Journal article

Automatic detection of the macula in retinal fundus images using seeded mode tracking approach.

Damon WK Wong, Jiang Liu, Ngan-Meng Tan, Fengshou Yin, Xiangang Cheng, Ching-Yu Cheng, Gemmy CM Cheung, Tien Yin Wong

Annu Int Conf IEEE Eng Med Biol Soc | Published : 2012

Abstract

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..

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