Abstract
Robust and effective optic disc (OD) detection is a necessary processing step in the research work of the automatic analysis of fundus images. In this paper, we propose a novel and robust method for the automated detection of ODs from fundus photographs. It is essentially carried out by performing template matching using the Best-Buddies Similarity (BBS) measure between the hand-marked OD region and the small parts of target images. For well characterizing the local spatial information of fundus images, a gradient constraint term was introduced for computing the BBS measurement. The performance of the proposed method is validated with Digital Retinal Images for Vessel Extraction (DRIVE) and Standard Diabetic Retinopathy Database Calibration Level 1 (DIARETDB1) databases, and quantitative results were obtained. Success rates/error distances of 100%/10.4 pixel and of 97.7%/12.9 pixel, respectively, were achieved. The algorithm has been tested and compared with other commonly used methods, and the results show that the proposed method shows superior performance.
Highlights
The optic disc (OD) is commonly considered one of the main features of a retinal fundus image.Accurate and early OD detection has been shown to be very important in ocular image analysis and computer-aided diagnosis
Diabetic Retinopathy Database Calibration Level 1 (DIARETDB1) databases, and results show that our approach outperforms state-of-the-art methods
The DIARETDB1 database consists of 89 retinal images, of which contain at least mild diabetic retinopathy and 5 are considered normal
Summary
The optic disc (OD) is commonly considered one of the main features of a retinal fundus image.Accurate and early OD detection has been shown to be very important in ocular image analysis and computer-aided diagnosis. The optic disc (OD) is commonly considered one of the main features of a retinal fundus image. OD detection is typically a key preprocessing component in computer algorithms developed for the automatic characterization of retinal anatomical structures (e.g., retinal vessels and the macula), which is helpful for aiding the ophthalmologist in determining the position of many retinal abnormalities such as exudates, drusen, and microaneurysms. OD detection aims to find the location and area of ODs in retinal fundus images. An OD has a very different appearance compared with the rest of the retina.
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