Medical Image Registration and Its Application in Retinal Images: A Review
This is an incremental review that helps audiences quickly understand the development of medical image registration, particularly for disease diagnosis and treatment in medical imaging.
The paper provides a comprehensive review of medical image registration methods, including traditional and deep learning-based approaches, with a focus on summarizing methodologies and highlighting recent advances and challenges in retinal image registration.
Medical image registration is vital for disease diagnosis and treatment with its ability to merge diverse information of images, which may be captured under different times, angles, or modalities. Although several surveys have reviewed the development of medical image registration, these surveys have not systematically summarized methodologies of existing medical image registration methods. To this end, we provide a comprehensive review of these methods from traditional and deep learning-based directions, aiming to help audiences understand the development of medical image registration quickly. In particular, we review recent advances in retinal image registration at the end of each section, which has not attracted much attention. Additionally, we also discuss the current challenges of retinal image registration and provide insights and prospects for future research.