Background and Objective: The study of small vessels allows for the analysis and diagnosis of diseases with strong vasculopathy. This type of vessels can be observed non-invasively in the retina via fundoscopy. The analysis of these vessels can be facilitated by applications built upon Retinal Image Registration (RIR), such as mosaicing, Super Resolution (SR) or eye shape estimation. RIR is challenging due to possible changes in the retina across time, the utilization of diverse acquisition devices with varying properties, or the curved shape of the retina.

Methods: We employ the Retinal Image Registration through Eye Modelling and Pose Estimation (REMPE) framework, which simultaneously estimates the cameras’ relative poses, as well as eye shape and orientation to develop RIR applications and to study their effectiveness.

Results: We assess quantitatively the suitability of the REMPE framework towards achieving SR and eye shape estimation. Additionally, we provide indicative results demonstrating qualitatively its usefulness in the context of longitudinal studies, mosaicing, and multiple image registration. Besides the improvement over registration accuracy, demonstrated via registration applications, the most important novelty presented in this work is the eye shape estimation and the generation of 3D point meshes. This has the potential for allowing clinicians to perform measurements on 3D representations of the eye, instead of doing so in 2D images that contain distortions induced because of the projection on the image space.

Conclusions: RIR is very effective in supporting applications such as SR, eye shape estimation, longitudinal studies, mosaicing and multiple image registration. Its improved registration accuracy compared to the state of the art translates directly in improved performance when supporting the aforementioned applications.

背景与目的：对小血管的研究可以分析和诊断强血管病。可以通过眼底镜在视网膜中无创地观察到这种类型的血管。这些血管的分析可以通过基于视网膜图像配准（RIR）的应用程序来促进，例如镶嵌，超分辨率（SR）或眼睛形状估计。由于视网膜随时间可能发生变化，使用具有不同属性的各种采集设备或视网膜的弯曲形状，因此RIR具有挑战性。

方法：我们通过眼睛建模和姿势估计（REMPE）框架使用视网膜图像配准，该框架同时估计摄像机的相对姿势以及眼睛的形状和方向，以开发RIR应用程序并研究其效果。

结果：我们定量评估了REMPE框架对实现SR和眼睛形状估计的适用性。此外，我们提供了指示性结果，从质量上证明了其在纵向研究，镶嵌和多图像配准的背景下的有用性。除了通过套准应用证明的套准精度的提高之外，这项工作中提出的最重要的新颖性是眼睛形状估计和3D点网格的生成。这有可能允许临床医生对眼睛的3D表示进行测量，而不是在包含因图像空间上的投影而引起的变形的2D图像中执行测量。

结论：RIR在支持SR，眼睛形状估计，纵向研究，镶嵌和多图像配准等应用方面非常有效。与现有技术相比，其改进的配准精度可直接支持支持上述应用的性能。