Accurate methods for manually marking retinal vessel widths

This paper compares two manual measurement techniques for measuring retinal vessel segment widths: the kick-points technique and the edge marking technique. An image set of 164 clear, high-resolution segments was used. The kick-points approach uses kick points marked by observers along interpolated cross-sectional intensity profile graphs; the edge marking method allows observers to nominate the edges on a zoomed-up image, and interpolates edge positions. The edgemarking method provides more precise measurements than the kick-points method, but these are subject to more inter-observer variability; we speculate that this result is due to differing observer perceptions of the edge location

Automated measurements of retinal bifurcations

This paper presents an analysis of the bifurcations of retinal vessels. The angles and relative diameters of blood vessels in 230 bifurcations were measured using a new automated procedure, and used to calculate the values of several features with known theoretical properties. The measurements are compared with predictions from theoretical models, and with manual measurements. The automated measurements agree with the theoretical prediction measurements with slightly different bias. The automated method can measure a large number of retinal bifurcations very rapidly, and may be useful in correlating bifurcation geometry with clinical conditions

A ribbon of twins for extracting vessel boundaries

This paper presents an efficient model for automatic detection and extraction of blood vessels in ocular fundus images. The model is formed using a combination of the concept of ribbon snakes and twin snakes. On each edge, the twin concept is introduced by using two snakes, one inside and one outside the boundary. The ribbon concept integrates the pair of twins on the two vessel edges into a single ribbon. The twins maintain the consistency of the vessel width, particularly on very blurred, thin and noisy vessels. The model exhibits excellent performance in extracting the boundaries of vessels, with improved robustness compared to alternative models in the presence of occlusion, poor contrast or noise. Results are presented which demonstrate the performance of the discussed edge extraction method, and show a significant improvement compared to classical snake formulations

Manual measurement of retinal bifurcation features

This paper introduces a new computerized tool for accurate manual measurement of features of retinal bifurcation geometry, designed for use in investigating correlations between measurement features and clinical conditions. The tool uses user-placed rectangles to measure the vessel width, and lines placed along vessel center lines to measure the angles. An analysis is presented of measurements taken from 435 bifurcations. These are compared with theoretical predictions based on optimality principles presented in the literature. The new tool shows better agreement with the theoretical predictions than a simpler manual method published in the literature, but there remains a significant discrepancy between current theory and measured geometry

REVIEW - A reference data set for retinal vessel profiles

This paper describes REVIEW, a new retinal vessel reference dataset. This dataset includes 16 images with 193 vessel segments, demonstrating a variety of pathologies and vessel types. The vessel edges are marked by three observers using a special drawing tool. The paper also describes the algorithm used to process these segments to produce vessel profiles, against which vessel width measurement algorithms can be assessed. Recommendations are given for use of the dataset in performance assessment. REVIEW can be downloaded from http://ReviewDB.lincoln.ac.uk

Study of the dislocation and the changes of the vessels before diabetic retinopathy

One of the main challenges remains the understanding of the diabetes effect in hemodynamic functionality (blood flow, oxygen perfusion etc.) and vascular geometric adaptation before the first lesions of diabetic retinopathy appear. Crucial and Important part is the study of the progress of diabetes through the screening program. Multiple images of the same patient are useful in order to understand the progress by comparing these images either by taking vascular measurements or/and using registration algorithms

An active contour model for segmenting and measuring retinal vessels

This paper presents an algorithm for segmenting and measuring retinal vessels, by growing a "Ribbon of Twins" active contour model, which uses two pairs of contours to capture each vessel edge, while maintaining width consistency. The algorithm is initialized using a generalized morphological order filter to identify approximate vessels centerlines. Once the vessel segments are identified the network topology is determined using an implicit neural cost function to resolve junction configurations. The algorithm is robust, and can accurately locate vessel edges under difficult conditions, including noisy blurred edges, closely parallel vessels, light reflex phenomena, and very fine vessels. It yields precise vessel width measurements, with sub-pixel average width errors. We compare the algorithm with several benchmarks from the literature, demonstrating higher segmentation sensitivity and more accurate width measurement

A Bayesian framework for the local configuration of retinal junctions

Retinal images contain forests of mutually intersecting and overlapping venous and arterial vascular trees. The geometry of these trees shows adaptation to vascular diseases including diabetes, stroke and hypertension. Segmentation of the retinal vascular network is complicated by inconsistent vessel contrast, fuzzy edges, variable image quality, media opacities, complex intersections and overlaps. This paper presents a Bayesian approach to resolving the con- figuration of vascular junctions to correctly construct the vascular trees. A probabilistic model of vascular joints (terminals, bridges and bifurcations) and their configuration in junctions is built, and Maximum A Posteriori (MAP) estimation used to select most likely configurations. The model is built using a reference set of 3010 joints extracted from the DRIVE public domain vascular segmentation dataset, and evaluated on 3435 joints from the DRIVE test set, demonstrating an accuracy of 95.2%

What is the pattern of self-harm and prison rule-breaking behaviour in personality disordered offenders in a high secure prison?

Purpose – The purpose of this paper is to describe the pattern of self-harm (SH) and proven prison-rule-breaking (PRB) behaviour in prisoners receiving treatment for personality disorders (PDs) within a high secure prison. Design/methodology/approach – A comparative quantitative case study design supported the understanding of the frequency and pattern of SH and PRB behavior across two stages of a personality disorder (PD) treatment programme for 74 male prisoners. Data obtained from the prison’s records was analysed using dependent t tests, chi square test of independence and time-frequency analyses. Findings – Inferential statistics showed that the frequency of SH and PRB behaviour statistically increased across two phases of the PD treatment programme, however the method of SH or type of PRB behaviour engaged in did not change. Mapping the frequencies of incidents using a time-frequency analysis shows the patterns of both behaviours to be erratic, peaking in the latter phase of treatment, yet the frequency of incidents tended to decline over time. Originality/value – This is the first study to explore SH and PRB behaviours in men across two phases of a PD treatment programme. This study highlights the need for continued psychological support alongside the PD treatment programme with a focus on supporting men in treatment to effectively manage their SH and PRB behaviour

Microaneurysm detection using deep learning and interleaved freezing

Diabetes affects one in eleven adults. Diabetic retinopathy is a microvascular complication of diabetes and the leading cause of blindness in the working-age population. Microaneurysms are the earliest clinical signs of diabetic retinopathy. This paper proposes an automatic method for detecting microaneurysms in fundus photographies. A novel patch-based fully convolutional neural network for detection of microaneurysms is proposed. Compared to other methods that require five processing stages, it requires only two. Furthermore, a novel network fine-tuning scheme called Interleaved Freezing is presented. This procedure significantly reduces the amount of time needed to re-train a network and produces competitive results. The proposed method was evaluated using publicly available and widely used datasets: E-Ophtha and ROC. It outperforms the state-of-the-art methods in terms of free-response receiver operatic characteristic (FROC) metric. Simplicity, performance, efficiency and robustness of the proposed method demonstrates its suitability for diabetic retinopathy screening applications