Quality maps for optical coherence tomography angiography

Abstract

A system, method, and/or device for determinizing a quality measure of OCT structural data and/or OCTA functional data uses a machine learning model trained to provide a single overall quality measure, or a quality map distribution for the OCT/OCTA data based on the generation of multiple features maps extracted from one or more slab views of the OCT/OCTA data. The extracted feature maps may be different texture-type maps, and the machine model is trained to determine the quality measure based on the texture maps.

Dependencies are inferred from the claim text.