title: An anomaly detection approach for the identification of DME patients using spectral domain optical coherence tomography images.
abstract: This paper proposes a method for automatic classification of spectral domain OCT data for the identification of patients with retinal diseases such as Diabetic Macular Edema (DME). We address this issue as an anomaly detection problem and propose a method that not only allows the classification of the OCT volume, but also allows the identification of the individual diseased B-scans inside the volume. Our approach is based on modeling the appearance of normal OCT images with a Gaussian Mixture Model (GMM) and detecting abnormal OCT images as outliers. The classification of an OCT volume is based on the number of detected outliers. Experimental results with two different datasets show that the proposed method achieves a sensitivity and a specificity of 80% and 93% on the first dataset, and 100% and 80% on the second one. Moreover, the experiments show that the proposed method achieves better classification performance than other recently published works.
authors.affiliation: LE2I, UMR6306, CNRS, Arts et Métiers, Université de Bourgogne-Franche Comté, F-21000 Dijon, France. Electronic address: dro-desire.sidibe@u-bourgogne.fr.
authors.forename: Désiré
authors.initials: D
authors.lastname: Sidibé
authors.affiliation: LE2I, UMR6306, CNRS, Arts et Métiers, Université de Bourgogne-Franche Comté, F-21000 Dijon, France.
authors.forename: Shrinivasan
authors.initials: S
authors.lastname: Sankar
authors.affiliation: LE2I, UMR6306, CNRS, Arts et Métiers, Université de Bourgogne-Franche Comté, F-21000 Dijon, France.
authors.forename: Guillaume
authors.initials: G
authors.lastname: Lemaître
authors.affiliation: LE2I, UMR6306, CNRS, Arts et Métiers, Université de Bourgogne-Franche Comté, F-21000 Dijon, France.
authors.forename: Mojdeh
authors.initials: M
authors.lastname: Rastgoo
authors.affiliation: LE2I, UMR6306, CNRS, Arts et Métiers, Université de Bourgogne-Franche Comté, F-21000 Dijon, France.
authors.forename: Joan
authors.initials: J
authors.lastname: Massich
authors.affiliation: Singaore Eye Research Institute, Singapore National Eye Center, Singapore; Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong.
authors.forename: Carol Y
authors.initials: CY
authors.lastname: Cheung
authors.affiliation: Singaore Eye Research Institute, Singapore National Eye Center, Singapore.
authors.forename: Gavin S W
authors.initials: GSW
authors.lastname: Tan
authors.affiliation: Singaore Eye Research Institute, Singapore National Eye Center, Singapore.
authors.forename: Dan
authors.initials: D
authors.lastname: Milea
authors.affiliation: Singaore Eye Research Institute, Singapore National Eye Center, Singapore.
authors.forename: Ecosse
authors.initials: E
authors.lastname: Lamoureux
authors.affiliation: Singaore Eye Research Institute, Singapore National Eye Center, Singapore.
authors.forename: Tien Y
authors.initials: TY
authors.lastname: Wong
authors.affiliation: LE2I, UMR6306, CNRS, Arts et Métiers, Université de Bourgogne-Franche Comté, F-21000 Dijon, France; Center for Intelligent Signal and Imaging Research (CISIR), EEE Department, Universiti Teknologi Petronas, 32610 Seri Iskandar, Perak, Malaysia.
authors.forename: Fabrice
authors.initials: F
authors.lastname: Mériaudeau
mesh_terms: D048909:Diabetes Complications / Q000150:complications / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D008269:Macular Edema / Q000150:complications / Q000000981:diagnostic imaging*; D008297:Male; D041623:Tomography, Optical Coherence
keywords: Anomaly detection; Classification; Diabetic macular edema; Diabetic retinopathy; SD-OCT