Evaluation of the corneal topography based on deep learning.

ABSTRACT:

Purpose

The current study designed a unique type of corneal topography evaluation method based on deep learning and traditional image processing algorithms. The type of corneal topography of patients was evaluated through the segmentation of important medical zones and the calculation of relevant medical indicators of orthokeratology (OK) lenses.

Methods

The clinical data of 1,302 myopic subjects was collected retrospectively. A series of neural network-based U-Net was used to segment the pupil and the treatment zone in the corneal topography, and the decentration, effective defocusing contact range, and other indicators were calculated according to the image processing algorithm. The type of corneal topography was evaluated according to the evaluation criteria given by the

SUBMITTER: Xu S 

PROVIDER: S-EPMC10794654 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature