Work

Classifying DME vs normal SD-OCT volumes: A review

Year: 2016

Type: conference-paper

Abstract: 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.

Source: Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition

DOI: 10.1109/icpr.2016.7899816

Authors: Joan Massich, Mojdeh Rastgoo, Guillaume Lemaitre, Carol Y. Cheung, Tien Y. Wong, Desire Sidibe, Fabrice Meriaudeau

Institutions: Université Bourgogne Franche-Comté, Laboratoire d’Électronique, Informatique et Image, Singapore National Eye Center, Singapore Eye Research Institute, Universiti Teknologi Petronas

Language: English

Topic: Retinal Imaging and Analysis

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W2528463361

FWCI: 5.236

Cites: 22

Cited by: 14

Related to: 10