@inproceedings{53cfc82288ad47318092f7023152cb7d,
title = "Optic Disc and Fovea Localisation in Ultra-widefield Scanning Laser Ophthalmoscope Images Captured in Multiple Modalities",
abstract = "We propose a convolutional neural network for localising the centres of the optic disc (OD) and fovea in ultra-wide field of view scanning laser ophthalmoscope (UWFoV-SLO) images of the retina. Images captured in both reflectance and autofluorescence (AF) modes, and central pole and eyesteered gazes, were used. The method achieved an OD localisation accuracy of 99.4% within one OD radius, and fovea localisation accuracy of 99.1% within one OD radius on a test set comprising of 1790 images. The performance of fovea localisation in AF images was comparable to the variation between human annotators at this task. The laterality of the image (whether the image is of the left or right eye) was inferred from the OD and fovea coordinates with an accuracy of 99.9%.",
keywords = "Convolutional neural networks, Fovea detection, Laterality determination, Optic disc detection, Retinal images",
author = "Wakeford, {Peter R.} and Enrico Pellegrini and Gavin Robertson and Michael Verhoek and Fleming, {Alan D.} and {van Hemert}, Jano and Heng, {Ik Siong}",
note = "Funding Information: P. R. Wakeford-Supported by the EPSRC Centre for Doctoral Training in Applied Photonics. Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 23rd Conference on Medical Image Understanding and Analysis, MIUA 2019 ; Conference date: 24-07-2019 Through 26-07-2019",
year = "2020",
month = jan,
day = "24",
doi = "10.1007/978-3-030-39343-4_34",
language = "English",
isbn = "9783030393427",
series = "Communications in Computer and Information Science",
publisher = "Springer",
pages = "399--410",
editor = "Yalin Zheng and Williams, {Bryan M.} and Ke Chen",
booktitle = "Medical Image Understanding and Analysis - 23rd Conference, MIUA 2019, Proceedings",
address = "United Kingdom",
}