Real-time retinal layer segmentation of OCT images: from graph cut to deep learning (Conference Presentation)

Segmentation of the retinal layers in OCT images is the critical step in analyzing OCT volumetric data for diagnosis and monitoring of retinal disease progression. Real-time retinal layer segmentation has become increasingly desirable with the increasing OCT acquisition speed. In this work we explored methods to accelerate image processing method to segment retinal layers in OCT B-scan images including graph cut and deep learning. We demonstrated ~30-ms and ~3-ms segmentation of 7 retina layers per OCT B-scan with graph cut and deep learning respectively. The accelerated OCT B-scan segmentation was then integrated with our GPU OCT image acquisition software.