Automated detection of fovea in fundus images based on vessel-free zone and adaptive Gaussian template

E-Fong Kao; Pi-Chen Lin; Ming-Chung Chou; Twei-Shiun Jaw; Gin-Chung Liu

doi:10.1016/j.cmpb.2014.08.003

Automated detection of fovea in fundus images based on vessel-free zone and adaptive Gaussian template

Comput Methods Programs Biomed. 2014 Nov;117(2):92-103. doi: 10.1016/j.cmpb.2014.08.003. Epub 2014 Aug 14.

Authors

E-Fong Kao¹, Pi-Chen Lin², Ming-Chung Chou³, Twei-Shiun Jaw⁴, Gin-Chung Liu⁴

Affiliations

¹ Department of Medical Imaging and Radiological Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan. Electronic address: tonykao@kmu.edu.tw.
² Division of Endocrinology and Metabolism, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.
³ Department of Medical Imaging and Radiological Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan.
⁴ Department of Medical Imaging, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.

PMID: 25168776
DOI: 10.1016/j.cmpb.2014.08.003

Abstract

This study developed a computerised method for fovea centre detection in fundus images. In the method, the centre of the optic disc was localised first by the template matching method, the disc-fovea axis (a line connecting the optic disc centre and the fovea) was then determined by searching the vessel-free region, and finally the fovea centre was detected by matching the fovea template around the centre of the axis. Adaptive Gaussian templates were used to localise the centres of the optic disc and fovea for the images with different resolutions. The proposed method was evaluated using three publicly available databases (DIARETDB0, DIARETDB1 and MESSIDOR), which consisted of a total of 1419 fundus images with different resolutions. The proposed method obtained the fovea detection accuracies of 93.1%, 92.1% and 97.8% for the DIARETDB0, DIARETDB1 and MESSIDOR databases, respectively. The overall accuracy of the proposed method was 97.0% in this study.

Keywords: Fovea centre detection; Fundus image; Gaussian template; Vessel-free zone.

MeSH terms

Algorithms*
Artificial Intelligence
Data Interpretation, Statistical
Fluorescein Angiography / methods*
Fundus Oculi
Humans
Image Enhancement / methods*
Image Interpretation, Computer-Assisted / methods*
Normal Distribution
Pattern Recognition, Automated / methods*
Reproducibility of Results
Retina / anatomy & histology*
Sensitivity and Specificity