The present invention discloses a registration method based on three-dimensional
retinal OCT images, which relates to the technical field of OCT
image registration, and includes the following steps: in the registration process of OCT images, firstly, the
anatomical feature points of the
retina are used as the key reference for basic alignment to perform preliminary registration to eliminate global mismatch errors; after the preliminary registration is completed, the OCT image is divided into a number of sub-areas with equal areas, so that each sub-area is used as an independent analysis unit, which is convenient for subsequent accurate analysis of the local optical characteristics of each analysis unit. The present invention eliminates global errors through preliminary registration of
retinal anatomical feature points, combines
image segmentation with abnormal
signal extraction, uses a
machine learning model to intelligently identify healthy and
scar tissue areas, and dynamically adjusts the weight to prioritize healthy areas, thereby reducing the interference of
scars on registration, improving registration reliability, and reducing clinical misjudgments, providing
technical support for accurate diagnosis and treatment of
retinal diseases.