An ensembling approach for optic cup detection based on spatial heuristic analysis in retinal fundus images.
Optic cup detection remains a challenging task in retinal image analysis, and is of particular importance for glaucoma evaluation, where disease severity is often assessed by the size of the optic cup. In this paper, we propose spatial heuristic ensembling (SHE), an approach which aims to fuse the advantages of each method based on the specific performance in each defined sector. In this way, we generate an ensembled optic cup which is obtained from the optimal combination of the component methods. We conduct experiments on the ORIGA data set of 650 retinal images and show that the ensemble approach performs better than the individual segmentations, reducing the relative overlap error, and CDR errors by as much as 0.04 CDR units. The results are promising for the continued development of such an approach for improving optic cup segmentation.
Institute For Infocomm Research, A*STAR, Singapore. wkwong@i2r.a-star.edu.sg
Damon W K
DW
Wong
Jiang
J
Liu
Ngan Meng
NM
Tan
Yin
Y
Fengshou
Carol
C
Cheung
Mani
M
Baskaran
Tin
T
Aung
Tien Yin
TY
Wong
D001499:Bayes Theorem; D016208:Databases, Factual; D003941:Diagnostic Techniques, Ophthalmological; D005654:Fundus Oculi; D005901:Glaucoma / Q000175:diagnosis / Q000473:pathology; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D009898:Optic Disk / Q000033:anatomy & histology*