Automatic detection of the macula in retinal fundus images using seeded mode tracking approach.
The macula is the part of the eye responsible for central high acuity vision. Detection of the macula is an important task in retinal image processing as a landmark for subsequent disease assessment, such as for age-related macula degeneration. In this paper, we have presented an approach to automatically determine the macula centre in retinal fundus images. First contextual information on the image is combined with a statistical model to obtain an approximate macula region of interest localization. Subsequently, we propose the use of a seeded mode tracking technique to locate the macula centre. The proposed approach is tested on a large dataset composed of 482 normal images and 162 glaucoma images from the ORIGA database and an additional 96 AMD images. The results show a ROI detection of 97.5%, and 90.5% correct detection of the macula within 1/3DD from a manual reference, which outperforms other current methods. The results are promising for the use of the proposed approach to locate the macula for the detection of macula diseases from retinal images.
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
Fengshou
F
Yin
Xiangang
X
Cheng
Ching-Yu
CY
Cheng
Gemmy C M
GC
Cheung
Tien Yin
TY
Wong
D000465:Algorithms; D001185:Artificial Intelligence; D005901:Glaucoma / Q000473:pathology*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008266:Macula Lutea / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D042262:Retinoscopy / Q000379:methods*; D012680:Sensitivity and Specificity