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Issue title: Recent Innovations on Biomedical Engineering
Guest editors: Wen-Hsiang Hsieh
Article type: Research Article
Authors: Jo, Eun Byeola | Lee, Ju Hwanb | Hwang, Yoo Nab | Kim, Sung Mina; b; *
Affiliations: [a] Department of Medical Biotechnology, Dongguk University-Bio Medi Campus, Seoul, Korea | [b] Department of Medical Devices Industry, Dongguk University-Seoul, Seoul, Korea
Correspondence: [*] Corresponding author: Sung Min Kim, Department of Medical Biotechnology, Dongguk University-Bio Medi Campus, 32, Dongguk-ro, Ilsan Dong-gu, Goyang-si, Gyeonggi-do, Korea. E-mail:smkim@dongguk.edu
Abstract: In this study, several variables related to the thickness of the retinal layer were measured via optical coherence tomography (OCT), and the clinical applicability of such measurements was evaluated to differentiate between diabetic cystoid macular edema (DCME) and postoperative cystoid macular edema (PCME). To this end, a total of 120 subjects (30 healthy individuals, 60 DCME patients, and 30 PCME patients) were selected as the experimental subjects. The six risk factors included the thicknesses for the total retina (TR), the inner retina (IR), the photoreceptor outer segments (POS), the outer retina (OR), the ganglion cell (GC), and the retinal nerve fiber layer (RNFL), and these were estimated by using a hierarchical approach through observations from OCT image scans. All of the risk factors were obtained from the OCT images captured within a 6-mm diameter from the center of the macula. The results of the experiment indicated that the proposed method can reliably differentiate between DCME and PCME. Moreover, as DCME and PCME progressed, the most significant deterioration was found in the central macular region. These results suggest that the proposed method has clinical applicability for the diagnosis of DCME and PCME from OCT images.
Keywords: Retinal layer, optical coherence tomography, diabetic cystoid macular edema, postoperative cystoid macular edema, hierarchical approach
DOI: 10.3233/THC-151052
Journal: Technology and Health Care, vol. 24, no. s1, pp. S59-S68, 2016
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