The role of haemorrhage and exudate detection in automated grading of diabetic retinopathy

Fleming, Alan D, Goatman, Keith A, Philip, Sam, Williams, Graeme J, Prescott, Gordon orcid iconORCID: 0000-0002-9156-2361, Scotland, Graham S, McNamee, Paul, Leese, Graham P, Wykes, William N et al (2009) The role of haemorrhage and exudate detection in automated grading of diabetic retinopathy. British Journal of Ophthalmology, 94 (6). pp. 706-711. ISSN 0007-1161

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Background/aims Automated grading has the potential to improve the efficiency of diabetic retinopathy screening services. While disease/no disease grading can be performed using only microaneurysm detection and image-quality assessment, automated recognition of other types of lesions may be advantageous. This study investigated whether inclusion of automated recognition of exudates and haemorrhages improves the detection of observable/referable diabetic retinopathy.

Methods Images from 1253 patients with observable/referable retinopathy and 6333 patients with non-referable retinopathy were obtained from three grading centres. All images were reference-graded, and automated disease/no disease assessments were made based on microaneurysm detection and combined microaneurysm, exudate and haemorrhage detection.

Results Introduction of algorithms for exudates and haemorrhages resulted in a statistically significant increase in the sensitivity for detection of observable/referable retinopathy from 94.9% (95% CI 93.5 to 96.0) to 96.6% (95.4 to 97.4) without affecting manual grading workload.

Conclusion Automated detection of exudates and haemorrhages improved the detection of observable/referable retinopathy.

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