An improved matched filter for blood vessel detection of digital retinal images
Computers in Biology and Medicine
Utilization of artificial neural networks in the diagnosis of optic nerve diseases
Computers in Biology and Medicine
Retinal vessel extraction by matched filter with first-order derivative of Gaussian
Computers in Biology and Medicine
Determination of foveal avascular zone in diabetic retinopathy digital fundus images
Computers in Biology and Medicine
Automatic model-based tracing algorithm for vessel segmentation and diameter estimation
Computer Methods and Programs in Biomedicine
Computer Methods and Programs in Biomedicine
IEEE Transactions on Information Technology in Biomedicine
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Automatic measurement and quantification of blood vessels' features and detection of vessel landmarks are key steps in the computer-aided diagnosis and diseases monitoring. This work proposes a novel and robust method for detecting vessel landmarks, i.e. bifurcation and crossovers, and measurement of different features, i.e. vessel orientation and vessel diameter as well as bifurcation angle, from the detected vessel network using simple and efficient local vessel pattern operator. The proposed method is applied to the publicly available DRIVE, STARE and ARIA databases and compared with existing state-of-the-art approaches. It shows higher accuracy in detection of vessel landmark and estimation of vessel features.