999 resultados para subpixel level


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Purpose: To quantify the uncertainties of carotid plaque morphology reconstruction based on patient-specific multispectral in vivo magnetic resonance imaging (MRI) and their impacts on the plaque stress analysis. Materials and Methods: In this study, three independent investigators were invited to reconstruct the carotid bifurcation with plaque based on MR images from two subjects to study the geometry reconstruction reproducibility. Finite element stress analyses were performed on the carotid bifurcations, as well as the models with artificially modified plaque geometries to mimic the image segmentation uncertainties, to study the impacts of the uncertainties to the stress prediction. Results: Plaque reconstruction reproducibility was generally high in the study. The uncertainties among interobservers are around one or the subpixel level. It also shows that the predicted stress is relatively less sensitive to the arterial wall segmentation uncertainties, and more affected by the accuracy of lipid region definition. For a model with lipid core region artificially increased by adding one pixel on the lipid region boundary, it will significantly increase the maximum Von Mises Stress in fibrous cap (>100%) compared with the baseline model for all subjects. Conclusion: The current in vivo MRI in the carotid plaque could provide useful and reliable information for plaque morphology. The accuracy of stress analysis based on plaque geometry is subject to MRI quality. The improved resolution/quality in plaque imaging with newly developed MRI protocols would generate more realistic stress predictions.

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This paper presents a unique two-stage image restoration framework especially for further application of a novel rectangular poor-pixels detector, which, with properties of miniature size, light weight and low power consumption, has great value in the micro vision system. To meet the demand of fast processing, only a few measured images shifted up to subpixel level are needed to join the fusion operation, fewer than those required in traditional approaches. By maximum likelihood estimation with a least squares method, a preliminary restored image is linearly interpolated. After noise removal via Canny operator based level set evolution, the final high-quality restored image is achieved. Experimental results demonstrate effectiveness of the proposed framework. It is a sensible step towards subsequent image understanding and object identification.

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In the fields of Machine Vision and Photogrammetry, extracted straight lines from digital images can be used either as vector elements of a digital representation or as control entities that allow the determination of the camera interior and exterior orientation parameters. Applications related with image orientation require feature extraction with subpixel precision, to guarantee the reliability of the estimated parameters. This paper presents three approaches for straight line extraction with subpixel precision. The first approach considers the subpixel refinement based on the weighted average of subpixel positions calculated on the direction perpendicular to the segmented straight line. In the second approach, a parabolic function is adjusted to the grey level profile of neighboring pixels in a perpendicular direction to the segmented line, followed by an interpolation of this model to estimate subpixel coordinates of the line center. In the third approach, the subpixel refinement is performed with a parabolic surface adjustment to the grey level values of neighboring pixels around the segmented line. The intersection of this surface with a normal plane to the line direction generates a parabolic equation that allows estimating the subpixel coordinates of the point in the straight line, assuming that this is the critical point of this function. Three experiments with real images were made and the approach based on parabolic surface adjustment has presented better results.

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International evidence on the cost and effects of interventions for reducing the global burden of depression remain scarce. Aims: To estimate the population-level cost-effectiveness of evidence-based depression interventions and their contribution towards reducing current burden. Method: Primary-care-based depression interventions were modelled at the level of whole populations in 14 epidemiological subregions of the world. Total population-level costs (in international dollars or I$) and effectiveness (disability adjusted life years (DALYs) averted) were combined to form average and incremental cost-effectiveness ratios. Results: Evaluated interventions have the potential to reduce the current burden of depression by 10–30%. Pharmacotherapy with older antidepressant drugs, with or without proactive collaborative care, are currently more cost-effective strategies than those using newer antidepressants, particularly in lower-income subregions. Conclusions: Even in resource-poor regions, each DALYaverted by efficient depression treatments in primary care costs less than 1 year of average per capita income, making such interventions a cost-effective use of health resources. However, current levels of burden can only be reduced significantlyif there is a substantialincrease substantial increase intreatment coverage.

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Internationally, recognition of the role of assessment to inform the learning process has received much attention in recent years. Assessment for learning, not just of learning is being supported by an increasing body of literature providing strategies that teachers and their students can incorporate to support the learning process (Assessment Reform Group, 2002; Broadfoot & Black, 2004; James, 2006). Concurrently there has been an increase internationally in systemic accountability requirements of schools in terms of student results. The convergence of these two movements has resulted in some education systems promoting standards-driven reform involving authentic assessment and a re-examination of the relationship between the teacher and the student in the learning process. In this context standards are intended to be used as the basis for judgements of student achievement; while the results from assessment tasks are meant to both inform the teaching/learning process, and to report and track student progress. In such system, the role and reliability of teacher judgement takes centre stage.