Fast Retinal Vessel Detection and Measurement Using Wavelets and Edge Location Refinement

The relationship between changes in retinal vessel morphology and the onset and progression of diseases such as diabetes, hypertension and retinopathy of prematurity (ROP) has been the subject of several large scale clinical studies. However, the difficulty of quantifying changes in retinal vessels in a sufficiently fast, accurate and repeatable manner has restricted the application of the insights gleaned from these studies to clinical practice. This paper presents a novel algorithm for the efficient detection and measurement of retinal vessels, which is general enough that it can be applied to both low and high resolution fundus photographs and fluorescein angiograms upon the adjustment of only a few intuitive parameters. Firstly, we describe the simple vessel segmentation strategy, formulated in the language of wavelets, that is used for fast vessel detection. When validated using a publicly available database of retinal images, this segmentation achieves a true positive rate of 70.27%, false positive rate of 2.83%, and accuracy score of 0.9371. Vessel edges are then more precisely localised using image profiles computed perpendicularly across a spline fit of each detected vessel centreline, so that both local and global changes in vessel diameter can be readily quantified. Using a second image database, we show that the diameters output by our algorithm display good agreement with the manual measurements made by three independent observers. We conclude that the improved speed and generality offered by our algorithm are achieved without sacrificing accuracy. The algorithm is implemented in MATLAB along with a graphical user interface, and we have made the source code freely available. 

Multi-scale colorectal tumour segmentation using a novel coarse to fine strategy

This paper addresses the problem of colorectal tumour segmentation in complex real world imagery. For efficient segmentation, a multi-scale strategy is developed for extracting the potentially cancerous region of interest (ROI) based on colour histograms while searching for the best texture resolution. To achieve better segmentation accuracy, we apply a novel bag-of-visual-words method based on rotation invariant raw statistical features and random projection based l2-norm sparse representation to classify tumour areas in histopathology images. Experimental results on 20 real world digital slides demonstrate that the proposed algorithm results in better recognition accuracy than several state of the art segmentation techniques.

Profiling: a Strategy for Successful Volunteer Recruitment in Credit Unions

Credit unions are non-profit financial organisations that provide financial services to their members. They are located in 97 countries across the world. All credit unions are governed by a volunteer board and many are reliant on volunteers for all their labour requirements. However, recruiting volunteers is a problem. The literature on recruitment issues in volunteering in general, suggests that the not-for-profit sector looks to the private sector for guidance on recruitment policies and approaches. One such approach which is considered in this paper is ‘market segmentation’ wherein the potential volunteer body is profiled to determine if an individual is likely to volunteer and if they are, to identify the type of role they are most likely to be attracted to. Prior literature on volunteering in non-profit organisations suggests that certain types of individual (dominant individuals) are more likely to volunteer. This paper investigates whether this dominant status profile is evident amongst volunteers in credit unions in Northern Ireland (NI). The study finds that people with dominant characteristics are more likely to be attracted to volunteering to the board of directors and individuals who have less dominant traits overall should be offered more social/participative type roles. This information can be used by credit union governing boards for volunteer recruitment, retention and management purposes.

The spectrum of endogenous human chromogranin A-derived peptides identified using a modified proteomic strategy.

The hypothesis that chromogranin A (CgA), a protein of neuroendocrine cell secretory granules, may be a precursor of biologically active peptides, rests on observed activities of peptide fragments largely produced by exogenous protease digestion of the bovine protein. Here we have adopted a modified proteomic strategy to isolate and characterise human CgA-derived peptides produced by endogenous prohormone convertases. Initial focus was on an insulinoma as previous studies have shown that CgA is rapidly processed in pancreatic beta cells and that tumours arising from these express appropriate prohormone convertases. Eleven novel peptides were identified arising from processing at both monobasic and dibasic sites and processing was most evident in the C-terminal domain of the protein. Some of these peptides were identified in endocrine tumours, such as mid-gut carcinoid and phaeochromocytoma, which arise from endocrine cells of different phenotype and in different anatomical sites. Two of the most interesting peptides, GR-44 and ER-37, representing the C-terminal region of CgA, were found to be amidated. These data would imply that the intact protein is C-terminally amidated and that these peptides are probably biologically active. The spectrum of novel CgA-derived peptides, described in the present study, should provide a basis for biological evaluation of authentic entities.

alpha-Synuclein aggregation in neurodegenerative diseases and its inhibition as a potential therapeutic strategy

