Automatic Blood Vessel Localization in Small Field of View Eye Images
Abstract
Localizing blood vessels in eye images is a crucial step in the automated and objective diagnosis of eye diseases. Most previous research has focused on extracting the centerlines of vessels in large field of view images. However, for diagnosing diseases of the optic disk region, like glaucoma, small field of view images have to be analyzed. One needs to identify not only the centerlines, but also vessel widths, which vary widely in these images. We present an automatic technique for localizing vessels in small field of view images using multiscale matched filters. We also estimate local vessel properties – width and orientation – along the length of each vessel. Furthermore, we explicitly account for highlights on thick vessels – central reflexes – which are ignored in many previous works. Qualitative and quantitative results demonstrate the efficacy of our method – e.g. vessel centers are localized with RMS and median errors of 2.11 and 1 pixels, respectively in 700×700 images.