title: Two-dimensional segmentation of the retinal vascular network from optical coherence tomography.
abstract: The automatic segmentation of the retinal vascular network from ocular fundus images has been performed by several research groups. Although different approaches have been proposed for traditional imaging modalities, only a few have addressed this problem for optical coherence tomography (OCT). Furthermore, these approaches were focused on the optic nerve head region. Compared to color fundus photography and fluorescein angiography, two-dimensional ocular fundus reference images computed from three-dimensional OCT data present additional problems related to system lateral resolution, image contrast, and noise. Specifically, the combination of system lateral resolution and vessel diameter in the macular region renders the process particularly complex, which might partly explain the focus on the optic disc region. In this report, we describe a set of features computed from standard OCT data of the human macula that are used by a supervised-learning process (support vector machines) to automatically segment the vascular network. For a set of macular OCT scans of healthy subjects and diabetic patients, the proposed method achieves 98% accuracy, 99% specificity, and 83% sensitivity. This method was also tested on OCT data of the optic nerve head region achieving similar results.
authors.affiliation: AIBILI-Association for Innovation and Biomedical Research on Light and Image, Azinhaga de Santa Comba, Celas, 3000-548 Coimbra, Portugal.
authors.forename: Pedro
authors.initials: P
authors.lastname: Rodrigues
authors.affiliation: University of Coimbra, IBILI-Institute for Biomedical Imaging and Life Sciences, Faculty of Medicine, Azinhaga de Santa Comba, Celas, 3000-548 Coimbra, Portugal.
authors.forename: Pedro
authors.initials: P
authors.lastname: Guimarães
authors.affiliation: AIBILI-Association for Innovation and Biomedical Research on Light and Image, Azinhaga de Santa Comba, Celas, 3000-548 Coimbra, PortugalbUniversity of Coimbra, IBILI-Institute for Biomedical Imaging and Life Sciences, Faculty of Medicine, Azinhaga de Santa Comba, Celas, 3000-548 Coimbra, Portugal.
authors.forename: Torcato
authors.initials: T
authors.lastname: Santos
authors.affiliation: AIBILI-Association for Innovation and Biomedical Research on Light and Image, Azinhaga de Santa Comba, Celas, 3000-548 Coimbra, Portugal.
authors.forename: Sílvia
authors.initials: S
authors.lastname: Simão
authors.affiliation: AIBILI-Association for Innovation and Biomedical Research on Light and Image, Azinhaga de Santa Comba, Celas, 3000-548 Coimbra, Portugal.
authors.forename: Telmo
authors.initials: T
authors.lastname: Miranda
authors.affiliation: University of Coimbra, IBILI-Institute for Biomedical Imaging and Life Sciences, Faculty of Medicine, Azinhaga de Santa Comba, Celas, 3000-548 Coimbra, PortugalcOpen University, Campus TagusPark, Department of Science and Technology, Mathematics Section, Av. Dr. Jacques Delors, 2740-122 Porto Salvo, Oeiras, Portugal.
authors.forename: Pedro
authors.initials: P
authors.lastname: Serranho
authors.affiliation: AIBILI-Association for Innovation and Biomedical Research on Light and Image, Azinhaga de Santa Comba, Celas, 3000-548 Coimbra, PortugalbUniversity of Coimbra, IBILI-Institute for Biomedical Imaging and Life Sciences, Faculty of Medicine, Azinhaga de Santa Comba, Celas, 3000-548 Coimbra, Portugal.
authors.forename: Rui
authors.initials: R
authors.lastname: Bernardes
mesh_terms: D048909:Diabetes Complications; D005654:Fundus Oculi; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D025341:Principal Component Analysis; D012164:Retinal Diseases / Q000473:pathology; D012171:Retinal Vessels / Q000033:anatomy & histology* / Q000473:pathology; D060388:Support Vector Machine; D041623:Tomography, Optical Coherence / Q000379:methods*