundus images.
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Acknowledgements
This work was supported by the National Science Foundation of China (61671242), a grant from the Fundamental Research Funds for the Central Universities (30920140111004), a six talent peaks project in Jiangsu Province (2014-SWYY-024), and the Open Fund Project of Fujian Provincial Key Laboratory of Information Processing and Intelligent Control (Minjiang University) (No. MJUKF201706).
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Li, P., Chen, Q., Fan, W., Yuan, S. (2017). Registration of OCT Fundus Images with Color Fundus Images Based on Invariant Features. In: Sun, X., Chao, HC., You, X., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2017. Lecture Notes in Computer Science(), vol 10603. Springer, Cham. https://doi.org/10.1007/978-3-319-68542-7_40
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DOI: https://doi.org/10.1007/978-3-319-68542-7_40
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