TY - GEN
T1 - Level-set based automatic cup-to-disc ratio determination using retinal fundus images in argali
AU - Wong, D. W.K.
AU - Liu, J.
AU - Lim, J. H.
AU - Jia, X.
AU - Yin, F.
AU - Li, H.
AU - Wong, T. Y.
N1 - Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2008
Y1 - 2008
N2 - Glaucoma is a leading cause of permanent blindness. However, disease progression can be limited if detected early. The optic cup-to-disc ratio (CDR) is one of the main clinical indicators of glaucoma, and is currently determined manually, limiting its potential in mass screening. In this paper, we propose an automatic CDR determination method using a variational level-set approach to segment the optic disc and cup from retinal fundus images. The method is a core component of ARGALI, a system for automated glaucoma risk assessment. Threshold analysis is used in preprocessing to estimate the initial contour. Due to the presence of retinal vasculature traversing the disc and cup boundaries which can cause inaccuracies in the detected contours, an ellipse-fitting post-processing step is also introduced. The method was tested on 104 images from the Singapore Malay Eye Study, and it was found the results produced a clinically acceptable variation of up to 0.2 CDR units from the manually graded samples, with potential use in mass screening.
AB - Glaucoma is a leading cause of permanent blindness. However, disease progression can be limited if detected early. The optic cup-to-disc ratio (CDR) is one of the main clinical indicators of glaucoma, and is currently determined manually, limiting its potential in mass screening. In this paper, we propose an automatic CDR determination method using a variational level-set approach to segment the optic disc and cup from retinal fundus images. The method is a core component of ARGALI, a system for automated glaucoma risk assessment. Threshold analysis is used in preprocessing to estimate the initial contour. Due to the presence of retinal vasculature traversing the disc and cup boundaries which can cause inaccuracies in the detected contours, an ellipse-fitting post-processing step is also introduced. The method was tested on 104 images from the Singapore Malay Eye Study, and it was found the results produced a clinically acceptable variation of up to 0.2 CDR units from the manually graded samples, with potential use in mass screening.
KW - Automated level-set segmentation
KW - Medical image processing
KW - Optic cup-to-disc ratio
UR - http://www.scopus.com/inward/record.url?scp=61849089473&partnerID=8YFLogxK
U2 - 10.1109/iembs.2008.4649648
DO - 10.1109/iembs.2008.4649648
M3 - Conference contribution
C2 - 19163151
AN - SCOPUS:61849089473
SN - 9781424418152
T3 - Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"
SP - 2266
EP - 2269
BT - Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
PB - IEEE Computer Society
T2 - 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Y2 - 20 August 2008 through 25 August 2008
ER -
