TY - GEN
T1 - Automatic fovea detection in retinal fundus images
AU - Liang, Ziyang
AU - Wong, Damon Wing Kee
AU - Liu, Jiang
AU - Tan, Ngan Meng
AU - Cheng, Xiangang
AU - Cheung, Gemmy Chui Ming
AU - Bhargava, Mayuri
AU - Wong, Tien Yin
N1 - Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2012
Y1 - 2012
N2 - T The fovea (centre of the retinal macula region) is responsible for central vision. Conditions which can affect the macula region in particular include AMD and macular oedema, which lead to a direct loss in visual acuity due to the effect on central vision. The detection of the fovea is an important step in the assessment of retinal images for pathologies relating to these visual conditions. In this paper, we propose a method to automatically detect the fovea in retinal fundus images. The method makes use of optic disc detection as a starting point. Using information from an extensive database, typical locations of the fovea are used to define search regions for subsequent analysis. We make use of a combination of the image characteristics of the macular region with noise and vessel removal for fovea detection. The proposed method is tested on a large database of 750 retinal fundus images, achieving an accuracy of 86.53%.
AB - T The fovea (centre of the retinal macula region) is responsible for central vision. Conditions which can affect the macula region in particular include AMD and macular oedema, which lead to a direct loss in visual acuity due to the effect on central vision. The detection of the fovea is an important step in the assessment of retinal images for pathologies relating to these visual conditions. In this paper, we propose a method to automatically detect the fovea in retinal fundus images. The method makes use of optic disc detection as a starting point. Using information from an extensive database, typical locations of the fovea are used to define search regions for subsequent analysis. We make use of a combination of the image characteristics of the macular region with noise and vessel removal for fovea detection. The proposed method is tested on a large database of 750 retinal fundus images, achieving an accuracy of 86.53%.
KW - computer aided detection
KW - disc diameter
KW - fovea
KW - fundus image
UR - http://www.scopus.com/inward/record.url?scp=84871700878&partnerID=8YFLogxK
U2 - 10.1109/ICIEA.2012.6361008
DO - 10.1109/ICIEA.2012.6361008
M3 - Conference contribution
AN - SCOPUS:84871700878
SN - 9781457721175
T3 - Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012
SP - 1746
EP - 1750
BT - Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012
T2 - 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012
Y2 - 18 July 2012 through 20 July 2012
ER -