Open AccessLocalization of diabetic macular edema areas via graph-based segmentation of OCT retinal images
Author(s) -
Nataly Ilyasova,
A. S. Shirokanev,
Н. С. Демин,
Evgeniy Zamyckij
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1368/3/032014
Subject(s) - segmentation , retinal , artificial intelligence , diabetic macular edema , macular edema , image segmentation , computer science , ophthalmology , graph , computer vision , edema , diabetic retinopathy , medicine , pattern recognition (psychology) , diabetes mellitus , surgery , theoretical computer science , endocrinology
We propose a technique for localization of diabetic macular edema areas via graph-based segmentation of OCT retinal images. The relevance of the research is associated with the high incidence rate of severe eye conditions due to diabetic macular edema among the world population. The technique relies upon a highly efficient graph-based image segmentation. Using a set of specially selected parameters, the accuracy of retinal area segmentation is enhanced. Optimal parameters found in the course of research have enabled a segmentation error of 2% to be achieved.