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Depositordc.contributorGiarratano, Ylenia
Funderdc.contributor.otherMRC - Medical Research Councilen_UK
Funderdc.contributor.otherNRS - NHS Research Scotlanden_UK
Data Creatordc.creatorGiarratano, Ylenia
Date Accessioneddc.date.accessioned2019-12-20T16:00:57Z
Date Availabledc.date.available2019-12-20T16:00:57Z
Citationdc.identifier.citationGiarratano, Ylenia. (2019). Optical Coherence Tomography Angiography retinal scans and segmentations, [image]. University of Edinburgh. Medical School. https://doi.org/10.7488/ds/2729.en
Persistent Identifierdc.identifier.urihttp://hdl.handle.net/10283/3528
Persistent Identifierdc.identifier.urihttps://doi.org/10.7488/ds/2729
Dataset Description (abstract)dc.description.abstractOptical Coherence Tomography Angiography retinal scans from 11 participants in the PREVENT study and associated manual segmentations of the vasculature in the scans. Optical coherence tomography angiography (OCTA) is a novel non-invasive imaging modality for the visualisation of microvasculature in vivo. OCTA has encountered broad adoption in retinal research. OCTA potential in the assessment of pathological conditions and the reproducibility of studies relies on the quality of the image analysis. However, automated segmentation of parafoveal OCTA images is still an open problem in the field. In this study, we generate the first open dataset of retinal parafoveal OCTA images with associated ground truth manual segmentations. Imaging was performed using the commercial RTVue-XR Avanti OCT system (OptoVue, Fremont, CA). Consequent B-scans, each one consisting of 304×304 A-scans, were generated in 3×3 mm field of view centered at the fovea. In this work, we selected images only of the superficial layer (containing the vasculature enclosed in the internal limiting membrane layer (ILM) and the inner plexiform layer (IPL)) from left and right eyes of 11 participants with and without family history of dementia as part of a prospective study aimed to find early biomarkers of neurodegenerative diseases (PREVENT). For each of those images we extracted five subimages, one from each clinical region of interest (ROI): superior, nasal, inferior, temporal, and fovea. Poor quality ROIs were discarded and from the remaining a dataset containing 55 ROIs was created.en_UK
Dataset Description (TOC)dc.description.tableofcontentsDataset consists of two zip archives containing subsets of optical coherence tomography angiography images (superficial layer) and their manual segmentation.en_UK
Languagedc.language.isoengen_UK
Publisherdc.publisherUniversity of Edinburgh. Medical Schoolen_UK
Rightsdc.rightsCreative Commons Attribution 4.0 International Public Licenseen
Subject Classificationdc.subject.classificationSubjects allied to Medicine::Ophthalmicsen_UK
Titledc.titleOptical Coherence Tomography Angiography retinal scans and segmentationsen_UK
Typedc.typeimageen_UK

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