Automated retinal boundary segmentation of optical coherence tomography images using an improved Canny operator.

ABSTRACT: Retinal segmentation is a prerequisite for quantifying retinal structural features and diagnosing related ophthalmic diseases. Canny operator is recognized as the best boundary detection operator so far, and is often used to obtain the initial boundary of the retina in retinal segmentation. However, the traditional Canny operator is susceptible to vascular shadows, vitreous artifacts, or noise interference in retinal segmentation, causing serious misdetection or missed detection. This paper proposed an improved Canny operator for automatic segmentation of retinal boundaries. The improved algorithm solves the problems of the traditional Canny operator by adding a multi-point boundary search step on the basis of the original method, and adjusts the convolution kernel. The algorithm was used

SUBMITTER: Liu J 

PROVIDER: S-EPMC8791938 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature