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Comparison of image registration methods for composing spectral retinal images

机译：构成光谱视网膜图像的图像配准方法的比较

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摘要

Spectral retinal images have significant potential for improving the early detection and visualization of subtle changes due to eye diseases and many systemic diseases. High resolution in both the spatial and the spectral domain can be achieved by capturing a set of narrow-band channel images from which the spectral images are composed. With imaging techniques where the eye movement between the acquisition of the images is unavoidable, image registration is required. As manual registration of the channel images is laborious and prone to error, a suitable automatic registration method is necessary. In this paper, the applicability of a set of image registration methods for the composition of spectral retinal images is studied. The registration methods are quantitatively compared using synthetic channel image data of an eye phantom and a semisynthetic set of retinal channel images generated by using known transformations. The experiments show that generalized dual-bootstrap iterative closest point method outperforms the other evaluated methods in registration accuracy, measured in pixel error, and the number of successful registrations. (C) 2017 Elsevier Ltd. All rights reserved.
机译：视网膜光谱图像具有巨大的潜力，可以改善由于眼疾和许多系统疾病引起的细微变化的早期检测和可视化。可以通过捕获一组窄带通道图像来构成空间图像和光谱域中的高分辨率，光谱图像是由这些图像组成的。对于其中在图像的获取之间不可避免的眼睛移动的成像技术，需要图像配准。由于手动注册频道图像比较费力并且容易出错，因此需要一种合适的自动注册方法。在本文中，研究了一套图像配准方法在光谱视网膜图像合成中的适用性。使用眼幻影的合成通道图像数据和通过使用已知转换生成的半合成视网膜通道图像集对配准方法进行定量比较。实验表明，广义的双引导迭代最近点法在配准精度，像素误差和成功配准的数量方面优于其他评估方法。 （C）2017 Elsevier Ltd.保留所有权利。

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