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Automatic optic disc detection in colour fundus images by means of multispectral analysis and information content

Martinez-Perez, ME; Witt, N; Parker, KH; Hughes, AD; Thom, SAM; (2019) Automatic optic disc detection in colour fundus images by means of multispectral analysis and information content. PeerJ , 7 , Article e7119. 10.7717/peerj.7119. Green open access

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Abstract

The optic disc (OD) in retinal fundus images is widely used as a reference in computer-based systems for the measurement of the severity of retinal disease. A number of algorithms have been published in the past 5 years to locate and measure the OD in digital fundus images. Our proposed algorithm, automatically: (i) uses the three channels (RGB) of the digital colour image to locate the region of interest (ROI) where the OD lies, (ii) measures the Shannon information content per channel in the ROI, to decide which channel is most appropriate for searching for the OD centre using the circular Hough transform. A series of evaluations were undertaken to test our hypothesis that using the three channels gives a better performance than a single channel. Three different databases were used for evaluation purposes with a total of 2,371 colour images giving a misdetection error of 3% in the localisation of the centre of the OD. We find that the area determined by our algorithm which assumes that the OD is circular, is similar to that found by other algorithms that detected the shape of the OD. Five metrics were measured for comparison with other recent studies. Combining the two databases where expert delineation of the OD is available (1,240 images), the average results for our multispectral algorithm are: TPR = 0.879, FPR = 0.003, Accuracy = 0.994, Overlap = 80.6% and Dice index = 0.878.

Type: Article
Title: Automatic optic disc detection in colour fundus images by means of multispectral analysis and information content
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.7717/peerj.7119
Publisher version: http://dx.doi.org/10.7717/peerj.7119
Language: English
Additional information: © 2019 Martinez-Perez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/).
Keywords: Computer-based systems, Information content, Optic disc detection, Retinal images, Visual multispectral imaging
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science > Population Science and Experimental Medicine
URI: https://discovery.ucl.ac.uk/id/eprint/10078480
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