Spearhead Health Inequalities Intervention Tool: background information

This document provides background information on the context for the Spearhead Health Inequalities Intervention Tool.

Apprenticeship Review - Background Issues Paper

The Government’s Action Plan for Jobs contained the following commitment regarding a review of apprenticeship: “Initiate a review of the apprenticeship training model, including costs, duration and demand with a view to providing an updated model of training that delivers the necessary skilled workforce to service the needs of a rapidly changing economy and ensures appropriate balance between supply and demand.” The first stage of the review process involves the preparation of this background issues paper which, inter alia, provides a factual description of the current system of apprenticeship, including the governance arrangements, trends and forecasts in relation to recruitment and identified strengths and weaknesses of the model and proposes a range of possible options for change.

Attracting, Developing and Training Effective Teachers - OECD Country Background Report for Ireland

This Country Background Report (CBR) on the teaching career in Ireland forms part of the major OECD study “Attracting, Developing and Retaining Effective Teachers.” Similar reports are being submitted from twenty six other countries. Nine of these countries are also engaged on ‘thematic’ studies of the teaching career, involving site visits by external reviewers appointed by the OECD. The format of the CBRs follows a common pattern, set out by the OECD in its Design and Implementation Plan. This is to facilitate comparative analysis of sub-themes of the reports. Thus, each CBR involves six chapters. The first two – “the national context” and “school system and the teaching force”– are intended to provide succinct overviews of these themes in line with queries posed in the OECD documentation. Each of the other four chapters is designed on a common format – identification of policy concerns; data, trends and factors; policy initiatives and their impact. Specific questions are posed regarding data, trends and factors. The same questions may be posed in relation to more than one sub-theme which gives rise to some repetition in the report, but is important for the comparative analysis.

Representing diffusion MRI in 5D for segmentation of white matter tracts with a level set method.

We present a method for segmenting white matter tracts from high angular resolution diffusion MR. images by representing the data in a 5 dimensional space of position and orientation. Whereas crossing fiber tracts cannot be separated in 3D position space, they clearly disentangle in 5D position-orientation space. The segmentation is done using a 5D level set method applied to hyper-surfaces evolving in 5D position-orientation space. In this paper we present a methodology for constructing the position-orientation space. We then show how to implement the standard level set method in such a non-Euclidean high dimensional space. The level set theory is basically defined for N-dimensions but there are several practical implementation details to consider, such as mean curvature. Finally, we will show results from a synthetic model and a few preliminary results on real data of a human brain acquired by high angular resolution diffusion MRI.

Do you look after someone? And are you from a black or minority ethnic background? (English and translations)

This leaflet is for BME (Black and Minority Ethnic) Carers. Carers can be people of all ages including children, young people, parents, older people. There is a cut off slip for BME Carers to fill in with their details. This information can then be sent to the Carer Worker in their local Trust. Details are on the leaflet.

Segmentación interactiva multi-clase de personas

La segmentació de persones es molt difícil a causa de la variabilitat de les diferents condicions, com la postura que aquestes adoptin, color del fons, etc. Per realitzar aquesta segmentació existeixen diferents tècniques, que a partir d'una imatge ens retornen un etiquetat indicant els diferents objectes presents a la imatge. El propòsit d'aquest projecte és realitzar una comparativa de les tècniques recents que permeten fer segmentació multietiqueta i que son semiautomàtiques, en termes de segmentació de persones. A partir d'un etiquetatge inicial idèntic per a tots els mètodes utilitzats, s'ha realitzat una anàlisi d'aquests, avaluant els seus resultats sobre unes dades publiques, analitzant 2 punts: el nivell de interacció i l'eficiència.

Background morbidity in HIV vaccine trial participants from various geographic regions as assessed by unsolicited adverse events.

