Novel layer segmentation algorithm for optical coherence tomography images
Technology description
Background
There exist algorithms to measure the entire thickness of the retina and NFL, they are not capable of segment retina into the above mentioned sub-layers. Moreover, with the existing algorithms, it is not possible to measure nerve fiber layer (NFL) thickness on macular region, which may be important for glaucoma assessment.
Technology
University researchers have developed a novel algorithm that enables us to quantify various retinal layers helping ophthalmologists to diagnose and evaluate a variety of disease status including glaucoma, diabetic retinopathy, and age-related macular degeneration. This novel algorithm automatically segments multiple layer structures within a cross-sectional image of the human retina acquired using optical coherence tomography (OCT).
Application area
* Diagnoses of ocular diseases involving retina (e.g. glaucoma, diabetic retinopathy etc.)
* Assess progression and status of these pathologies
* OCT users
Advantages
* First working algorithm for retinal segmentation on OCT images that measures thickness of the following 5 important retinal layers.