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Registration of OCT Fundus Images with Color Fundus Images Based on Invariant Features

机译：基于不变性特征的OCT眼底图像与彩色眼底图像配准

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摘要

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 urn) in different qualities for both of color fundus images and OCT fundus images.
机译：疾病诊断和治疗通常由从同一患者获得的多个图像来支持。多峰视网膜眼底图像配准技术是整合从多个眼底图像获得的信息以进行全面理解的基础。在本文中，我们基于不变性特征提出了一种将OCT眼底图像（OFI）与彩色眼底照片（CFP）配准的算法。基于视网膜眼底图像的血管脊来定义局部相似性函数。根据局部最大相似度函数，我们可以提取有效图像块，然后获取特征匹配点。我们最终可以通过使用二次曲面模型计算变换矩阵参数来实现配准。该算法在包含3只正常眼和18只具有年龄相关性黄斑变性的眼睛的样本集上进行了测试。实验表明，该方法对彩色眼底图像和OCT眼底图像在不同质量下具有较高的准确度（均方根误差为111.06 urn）。

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