Improved automated optic cup segmentation based on detection of blood vessel bends in retinal fundus images.

Abstract

Glaucoma is a leading cause of permanent blindness. Retinal imaging is useful for early detection of glaucoma. In order to evaluate the presence of glaucoma, ophthalmologists may determine the cup and disc areas and diagnose glaucoma using a vertical optic cup-to-disc (C/D) ratio and a rim-to-disc (R/D) ratio. Previously we proposed a method to determine cup edge by analyzing a vertical profile of pixel values, but this method provided a cup edge smaller than that of an ophthalmologist. This paper describes an improved method using the locations of the blood vessel bends. The blood vessels were detected by a concentration feature determined from the density gradient. The blood vessel bends were detected by tracking the blood vessels from the disc edge to the primary cup edge, which was determined by our previous method. Lastly, the vertical C/D ratio and the R/D ratio were calculated. Using forty-four images, including 32 glaucoma images, the AUCs of both the vertical C/D ratio and R/D ratio by this proposed method were 0.966 and 0.936, respectively.

• Authors: Yuji Hatanaka, Yuuki Nagahata, Chisako Muramatsu, Susumu Okumura, Kazunori Ogohara, Akira Sawada, Kyoko Ishida, Tetsuya Yamamoto, Hiroshi Fujita
• Journal: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference (Annu Int Conf IEEE Eng Med Biol Soc) Vol. 2014 Pg. 126-9 ( 2014) ISSN: 2694-0604 [Electronic] United States
• PMID: 25569913 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)

Topics

• Area Under Curve
• Fundus Oculi
• Glaucoma (diagnosis)
• Humans
• Image Interpretation, Computer-Assisted
• ROC Curve
• Retina (pathology)
• Retinal Vessels (pathology)