Automatic optic disc segmentation with peripapillary atrophy elimination

• Published in: 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society Vol. 2011; pp. 6224 - 6227
• Main Authors: Jun Cheng, Jiang Liu, Wong, D. W. K., Fengshou Yin, Cheung, C., Baskaran, M., Tin Aung, Tien Yin Wong
• Format: Conference Proceeding Journal Article
• Language: English
• Published: United States IEEE 01.01.2011
• Subjects: Adaptive optics; Algorithms; Automatic Data Processing; Automation; Biomedical optical imaging; Databases, Factual; Diagnosis, Computer-Assisted - methods; Diagnostic Imaging - methods; Fundus Oculi; Glaucoma - diagnosis; Glaucoma - diagnostic imaging; Humans; Image edge detection; Image Processing, Computer-Assisted; Image segmentation; Models, Statistical; Optic Atrophy - pathology; Optic Disk - pathology; Optical imaging; Optical sensors; Radiography; Reproducibility of Results; Transforms
• ISBN: 9781424441211; 1424441218
• ISSN: 1094-687X; 1557-170X
• DOI: 10.1109/IEMBS.2011.6091537

Optic disc segmentation from retinal fundus image is a fundamental but important step for automatic glaucoma diagnosis. In this paper, an optic disc segmentation method is proposed based on peripapillary atrophy elimination. The elimination is done through edge filtering, constraint elliptical Hough transform and peripapillary atrophy detection. With the elimination, edges that are likely from non-disc structures especially peripapillary atrophy are excluded to make the segmentation more accurate. The proposed method has been tested in a database of 650 images with disc boundaries marked by trained professionals manually. The experimental results by the proposed method show average m 1 , m 2 and m VD of 10.0%, 7.4% and 4.9% respectively. It can be used to compute cup to disc ratio as well as other features for application in automatic glaucoma diagnosis systems.