Automatic extraction of vascularity measurements using OCT-A images
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Automatic extraction of vascularity measurements using OCT-A imagesDate
2018Citation
M. Díaz, J. Novo, M. G. Penedo, y M. Ortega, «Automatic extraction of vascularity measurements using OCT-A images», Procedia Computer Science, vol. 126, pp. 273-281, 2018, doi: 10.1016/j.procs.2018.07.261.
Abstract
[Absctract]: Optical Coherence Tomography Angiography (OCT-A) represents a new modality of ophthalmological imaging that stands out for being a non-invasive capture technique that facilitates the analysis of the vascular characteristics of the eye fundus. In this paper, we propose a complete automatic methodology that identifies the vascular and avascular zones in OCT-A images, quantifying each one of them for their posterior use in clinical analyses and diagnostic processes. To achieve this, we firstly intensify the vascular characteristics to facilitate the posterior extraction. Then, a set of image processing techniques are combined to differentiate both vascular and avascular regions and, finally, measure their representative parameters. The proposed methodology was tested on a set of images that were marked by an expert ophthalmologist, being used as reference in the validation of the method. The proposed approach presented satisfactory results in the validation experiments with the vascular and avascular measurements, demonstrating their utility for the diagnosis and monitoring of different vascular diseases that are frequently analysed through the retinal microcirculation.
Keywords
Computer-aided diagnosis
Image Segmentation
Retinal imaging
Optical Coherence Tomography Angiography
Vascularity
Image Segmentation
Retinal imaging
Optical Coherence Tomography Angiography
Vascularity
Description
The conference was held in Belgrade, Serbia, 3-5 September 2018.
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Atribución-NoComercial-SinDerivadas 3.0 España
ISSN
1877-0509