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Validation of Retinal Image Registration Algorithms by a Projective Imaging Distortion Model

机译：投影成像畸变模型对视网膜图像配准算法的验证

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摘要

Fundus camera imaging of the retina is widely used to document ophthalmologic disorders including diabetic retinopathy, glaucoma, and age-related macular degeneration. The retinal images typically have a limited field of view due mainly to the curvedness of human retina, so multiple images are to be joined together using image registration technique to form a montage with a larger field of view. A variety of methods for retinal image registration have been proposed, but evaluating such methods objectively is difficult due to the lack of a reference standard for the true alignment of the individual images that make up the montage. A method of generating simulated retinal image set by modeling geometric distortions due to the eye geometry and the image acquisition process is described in this paper. We also present the validation tool for any retinal image registration method by tracing back the distortion path and accessing the geometric misalignment from the coordinate system of reference standard. The quantitative comparison for different registration methods is given in the experiment, so the registration performance is evaluated in an objective manner.
机译：视网膜的眼底照相机成像被广泛用于记录眼科疾病，包括糖尿病性视网膜病，青光眼和与年龄有关的黄斑变性。视网膜图像通常主要由于人类视网膜的弯曲而具有有限的视野，因此将使用图像配准技术将多个图像连接在一起以形成具有较大视野的蒙太奇。已经提出了多种用于视网膜图像配准的方法，但是由于缺乏用于构成蒙太奇的单个图像的真实对准的参考标准，因此客观地评估这种方法是困难的。本文介绍了一种通过对由于眼睛几何形状和图像采集过程引起的几何畸变建模来生成模拟视网膜图像集的方法。我们还通过追溯变形路径并从参考标准的坐标系中访问几何未对准，提出了用于任何视网膜图像配准方法的验证工具。实验中给出了不同配准方法的定量比较，从而客观地评价了配准性能。

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