  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.
