Pan Lingjiao, Chen Xinjian
IEEE Rev Biomed Eng. 2023;16:307-318. doi: 10.1109/RBME.2021.3110958. Epub 2023 Jan 5.
Retinal image registration is a critical task in the diagnosis and treatment of various eye diseases. And as a relatively new imaging method, optical coherence tomography (OCT) has been widely used in the diagnosis of retinal diseases. This paper is devoted to retinal OCT image registration methods and their clinical applications. Registration methods including volumetric transformation-based registration methods and image features-based registration methods are systematically reviewed. Furthermore, to better understanding these methods, their applications in correcting scanning artifacts, reducing speckle noise, fusing and splicing images and evaluating longitudinal disease progression are studied as well. At the end of this paper, registration of retina with serious pathology and registration with deep learning technique are also discussed.
视网膜图像配准是各种眼科疾病诊断和治疗中的一项关键任务。作为一种相对较新的成像方法,光学相干断层扫描(OCT)已广泛应用于视网膜疾病的诊断。本文致力于视网膜OCT图像配准方法及其临床应用。系统综述了包括基于体积变换的配准方法和基于图像特征的配准方法在内的配准方法。此外,为了更好地理解这些方法,还研究了它们在校正扫描伪影、减少斑点噪声、融合和拼接图像以及评估疾病纵向进展方面的应用。在本文结尾,还讨论了严重病变视网膜的配准以及深度学习技术的配准。