MSGANet-RAV: A multiscale guided attention network for artery-vein segmentation and classification from optic disc and retinal images.

ABSTRACT:

Background

Retinal and optic disc images are used to assess changes in the retinal vasculature. These can be changes associated with diseases such as diabetic retinopathy and glaucoma or induced using ophthalmodynamometry to measure arterial and venous pressure. Key steps toward automating the assessment of these changes are the segmentation and classification of the veins and arteries. However, such segmentation and classification are still required to be manually labelled by experts. Such automated labelling is challenging because of the complex morphology, anatomical variations, alterations due to disease and scarcity of labelled data for algorithm development. We present a deep machine learning solution called the multiscale guided attention network for retinal artery and vein

SUBMITTER: Chowdhury AZME 

PROVIDER: S-EPMC9732479 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature