| dc.contributor |
MRC - Medical Research Council |
|
| dc.contributor |
NRS - NHS Research Scotland |
|
| dc.contributor |
Giarratano, Ylenia |
|
| dc.creator |
Giarratano, Ylenia |
|
| dc.date |
2019-12-20T16:00:57Z |
|
| dc.date |
2019-12-20T16:00:57Z |
|
| dc.date.accessioned |
2023-02-17T20:51:39Z |
|
| dc.date.available |
2023-02-17T20:51:39Z |
|
| dc.identifier |
Giarratano, Ylenia. (2019). Optical Coherence Tomography Angiography retinal scans and segmentations, [image]. University of Edinburgh. Medical School. https://doi.org/10.7488/ds/2729. |
|
| dc.identifier |
https://hdl.handle.net/10283/3528 |
|
| dc.identifier |
https://doi.org/10.7488/ds/2729 |
|
| dc.identifier.uri |
http://localhost:8080/xmlui/handle/CUHPOERS/243906 |
|
| dc.description |
Optical 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. |
|
| dc.description |
Dataset consists of two zip archives containing subsets of optical coherence tomography angiography images (superficial layer) and their manual segmentation. |
|
| dc.format |
application/zip |
|
| dc.format |
application/zip |
|
| dc.language |
eng |
|
| dc.publisher |
University of Edinburgh. Medical School |
|
| dc.rights |
Creative Commons Attribution 4.0 International Public License |
|
| dc.subject |
Subjects allied to Medicine::Ophthalmics |
|
| dc.title |
Optical Coherence Tomography Angiography retinal scans and segmentations |
|
| dc.type |
image |
|