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Automated quantification of retinal vessel morphometry in the UK biobank cohort

Automated quantification of retinal vessel morphometry in the UK biobank cohort
Automated quantification of retinal vessel morphometry in the UK biobank cohort

The morphometric characteristics of the retinal vascular network have been associated with risk markers of many systemic and vascular diseases. However, analysis of data from large population based studies is needed to help resolve uncertainties in these associations. QUARTZ (QUantitative Analysis of Retinal vessel Topology and siZe) is a fully automated retinal image analysis system that has been designed to process large numbers of retinal images and obtains quantitative measures of vessel morphology to be used in epidemiological studies. QUARTZ has been used to process retinal images from UK Biobank which is a large population-based cohort study. In this paper, we address issues of robustness with respect to processing large datasets and validate QUARTZ using a subset of 4,692 UK Biobank retinal images. Ground truth data produced by human observers for validation have been made available online. Following validation, 135,867 retinal images (68,549 participants) from the UK Biobank study were processed by QUARTZ. 71.53% of these images were classified as being of adequate quality, which equated to 80.90% participants with at least one image of adequate quality. The vessel morphometric data are currently being used in epidemiological studies. The intention of the UK Biobank Eye and Vision Consortium is to include these derived measures in the UK Biobank data archive.

Disease biomarkers, Large retinal datasets, Retinal image analysis, UK Biobank
1-6
IEEE
Welikala, R. A.
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Fraz, M. M.
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Morgan, James
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on behalf of the UK Biobank Eye and Vision Consortium
Welikala, R. A.
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Fraz, M. M.
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Habib, M. M.
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Daniel-Tong, S.
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Yates, M.
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Foster, P. J.
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Whincup, P. H.
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Rudnicka, Alicja
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Strachan, D. P.
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Owen, C. G.
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Barman, Sarah
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Aslam, Tariq
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Barman, Sarah
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Paul Bishop, S.
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Blows, Peter
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Carare, Roxana
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Chakravarthy, Usha
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Chan, Michelle
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Dick, Andrew
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Foster, Paul
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Gallacher, John
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Garway-Heath, David Ted
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Hammond, Chris
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Khaw, Sir Peng Tee
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Khawaja, Anthony
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Lascaratos, Gerassimos
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Lotery, Andrew
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Mackie, Sarah
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Martin, Keith
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McGaughey, Michelle
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McGuinness, Bernadette
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McKay, Gareth
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Morgan, James
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Welikala, R. A., Fraz, M. M., Habib, M. M., Daniel-Tong, S., Yates, M., Foster, P. J., Whincup, P. H., Rudnicka, Alicja, Strachan, D. P., Owen, C. G. and Barman, Sarah , on behalf of the UK Biobank Eye and Vision Consortium (2018) Automated quantification of retinal vessel morphometry in the UK biobank cohort. In Proceedings of the 7th International Conference on Image Processing Theory, Tools and Applications, IPTA 2017. vol. 2018-January, IEEE. pp. 1-6 . (doi:10.1109/IPTA.2017.8310108).

Record type: Conference or Workshop Item (Paper)

Abstract

The morphometric characteristics of the retinal vascular network have been associated with risk markers of many systemic and vascular diseases. However, analysis of data from large population based studies is needed to help resolve uncertainties in these associations. QUARTZ (QUantitative Analysis of Retinal vessel Topology and siZe) is a fully automated retinal image analysis system that has been designed to process large numbers of retinal images and obtains quantitative measures of vessel morphology to be used in epidemiological studies. QUARTZ has been used to process retinal images from UK Biobank which is a large population-based cohort study. In this paper, we address issues of robustness with respect to processing large datasets and validate QUARTZ using a subset of 4,692 UK Biobank retinal images. Ground truth data produced by human observers for validation have been made available online. Following validation, 135,867 retinal images (68,549 participants) from the UK Biobank study were processed by QUARTZ. 71.53% of these images were classified as being of adequate quality, which equated to 80.90% participants with at least one image of adequate quality. The vessel morphometric data are currently being used in epidemiological studies. The intention of the UK Biobank Eye and Vision Consortium is to include these derived measures in the UK Biobank data archive.

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More information

Published date: 8 March 2018
Venue - Dates: 7th International Conference on Image Processing Theory, Tools and Applications, IPTA 2017, , Montreal, Canada, 2017-11-28 - 2017-12-01
Keywords: Disease biomarkers, Large retinal datasets, Retinal image analysis, UK Biobank
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Identifiers

Local EPrints ID: 438702
URI: http://eprints.soton.ac.uk/id/eprint/438702
DOI: doi:10.1109/IPTA.2017.8310108
PURE UUID: 3aefb4df-f178-46b3-a3ef-a258a3c45073
ORCID for Roxana Carare: ORCID iD orcid.org/0000-0001-6458-3776
ORCID for Andrew Lotery: ORCID iD orcid.org/0000-0001-5541-4305

Catalogue record

Date deposited: 23 Mar 2020 17:30
Last modified: 18 Mar 2024 02:57

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Contributors

Author: R. A. Welikala
Author: M. M. Fraz
Author: M. M. Habib
Author: S. Daniel-Tong
Author: M. Yates
Author: P. J. Foster
Author: P. H. Whincup
Author: Alicja Rudnicka
Author: D. P. Strachan
Author: C. G. Owen
Author: Sarah Barman
Author: Tariq Aslam
Author: Sarah Barman
Author: S. Paul Bishop
Author: Peter Blows
Author: Catey Bunce
Author: Roxana Carare ORCID iD
Author: Usha Chakravarthy
Author: Michelle Chan
Author: Antonietta Chianca
Author: Valentina Cipriani
Author: David Crabb
Author: Philippa Cumberland
Author: Alexander Day
Author: Parul Desai
Author: Bal Dhillon
Author: Andrew Dick
Author: Paul Foster
Author: John Gallacher
Author: David Ted Garway-Heath
Author: Srini Goverdhan
Author: Jeremy Guggenheim
Author: Priyal Gupta
Author: Chris Hammond
Author: Ruth Hogg
Author: Anne Hughes
Author: Pearse Keane
Author: Sir Peng Tee Khaw
Author: Anthony Khawaja
Author: Gerassimos Lascaratos
Author: Andrew Lotery ORCID iD
Author: Phil Luthert
Author: Tom Mac-Gillivray
Author: Sarah Mackie
Author: Keith Martin
Author: Michelle McGaughey
Author: Bernadette McGuinness
Author: Gareth McKay
Author: Martin McKibbin
Author: James Morgan
Corporate Author: on behalf of the UK Biobank Eye and Vision Consortium

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