Background: Recently, more clinical trials are being conducted in Africa and Asia, therefore, background morbidity in the respective populations is of interest. Between 2000 and 2007, the International AIDS Vaccine Initiative sponsored 19 Phase 1 or 2A preventive HIV vaccine trials in the US, Europe, Sub-Saharan Africa and India, enrolling 900 healthy HIV-1 uninfected volunteers.   Objective To assess background morbidity as reflected by unsolicited adverse events (AEs), unrelated to study vaccine, reported in clinical trials from four continents. Methods All but three clinical trials were double-blind, randomized, and placebo-controlled. Study procedures and data collection methods were standardized. The frequency and severity of AEs reported during the first year of the trials were analyzed. To avoid confounding by vaccine-related events, solicited reactogenicity and other AEs occurring within 28 d after any vaccination were excluded. Results In total, 2134 AEs were reported by 76% of all participants; 73% of all events were mild. The rate of AEs did not differ between placebo and vaccine recipients. Overall, the percentage of participants with any AE was higher in Africa (83%) compared with Europe (71%), US (74%) and India (65%), while the percentage of participants with AEs of moderate or greater severity was similar in all regions except India. In all regions, the most frequently reported AEs were infectious diseases, followed by gastrointestinal disorders. Conclusions Despite some regional differences, in these healthy participants selected for low risk of HIV infection, background morbidity posed no obstacle to clinical trial conduct and interpretation. Data from controlled clinical trials of preventive interventions can offer valuable insights into the health of the eligible population.

Chagas disease: what is known and what is needed - A background article

Chagas disease began millions of years ago as an enzootic disease of wild animals and started to be transmitted to man accidentally in the form of an anthropozoonosis when man invaded wild ecotopes. Endemic Chagas disease became established as a zoonosis over the last 200-300 years through forest clearance for agriculture and livestock rearing and adaptation of triatomines to domestic environments and to man and domestic animals as a food source. It is estimated that 15 to 16 million people are infected with Trypanosoma cruzi in Latin America and 75 to 90 million people are exposed to infection. When T. cruzi is transmitted to man through the feces of triatomines, at bite sites or in mucosa, through blood transfusion or orally through contaminated food, it invades the bloodstream and lymphatic system and becomes established in the muscle and cardiac tissue, the digestive system and phagocytic cells. This causes inflammatory lesions and immune responses, particularly mediated by CD4+, CD8+, interleukin-2 (IL) and IL-4, with cell and neuron destruction and fibrosis, and leads to blockage of the cardiac conduction system, arrhythmia, cardiac insufficiency, aperistalsis, and dilatation of hollow viscera, particularly the esophagus and colon. T. cruzi may also be transmitted from mother to child across the placenta and through the birth canal, thus causing abortion, prematurity, and organic lesions in the fetus. In immunosuppressed individuals, T. cruzi infection may become reactivated such that it spreads as a severe disease causing diffuse myocarditis and lesions of the central nervous system. Chagas disease is characterized by an acute phase with or without symptoms, and with entry point signs (inoculation chagoma or Romaña's sign), fever, adenomegaly, hepatosplenomegaly, and evident parasitemia, and an indeterminate chronic phase (asymptomatic, with normal results from electrocardiogram and x-ray of the heart, esophagus, and colon) or with a cardiac, digestive or cardiac-digestive form. There is great regional variation in the morbidity due to Chagas disease, and severe cardiac or digestive forms may occur in 10 to 50% of the cases, or the indeterminate form in the other asymptomatic cases, but with positive serology. Several acute cases have been reported from Amazon region most of them by T. cruzi I, Z3, and a hybrid ZI/Z3. We conclude this article presenting the ten top Chagas disease needs for the near future.

Improving Clustering Algorithms for Image Segmentation using Contour and Region Information

In image segmentation, clustering algorithms are very popular because they are intuitive and, some of them, easy to implement. For instance, the k-means is one of the most used in the literature, and many authors successfully compare their new proposal with the results achieved by the k-means. However, it is well known that clustering image segmentation has many problems. For instance, the number of regions of the image has to be known a priori, as well as different initial seed placement (initial clusters) could produce different segmentation results. Most of these algorithms could be slightly improved by considering the coordinates of the image as features in the clustering process (to take spatial region information into account). In this paper we propose a significant improvement of clustering algorithms for image segmentation. The method is qualitatively and quantitative evaluated over a set of synthetic and real images, and compared with classical clustering approaches. Results demonstrate the validity of this new approach

