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Reproducibility of Retinal Vascular Phenotypes Obtained with Optical Coherence Tomography Angiography: Importance of Vessel Segmentation

Conference paper
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Part of the Lecture Notes in Computer Science book series (LNCS, volume 12722)

Abstract

Optical coherence tomography angiography (OCTA) is a non-invasive imaging method that can visualize the finest vascular networks in the human retina. OCTA image analysis has been successfully applied to the investigation of retinal vascular diseases of the eye and other systemic conditions that may manifest in the eye. To characterize and distinguish OCTA images from different pathologies, it is important to identify quantitative metrics and phenotypes that have high reproducibility and are not overly susceptible to the effects of imaging artifacts. This paper demonstrates the reproducibility of several recently demonstrated candidate OCTA quantitative metrics: mean curvature and tortuosity of the whole, foveal, superior, nasal, inferior, and temporal regions; foveal and parafoveal vessel skeleton density; and finally, foveal avascular zone area and acircularity index. This paper also highlights the importance of vessel segmentation choice on reproducibility using two different segmentation methods: optimally oriented flux and Frangi filter.

Keywords

OCTA imaging Retinal vascular phenotype Reproducibility 

Notes

Acknowledgements

DR and YG were supported by two Medical Research Council Precision Medicine Doctoral Training Programme scholarships (MR/N013166/1). MOB is supported by grants from EPSRC (EP/R029598/1, EP/T008806/1), Fondation Leducq (17 CVD 03), the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 801423, and British Heart Foundation/The Alan Turing Institute under a Cardiovascular Data Science Award. TJM and MOB acknowledge the funders of the SCONe project (https://www.ed.ac.uk/ophthalmology/scone). This project was supported in part by the Alzheimer’s Drug Discovery Foundation and the Heed Foundation (SC) and the VitreoRetinal Surgery Foundation (SC).

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© Springer Nature Switzerland AG 2021

Authors and Affiliations

  1. 1.Centre for Medical Informatics, Usher InstituteThe University of EdinburghEdinburghScotland
  2. 2.Edinburgh Clinical Research Facility and Edinburgh ImagingUniversity of EdinburghEdinburghScotland
  3. 3.Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghScotland
  4. 4.Department of OphthalmologyDuke University School of MedicineDurhamUSA

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