Open AccessReal time Fully Automated Internal Layer Segmentation of Human Retina in Optical Coherence Tomography Images
Author(s) -
YoungMin Han,
Naresh Kumar Ravichandran,
Pilun Kim,
Mansik Jeon,
Jeehyun Kim
Publication year - 2020
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.c5632.029320
Subject(s) - optical coherence tomography , internal limiting membrane , computer science , nerve fiber layer , retinal , segmentation , artificial intelligence , computer vision , retina , frame rate , optics , macular hole , ophthalmology , physics , medicine , visual acuity , vitrectomy
In the field of ophthalmology, optical coherence tomography (OCT) has proven to be a powerful imaging technique when it comes to diagnosing various eye-related diseases. This research article introduces a real-time automatic retinal layer segmentation algorithm based on intensity variation in the OCT images. The built algorithm is capable of detecting internal retinal layers like the internal limiting membrane (ILM), the retinal pigment epithelium (RPE) and the retinal nerve fiber layer (RNFL) with micrometer level precision, the algorithm uses openMP for parallelized computation for real-time visualization of the segmented retinal layers. The total execution time of the algorithm was evaluated using various image sizes and compared with the OCT frame rate to demonstrate the efficiency of real-time segmentation.