Blood vessels segmentation with GUI in digital fundus images for automated detection of diabetic retinopathy

Abstract

Diabetic retinopathy (DR) is the retinal disease caused by diabetes that involves damage to the small blood vessels in the posterior of the eye. Early stage of DR may not cause symptoms. But the progression of the disease leads to the proliferative stage. This causes leakage of protein and blood in the retina. Blood vessel segmentation is a helpful tool in the treatment of diabetic retinopathy. Many studies have been carried out in the last decade in order to derive an accurate blood vessel detection and segmentation in retinal images because vascular anomalies are one of the strongest signs of DR. An user friendly graphical user interface (GUI) which is MATLAB based that segments the blood vessels by means of adaptive median thresholding is proposed in this paper. From the segmented image, various features of blood vessels like area, mean, standard deviation, energy, entropy and histogram are calculated, in order to distinguish the image as normal or abnormal. With respect to the ground truth, performance measures like accuracy, specificity and sensitivity are calculated. The GUI is implemented using MATLAB and the feature parameters are calculated. The average accuracy, specificity and sensitivity were found to be 0.95, 0.99 and 0.77 respectively for drive images using Adaptive median thresholding.

A review of feature-based retinal image analysis

“…Measuring the width (cross-section diameter), tortuosity (relative curvature), branching morphology (angle and coefficient) and fractal dimension of the vasculature allows the detection of blood filled dilatations, called microaneurysms, and of new vascularization [59,[61][62][63]. Changes in these biomarkers can also be statistically related to hypertension, obesity, cardiovascular disease, cerebrovascular diseases and stroke, increasingly common conditions globally [64][65][66][67][68].…”

Graphical Interface to Improve Python Language Teaching and Image Processing

“…In [12] an authentication system is developed with a graphical interface that implements feature extraction algorithms, in addition to algorithms for protecting biometric templates. [ [13] proposes a MATLAB-based graphical user interface for segmentation of blood vessels by applying various algorithms to distinguish an image as normal or abnormal. In [14] a system is proposed for the location of the optical disc and the optical cup in order to detect possible cases of glaucoma, in fundus images.…”