Cynomolgus monkey's choroid reference database derived from hybrid deep learning optical coherence tomography segmentation.

ABSTRACT: Cynomolgus monkeys exhibit human-like features, such as a fovea, so they are often used in non-clinical research. Nevertheless, little is known about the natural variation of the choroidal thickness in relation to origin and sex. A combination of deep learning and a deterministic computer vision algorithm was applied for automatic segmentation of foveolar optical coherence tomography images in cynomolgus monkeys. The main evaluation parameters were choroidal thickness and surface area directed from the deepest point on OCT images within the fovea, marked as the nulla with regard to sex and origin. Reference choroid landmarks were set underneath the nulla and at 500 µm intervals laterally up to a distance of 2000 µm nasally and temporally, complemented by a sub-analysis of the central bouqu

SUBMITTER: Maloca PM 

PROVIDER: S-EPMC9346135 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature