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首页> 外文期刊>Journal of computer sciences >MULTIMODAL RETINAL IMAGE REGISTRATION USING RANSAC MATCHING AND GRADIENT ICP ALGORITHM | Science Publications
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MULTIMODAL RETINAL IMAGE REGISTRATION USING RANSAC MATCHING AND GRADIENT ICP ALGORITHM | Science Publications

机译：RANSAC匹配和梯度ICP算法的多模态视网膜图像配准|科学出版物

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摘要

> Multimodal retinal imaging is an important facet of the diagnosis and therapy of retinal disorders like retinopathy, occlusion. Many imaging techniques for multimodal retinal images are developing in the recent years. These novel developments are subjected to a tradeoff between the computational time and effective registration. This study aims at developing a new algorithm based on the RANSAC matching and gradient iterative closest point technique which has proven to have less computational time with the best matched coordinates irrespective of the nature of the input retinal image. This study uses a new adaptive thresholding technique to extract the bifurcations from the target image and the control points are selected using the RANSAC matching algorithm. The registration is achieved by implementing gradient iterative closest point algorithm to minimize the mean square error between the target control points of the base and the reference images.
机译： >多模态视网膜成像是诊断和治疗视网膜疾病（如视网膜病变，闭塞）的重要方面。近年来，用于多模式视网膜图像的许多成像技术正在发展。这些新颖的发展需要在计算时间和有效注册之间进行权衡。这项研究旨在开发一种基于RANSAC匹配和梯度迭代最近点技术的新算法，该算法已被证明具有最佳匹配坐标的计算时间更少，而与输入视网膜图像的性质无关。这项研究使用一种新的自适应阈值技术从目标图像中提取分叉点，并使用RANSAC匹配算法选择控制点。通过实现梯度迭代最近点算法来最小化基本图像和参考图像的目标控制点之间的均方误差，从而实现配准。

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