Hernandez-Matas Carlos, Zabulis Xenophon, Argyros Antonis A
Annu Int Conf IEEE Eng Med Biol Soc. 2017 Jul;2017:377-381. doi: 10.1109/EMBC.2017.8036841.
This work regards an investigation of the accuracy of a state-of-the-art, keypoint-based retinal image registration approach, as to the type of keypoint features used to guide the registration process. The employed registration approach is a local method that incorporates the notion of a 3D retinal surface imaged from different viewpoints and has been shown, experimentally, to be more accurate than competing approaches. The correspondences obtained between SIFT, SURF, Harris-PIIFD and vessel bifurcations are studied, either individually or in combinations. The combination of SIFT features with vessel bifurcations was found to perform better than other combinations or any individual feature type, alone. The registration approach is also comparatively evaluated against representative methods of the state-of-the-art in retinal image registration, using a benchmark dataset that covers a broad range of cases regarding the overlap of the acquired images and the anatomical characteristics of the imaged retinas.
这项工作是关于一种基于关键点的视网膜图像配准方法的准确性研究，该方法代表了当前的技术水平，涉及用于指导配准过程的关键点特征类型。所采用的配准方法是一种局部方法，它纳入了从不同视角对三维视网膜表面进行成像的概念，并且通过实验表明，该方法比其他竞争方法更准确。研究了在尺度不变特征变换（SIFT）、加速鲁棒特征（SURF）、哈里斯 - 相位不变特征点检测器（Harris - PIIFD）和血管分叉点之间获得的对应关系，这些对应关系可以单独研究，也可以组合研究。结果发现，SIFT特征与血管分叉点的组合比其他组合或任何单独的特征类型表现更好。此外，使用一个基准数据集，该数据集涵盖了关于采集图像的重叠以及成像视网膜的解剖特征等广泛案例，将该配准方法与视网膜图像配准领域当前技术水平的代表性方法进行了比较评估。