There is strong evidence for the involvement of alpha-synuclein in the pathologies of several neurodegenerative disorders, including PD (Parkinson's disease). Development of disease appears to be linked to processes that increase the rate at which alpha-synuclein forms aggregates. These processes include increased protein concentration (via either increased rate of synthesis or decreased rate of degradation), and altered forms of alpha-synuclein (such as truncations, missense mutations, or chemical modifications by oxidative reactions). Aggregated forms of the protein are toxic to cells and one therapeutic strategy would be to reduce the rate at which aggregation occurs. To this end we have designed several peptides that reduce alpha-synuclein aggregation. A cell-permeable version of one such peptide was able to inhibit the DNA damage induced by Fe(II) in neuronal cells transfected with alpha-synuclein (A53T), a familial PD-associated mutation.

Inhibitors of alpha-synuclein oligomerization and toxicity: a future therapeutic strategy for Parkinson's disease and related disorders.

An abundance of genetic, histopathological, and biochemical evidence has implicated the neuronal protein, alpha-synuclein (alpha-syn) as a key player in the development of several neurodegenerative diseases, the so-called synucleinopathies, of which Parkinson's disease (PD) is the most prevalent. Development of disease appears to be linked to events that increase the intracellular concentration of alpha-syn or cause its chemical modification, either of which can accelerate the rate at which it forms aggregates. Examples of such events include increased copy number of genes, decreased rate of degradation via the proteasome or other proteases, or altered forms of alpha-syn, such as truncations, missense mutations, or chemical modifications by oxidative reactions. Aggregated forms of the protein, especially newly formed soluble aggregates, are toxic to cells, so that one therapeutic strategy would be to reduce the rate at which such oligomerization occurs. We have therefore designed several peptides and also identified small molecules that can inhibit alpha-syn oligomerization and toxicity in vitro. These compounds could serve as lead compounds for the design of new drugs for the treatment of PD and related disorders in the future.

What motion distributions yield global transparency and spatial segmentation?

We have examined the ability of observers to parse bimodal local-motion distributions into two global motion surfaces, either overlapping (yielding transparent motion) or spatially segregated (yielding a motion boundary). The stimuli were random dot kinematograms in which the direction of motion of each dot was drawn from one of two rectangular probability distributions. A wide range of direction distribution widths and separations was tested. The ability to discriminate the direction of motion of one of the two motion surfaces from the direction of a comparison stimulus was used as an objective test of the perception of two discrete surfaces. Performance for both transparent and spatially segregated motion was remarkably good, being only slightly inferior to that achieved with a single global motion surface. Performance was consistently better for segregated motion than for transparency. Whereas transparent motion was only perceived with direction distributions which were separated by a significant gap, segregated motion could be seen with abutting or even partially overlapping direction distributions. For transparency, the critical gap increased with the range of directions in the distribution. This result does not support models in which transparency depends on detection of a minimum size of gap defining a bimodal direction distribution. We suggest, instead, that the operations which detect bimodality are scaled (in the direction domain) with the overall range of distributions. This yields a flexible, adaptive system that determines whether a gap in the direction distribution serves as a segmentation cue or is smoothed as part of a unitary computation of global motion.

Continuity - based and discontinuity - based segmentation in transparent and spatially segregated global motion

The mechanisms underlying the parsing of a spatial distribution of velocity vectors into two adjacent (spatially segregated) or overlapping (transparent) motion surfaces were examined using random dot kinematograms. Parsing might occur using either of two principles. Surfaces might be defined on the basis of similarity of motion vectors and then sharp perceptual boundaries drawn between different surfaces (continuity-based segmentation). Alternatively, detection of a high gradient of direction or speed separating the motion surfaces might drive the process (discontinuity-based segmentation). To establish which method is used, we examined the effect of blurring the motion direction gradient. In the case of a sharp direction gradient, each dot had one of two directions differing by 135°. With a shallow gradient, most dots had one of two directions but the directions of the remainder spanned the range between one motion-defined surface and the other. In the spatial segregation case the gradient defined a central boundary separating two regions. In the transparent version the dots were randomly positioned. In both cases all dots moved with the same speed and existed for only two frames before being randomly replaced. The ability of observers to parse the motion distribution was measured in terms of their ability to discriminate the direction of one of the two surfaces. Performance was hardly affected by spreading the gradient over at least 25% of the dots (corresponding to a 1° strip in the segregation case). We conclude that detection of sharp velocity gradients is not necessary for distinguishing different motion surfaces.