Automatic arteriovenous crossing phenomenon detection on retinal fundus images

Abstract

Arteriolosclerosis is one cause of acquired blindness. Retinal fundus image examination is useful for early detection of arteriolosclerosis. In order to diagnose the presence of arteriolosclerosis, the physicians find the silver-wire arteries, the copper-wire arteries and arteriovenous crossing phenomenon on retinal fundus images. The focus of this study was to develop the automated detection method of the arteriovenous crossing phenomenon on the retinal images. The blood vessel regions were detected by using a double ring filter, and the crossing sections of artery and vein were detected by using a ring filter. The center of that ring was an interest point, and that point was determined as a crossing section when there were over four blood vessel segments on that ring. And two blood vessels gone through on the ring were classified into artery and vein by using the pixel values on red and blue component image. Finally, V 2 -to-V 1 ratio was measured for recognition of abnormalities. V 1 was the venous diameter far from the blood vessel crossing section, and V 2 was the venous diameter near from the blood vessel crossing section. The crossing section with V 2 -to-V 1 ratio over 0.8 was experimentally determined as abnormality. Twenty four images, including 27 abnormalities and 54 normal crossing sections, were used for preliminary evaluation of the proposed method. The proposed method was detected 73% of crossing sections when the 2.8 sections per image were mis-detected. And, 59% of abnormalities were detected by measurement of V 1 -to-V 2 ratio when the 1.7 sections per image were mis-detected.