Classifying DME vs Normal SD-OCT volumes: A review
| Affiliation auteurs | !!!! Error affiliation !!!! |
| Titre | Classifying DME vs Normal SD-OCT volumes: A review |
| Type de publication | Conference Paper |
| Year of Publication | 2016 |
| Auteurs | Massich J, Rastgoo M, Lemaitre G, Cheung CY, Wong TY, Sidibe D, Meriaudeau F |
| Conference Name | 2016 23RD INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR) |
| Publisher | Int Assoc Pattern Recognit; Int Conf Pattern Recognit, Org Comm; Elsevier; IBM Res; INTEL; CONACYT |
| Conference Location | 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA |
| ISBN Number | 978-1-5090-4847-2 |
| Mots-clés | benchmark, Diabetic Macular Edema (DME), Machine Learning (ML), Spectral Domain OCT (SD-OCT) |
| Résumé | This article reviews the current state of automatic classification methodologies to identify Diabetic Macular Edema (DME) versus normal subjects based on Spectral Domain OCT (SD-OCT) data. Addressing this classification problem has valuable interest since early detection and treatment of DME play a major role to prevent eye adverse effects such as blindness. The main contribution of this article is to cover the lack of a public dataset and benchmark suited for classifying DME and normal SD-OCT volumes, providing our own implementation of the most relevant methodologies in the literature. Subsequently, 6 different methods were implemented and evaluated using this common benchmark and dataset to produce reliable comparison. |