VMseg: Using spatial variance to automatically segment retinal non-perfusion on OCT-angiography.

ABSTRACT:

Background and objectives

To develop and test VMseg, a new image processing algorithm performing automatic segmentation of retinal non-perfusion in widefield OCT-Angiography images, in order to estimate the non-perfusion index in diabetic patients.

Methods

We included diabetic patients with severe non-proliferative or proliferative diabetic retinopathy. We acquired images using the PlexElite 9000 OCT-A device with a photomontage of 5 images of size 12 x 12 mm. We then developed VMseg, a Python algorithm for non-perfusion detection, which binarizes a variance map calculated through convolution and morphological operations. We used 70% of our data set (development set) to fine-tune the algorithm parameters (convolution and morphological parameters, binarization thresholds) and

SUBMITTER: LE Boite H 

PROVIDER: S-EPMC11305542 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature