An image analysis framework for the early assessment of hypertensive retinopathy signs

This paper presents a framework for the detection and measurement of retinal vessels in fundoscopy images. The proposed method segments retinal vessels, enabling the actual measurement of the vessel diameter. A Graphical User Interface (GUI) further supports a number of methods for the automatic and interactive measurement of vessel diameters at any selected point or region of interest. In addition, it provides methods for editing the vessel representation in order to recover from possible segmentation misclassifications. All the above steps are integrated into a clinical application capable of supporting vascular risk stratification in persons with hypertension. The performance of the segmentation is assessed on two publicly available DRIVE and STARE datasets. The experimental results show that the method can achieve a high accuracy on both datasets with very low computational cost, being comparative or slightly better than widely used supervised and unsupervised methods.