An Automated Method for Retinal Arteriovenous Nicking Quantification From Color Fundus Images

Abstract

Retinal arteriovenous (AV) nicking is one of the prominent and significant microvascular abnormalities. It is characterized by the decrease in the venular caliber at both sides of an artery-vein crossing. Recent research suggests that retinal AV nicking is a strong predictor of eye diseases such as branch retinal vein occlusion and cardiovascular diseases such as stroke. In this study, we present a novel method for objective and quantitative AV nicking assessment. From the input retinal image, the vascular network is first extracted using the multiscale line detection method. The crossover point detection method is then performed to localize all AV crossing locations. At each detected crossover point, the four vessel segments, two associated with the artery and two associated with the vein, are identified and two venular segments are then recognized through the artery-vein classification method. The vessel widths along the two venular segments are measured and analyzed to compute the AV nicking severity of that crossover. The proposed method was validated on 47 high-resolution retinal images obtained from two population-based studies. The experimental results indicate a strong correlation between the computed AV nicking values and the expert grading with a Spearman correlation coefficient of 0.70. Sensitivity was 77% and specificity was 92% (Kappa κ = 0.70) when comparing AV nicking detected using the proposed method to that detected using a manual grading method, performed by trained photographic graders.

Clinical utilization of automated image analysis software for improving retinal reader's performance

“…The performance was measured in terms of detection sensitivity per vascular abnormality and false positives per image (FPPI) as given in Table 3, which shows comparable results to the literature method for detecting AV nicking [21]. To our knowledge, there is no literature reported on automated detection methods for copper-silver wiring and emboli, therefore our methods are a novel contribution.…”

A Review on the Extraction of Quantitative Retinal Microvascular Image Feature

“…Due to this arteriovenous crossing, the vein inflates either side of artery cross-section point. In several types of research related to retinal imaging, AV nicking has been found as the early indicator of eye-related diseases such as BRVO, diabetes, hypertension, and acute stroke [ 30 , 60 , 61 ]. Figure 2 shows the normal and affected AV crossing scenario.…”

Automatic detection of arteriovenous nicking in retinal images

“…Where, 1 WidthApproach represents the vascular width of S1 near the crossing area, and 1 WidthAway is the width away from the crossing area. So as to 2 WidthApproach and 2 WidthAway . The meanings of these parameters are shown in Fig.10.…”

“…It is characterized as veins compressed by hardened arteries in crossing area. Because AV-nicking is an indicator of high blood pressure, retinal AV-nicking detection becomes an important basis for early diagnosis and treatment of related diseases [2][3][4][5].…”

“…There are not many relevant automatic detection methods [2] [3]. Manual detection of AV-nicking is difficult and time consuming, since the blood vessels in a retinal image are complicated in structure with low contrast.…”