The evidence for automated grading in diabetic retinopathy screening

Alan D Fleming, Sam Philip, Keith A Goatman, Gordon J Prescott, Peter F Sharp, John A Olson

Research output: Contribution to journalArticle

13 Citations (Scopus)
5 Downloads (Pure)

Abstract

Systematic screening for diabetic retinopathy using retinal photography has been shown to reduce the incidence of blindness among people with diabetes. The implementation of diabetic retinopathy screening programmes faces several challenges. Consequently, methods for improving the efficiency of screening are being sought, one of which is the automation of image grading involving detection of images with either disease or of inadequate quality using computer software. This review aims to bring together the available evidence that is suitable for making a judgement about whether automated grading systems could be used effectively in diabetic retinopathy screening. To do this, it focuses on studies made by the few centres who have presented results tests of automated grading software on large sets of patients or screening episodes. It also considers economic model analyses and papers describing the effectiveness of manual grading in order that the effect of replacing stages of manual grading by automated grading can be judged. In conclusion, the review shows that there is sufficient evidence to suggest that automated grading, operating as a disease / no disease grader, is safe and could reduce the workload of manual grading in diabetic retinopathy screening.
Original languageEnglish
Pages (from-to)246-252
Number of pages7
JournalCurrent Diabetes Reviews
Volume7
Issue number4
DOIs
Publication statusPublished - Jul 2011

Fingerprint

Diabetic Retinopathy
Software
Economic Models
Photography
Automation
Blindness
Workload
Incidence

Keywords

  • diabetic retinopathy
  • screening
  • computer-assisted image analysis
  • imaging
  • telemedicine
  • automated grading
  • blindness
  • sit-lamp examination
  • microaneurysm detectin
  • haemorrhage

Cite this

The evidence for automated grading in diabetic retinopathy screening. / Fleming, Alan D; Philip, Sam; Goatman, Keith A; Prescott, Gordon J; Sharp, Peter F; Olson, John A.

In: Current Diabetes Reviews, Vol. 7, No. 4, 07.2011, p. 246-252.

Research output: Contribution to journalArticle

Fleming, Alan D ; Philip, Sam ; Goatman, Keith A ; Prescott, Gordon J ; Sharp, Peter F ; Olson, John A. / The evidence for automated grading in diabetic retinopathy screening. In: Current Diabetes Reviews. 2011 ; Vol. 7, No. 4. pp. 246-252.
@article{744b8b01359a4d66b6382d02ae52b9fc,
title = "The evidence for automated grading in diabetic retinopathy screening",
abstract = "Systematic screening for diabetic retinopathy using retinal photography has been shown to reduce the incidence of blindness among people with diabetes. The implementation of diabetic retinopathy screening programmes faces several challenges. Consequently, methods for improving the efficiency of screening are being sought, one of which is the automation of image grading involving detection of images with either disease or of inadequate quality using computer software. This review aims to bring together the available evidence that is suitable for making a judgement about whether automated grading systems could be used effectively in diabetic retinopathy screening. To do this, it focuses on studies made by the few centres who have presented results tests of automated grading software on large sets of patients or screening episodes. It also considers economic model analyses and papers describing the effectiveness of manual grading in order that the effect of replacing stages of manual grading by automated grading can be judged. In conclusion, the review shows that there is sufficient evidence to suggest that automated grading, operating as a disease / no disease grader, is safe and could reduce the workload of manual grading in diabetic retinopathy screening.",
keywords = "diabetic retinopathy, screening, computer-assisted image analysis, imaging, telemedicine, automated grading, blindness, sit-lamp examination, microaneurysm detectin, haemorrhage",
author = "Fleming, {Alan D} and Sam Philip and Goatman, {Keith A} and Prescott, {Gordon J} and Sharp, {Peter F} and Olson, {John A}",
year = "2011",
month = "7",
doi = "10.2174/157339911796397802",
language = "English",
volume = "7",
pages = "246--252",
journal = "Current Diabetes Reviews",
issn = "1573-3998",
publisher = "Bentham Science Publishers B.V.",
number = "4",

}

TY - JOUR

T1 - The evidence for automated grading in diabetic retinopathy screening

AU - Fleming, Alan D

AU - Philip, Sam

AU - Goatman, Keith A

AU - Prescott, Gordon J

AU - Sharp, Peter F

AU - Olson, John A

PY - 2011/7

Y1 - 2011/7

N2 - Systematic screening for diabetic retinopathy using retinal photography has been shown to reduce the incidence of blindness among people with diabetes. The implementation of diabetic retinopathy screening programmes faces several challenges. Consequently, methods for improving the efficiency of screening are being sought, one of which is the automation of image grading involving detection of images with either disease or of inadequate quality using computer software. This review aims to bring together the available evidence that is suitable for making a judgement about whether automated grading systems could be used effectively in diabetic retinopathy screening. To do this, it focuses on studies made by the few centres who have presented results tests of automated grading software on large sets of patients or screening episodes. It also considers economic model analyses and papers describing the effectiveness of manual grading in order that the effect of replacing stages of manual grading by automated grading can be judged. In conclusion, the review shows that there is sufficient evidence to suggest that automated grading, operating as a disease / no disease grader, is safe and could reduce the workload of manual grading in diabetic retinopathy screening.

AB - Systematic screening for diabetic retinopathy using retinal photography has been shown to reduce the incidence of blindness among people with diabetes. The implementation of diabetic retinopathy screening programmes faces several challenges. Consequently, methods for improving the efficiency of screening are being sought, one of which is the automation of image grading involving detection of images with either disease or of inadequate quality using computer software. This review aims to bring together the available evidence that is suitable for making a judgement about whether automated grading systems could be used effectively in diabetic retinopathy screening. To do this, it focuses on studies made by the few centres who have presented results tests of automated grading software on large sets of patients or screening episodes. It also considers economic model analyses and papers describing the effectiveness of manual grading in order that the effect of replacing stages of manual grading by automated grading can be judged. In conclusion, the review shows that there is sufficient evidence to suggest that automated grading, operating as a disease / no disease grader, is safe and could reduce the workload of manual grading in diabetic retinopathy screening.

KW - diabetic retinopathy

KW - screening

KW - computer-assisted image analysis

KW - imaging

KW - telemedicine

KW - automated grading

KW - blindness

KW - sit-lamp examination

KW - microaneurysm detectin

KW - haemorrhage

U2 - 10.2174/157339911796397802

DO - 10.2174/157339911796397802

M3 - Article

VL - 7

SP - 246

EP - 252

JO - Current Diabetes Reviews

JF - Current Diabetes Reviews

SN - 1573-3998

IS - 4

ER -