An information theoretic framework for image segmentation

In this paper, an information theoretic framework for image segmentation is presented. This approach is based on the information channel that goes from the image intensity histogram to the regions of the partitioned image. It allows us to define a new family of segmentation methods which maximize the mutual information of the channel. Firstly, a greedy top-down algorithm which partitions an image into homogeneous regions is introduced. Secondly, a histogram quantization algorithm which clusters color bins in a greedy bottom-up way is defined. Finally, the resulting regions in the partitioning algorithm can optionally be merged using the quantized histogram

Segmentation automatique de la matière grise et de la matière blanche par un algorithme génétique : une étude de validation

Résumé Objectif: l'observation des variations de volume de la matière grise (MG), de la matière blanche (MB), et du liquide céphalo-rachidien (LCR) est particulièrement utile dans l'étude de nombreux processus physiopathologiques, la mesure quantitative 'in vivo' de ces volumes présente un intérêt considérable tant en recherche qu'en pratique clinique. Cette étude présente et valide une méthode de segmentation automatique du cerveau avec mesure des volumes de MG et MB sur des images de résonance magnétique. Matériel et Méthode: nous utilisons un algorithme génétique automatique pour segmenter le cerveau en MG, MB et LCR à partir d'images tri-dimensionnelles de résonance magnétique en pondération Ti. Une étude morphométrique a été conduite sur 136 sujets hommes et femmes de 15 à 74 ans. L'algorithme a ensuite été validé par 5 approches différentes: I. Comparaison de mesures de volume sur un cerveau de cadavre par méthode automatique et par mesure de déplacement d'eau selon la méthode d'Archimède. 2. Comparaison de mesures surfaces sur des images bidimensionnelles segmentées soit par un traçage manuel soit par la méthode automatique. 3. Evaluation de la fiabilité de la segmentation par acquisitions et segmentations itératives du même cerveau. 4. Les volumes de MG, MB et LCR ont été utilisés pour une étude du vieillissement normal de la population. 5. Comparaison avec les données existantes de la littérature. Résultats: nous avons pu observer une variation de la mesure de 4.17% supplémentaire entre le volume d'un cerveau de cadavre mesuré par la méthode d'Archimède, en majeure partie due à la persistance de tissus après dissection_ La comparaison des méthodes de comptage manuel de surface avec la méthode automatique n'a pas montré de variation significative. L'épreuve du repositionnement du même sujet à diverses reprises montre une très bonne fiabilité avec une déviation standard de 0.46% pour la MG, 1.02% pour la MB et 3.59% pour le LCR, soit 0.19% pour le volume intracrânien total (VICT). L'étude morphométrique corrobore les résultats des études anatomiques et radiologiques existantes. Conclusion: la segmentation du cerveau par un algorithme génétique permet une mesure 100% automatique, fiable et rapide des volumes cérébraux in vivo chez l'individu normal.

Multimodal evaluation for medical image segmentation

This paper is a joint effort between five institutionsthat introduces several novel similarity measures andcombines them to carry out a multimodal segmentationevaluation. The new similarity measures proposed arebased on the location and the intensity values of themisclassified voxels as well as on the connectivity andthe boundaries of the segmented data. We showexperimentally that the combination of these measuresimprove the quality of the evaluation. The study that weshow here has been carried out using four differentsegmentation methods from four different labs applied toa MRI simulated dataset of the brain. We claim that ournew measures improve the robustness of the evaluation andprovides better understanding about the differencebetween segmentation methods.

3D Automated Lung Nodule Segmentation in HRCT

A fully-automated 3D image analysis method is proposed to segment lung nodules in HRCT. A specific gray-level mathematical morphology operator, the SMDC-connection cost, acting in the 3D space of the thorax volume is defined in order to discriminate lung nodules from other dense (vascular) structures. Applied to clinical data concerning patients with pulmonary carcinoma, the proposed method detects isolated, juxtavascular and peripheral nodules with sizes ranging from 2 to 20 mm diameter. The segmentation accuracy was objectively evaluated on real and simulated nodules. The method showed a sensitivity and a specificity ranging from 85% to 97% and from 90% to 98%, respectively.