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Registration of Optical Coherence Tomography (Oct) of Optic Nerve Head and Fundus Images Using Speeded-Up Robust Features (Surf) and Random Sample Consensus (Ransac) Algorithms



Ahdi A1 ; Rabbani H2 ; Vard A2
Authors
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Authors Affiliations
  1. 1. Department of Biomedical Engineering, School of Medicine AND Student Research Committee, Isfahan University of Medical Sciences, Isfahan, Iran
  2. 2. Department of Biomedical Engineering, School of Advanced Medical Technology, Isfahan University of Medical Sciences, Isfahan, Iran

Source: Journal of Isfahan Medical School Published:2016

Abstract

Background: Registration of images is the process of matching two images of an area or a scene with different conditions or imaging times or taken by different sets to achieve more accurate and detailed information. The purpose of this study was registration of three-dimensional optical coherence tomography (OCT) optic nerve head and fundus images. Methods: Data used in this study were taken via 3D-OCT (Topcon model 1000) and contained images of threedimensional OCT and two-dimensional colored fundus. This study was performed on 40 volunteers with normal eyes. In the first step, the projection of 3D-OCT images was gotten; then, the projection images of extracted vessels of two-dimensional fundus were achieved. Speeded-up robust features (SURF) algorithm was used to find the points and their feature vectors and then to match the feature vectors. In the next step, eliminated outliers points were deleted using Random sample consensus (RANSAC) algorithm. Finally, the scale and the angle for changing optic disc OCT images to be registered with fundus image were achieved. Findings: Combining the projections of OCT and colored fundus images were well done using SURF and RANSAC algorithms. The best obtained parameters were match threshold of 100 in SURF algorithm and maximum distance of 15 in RANSAC algorithm with the mean square errors of 0.0272 and 0.0268, respectively. Due to lack of conversion of projection between the data of OCT and fundus images, for estimating the RANSAC algorithm, similarity function that just adjusted the values of transfer, rotation and scale, would lead to better results. The overall error for the data of 40 normal eyes selecting optimal values of parameters was 0.0038 ± 0.0268. Conclusion: Registration of projection of OCT and fundus images via combining the information of OCT and fundus images can provide valuable anatomical information from the eyes for ophthalmologists. © 2016, Isfahan University of Medical Sciences(IUMS). All rights reserved.
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