Publication: Automated classification between age-related macular degeneration and Diabetic macular edema in OCT image using image segmentation
No. of Pages/File Size
BMEiCON 2014 - 7th Biomedical Engineering International Conference. (2015)
Jathurong Sugmk, Supapom Kiattisin, Adisom Leelasantitham (2015). Automated classification between age-related macular degeneration and Diabetic macular edema in OCT image using image segmentation. Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/35919.
Automated classification between age-related macular degeneration and Diabetic macular edema in OCT image using image segmentation
© 2014 IEEE. Age-related macular degeneration (AMD) and Diabetic macular edema (DME) are to lead causes to make a visual loss in people. People are suffered from the use of many time to diagnose and to wait for treatment both of diseases. This paper proposes a step of image segmentation to be divided the optical coherence tomography (OCT) to find the retinal pigment epithelium (RPE) layer and to detect a shape of drusen in RPE layer. Then, the RPE layer is used for finding retinal nerve fiber layer (RNFL) and for detecting a bubble of blood area in RNFL complex. Finally, this method uses a binary classification to classify two diseases characteristic between AMD and DME. We use 16 OCT images of a case study to segmentation and classify two diseases. In the experimental results, 10 images of AMD and 6 images of DME can be detected and classified to accuracy of 87.5%.