113 resultados para Active regions

em Consorci de Serveis Universitaris de Catalunya (CSUC), Spain


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Purpose: To evaluate the suitability of an improved version of an automatic segmentation method based on geodesic active regions (GAR) for segmenting cerebral vasculature with aneurysms from 3D X-ray reconstruc-tion angiography (3DRA) and time of °ight magnetic resonance angiography (TOF-MRA) images available in the clinical routine.Methods: Three aspects of the GAR method have been improved: execution time, robustness to variability in imaging protocols and robustness to variability in image spatial resolutions. The improved GAR was retrospectively evaluated on images from patients containing intracranial aneurysms in the area of the Circle of Willis and imaged with two modalities: 3DRA and TOF-MRA. Images were obtained from two clinical centers, each using di®erent imaging equipment. Evaluation included qualitative and quantitative analyses ofthe segmentation results on 20 images from 10 patients. The gold standard was built from 660 cross-sections (33 per image) of vessels and aneurysms, manually measured by interventional neuroradiologists. GAR has also been compared to an interactive segmentation method: iso-intensity surface extraction (ISE). In addition, since patients had been imaged with the two modalities, we performed an inter-modality agreement analysis with respect to both the manual measurements and each of the two segmentation methods. Results: Both GAR and ISE di®ered from the gold standard within acceptable limits compared to the imaging resolution. GAR (ISE, respectively) had an average accuracy of 0.20 (0.24) mm for 3DRA and 0.27 (0.30) mm for TOF-MRA, and had a repeatability of 0.05 (0.20) mm. Compared to ISE, GAR had a lower qualitative error in the vessel region and a lower quantitative error in the aneurysm region. The repeatabilityof GAR was superior to manual measurements and ISE. The inter-modality agreement was similar between GAR and the manual measurements. Conclusions: The improved GAR method outperformed ISE qualitatively as well as quantitatively and is suitable for segmenting 3DRA and TOF-MRA images from clinical routine.

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In this paper a colour texture segmentation method, which unifies region and boundary information, is proposed. The algorithm uses a coarse detection of the perceptual (colour and texture) edges of the image to adequately place and initialise a set of active regions. Colour texture of regions is modelled by the conjunction of non-parametric techniques of kernel density estimation (which allow to estimate the colour behaviour) and classical co-occurrence matrix based texture features. Therefore, region information is defined and accurate boundary information can be extracted to guide the segmentation process. Regions concurrently compete for the image pixels in order to segment the whole image taking both information sources into account. Furthermore, experimental results are shown which prove the performance of the proposed method

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An unsupervised approach to image segmentation which fuses region and boundary information is presented. The proposed approach takes advantage of the combined use of 3 different strategies: the guidance of seed placement, the control of decision criterion, and the boundary refinement. The new algorithm uses the boundary information to initialize a set of active regions which compete for the pixels in order to segment the whole image. The method is implemented on a multiresolution representation which ensures noise robustness as well as computation efficiency. The accuracy of the segmentation results has been proven through an objective comparative evaluation of the method

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For the ∼1% of the human genome in the ENCODE regions, only about half of the transcriptionally active regions (TARs) identified with tiling microarrays correspond to annotated exons. Here we categorize this large amount of “unannotated transcription.” We use a number of disparate features to classify the 6988 novel TARs—array expression profiles across cell lines and conditions, sequence composition, phylogenetic profiles (presence/absence of syntenic conservation across 17 species), and locations relative to genes. In the classification, we first filter out TARs with unusual sequence composition and those likely resulting from cross-hybridization. We then associate some of those remaining with proximal exons having correlated expression profiles. Finally, we cluster unclassified TARs into putative novel loci, based on similar expression and phylogenetic profiles. To encapsulate our classification, we construct a Database of Active Regions and Tools (DART.gersteinlab.org). DART has special facilities for rapidly handling and comparing many sets of TARs and their heterogeneous features, synchronizing across builds, and interfacing with other resources. Overall, we find that ∼14% of the novel TARs can be associated with known genes, while ∼21% can be clustered into ∼200 novel loci. We observe that TARs associated with genes are enriched in the potential to form structural RNAs and many novel TAR clusters are associated with nearby promoters. To benchmark our classification, we design a set of experiments for testing the connectivity of novel TARs. Overall, we find that 18 of the 46 connections tested validate by RT-PCR and four of five sequenced PCR products confirm connectivity unambiguously.

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Background: Information about the composition of regulatory regions is of great value for designing experiments to functionally characterize gene expression. The multiplicity of available applications to predict transcription factor binding sites in a particular locus contrasts with the substantial computational expertise that is demanded to manipulate them, which may constitute a potential barrier for the experimental community. Results: CBS (Conserved regulatory Binding Sites, http://compfly.bio.ub.es/CBS) is a public platform of evolutionarily conserved binding sites and enhancers predicted in multiple Drosophila genomes that is furnished with published chromatin signatures associated to transcriptionally active regions and other experimental sources of information. The rapid access to this novel body of knowledge through a user-friendly web interface enables non-expert users to identify the binding sequences available for any particular gene, transcription factor, or genome region. Conclusions: The CBS platform is a powerful resource that provides tools for data mining individual sequences and groups of co-expressed genes with epigenomics information to conduct regulatory screenings in Drosophila.

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We propose a probabilistic object classifier for outdoor scene analysis as a first step in solving the problem of scene context generation. The method begins with a top-down control, which uses the previously learned models (appearance and absolute location) to obtain an initial pixel-level classification. This information provides us the core of objects, which is used to acquire a more accurate object model. Therefore, their growing by specific active regions allows us to obtain an accurate recognition of known regions. Next, a stage of general segmentation provides the segmentation of unknown regions by a bottom-strategy. Finally, the last stage tries to perform a region fusion of known and unknown segmented objects. The result is both a segmentation of the image and a recognition of each segment as a given object class or as an unknown segmented object. Furthermore, experimental results are shown and evaluated to prove the validity of our proposal

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The article presents and discusses estimates of social and economic indicators for Italy’s regions in benchmark years roughly from Unification to the present day: life expectancy, education, GDP per capita at purchasing power parity, and the new Human Development Index (HDI). A broad interpretative hypothesis, based on the distinction between passive and active modernization, is proposed to account for the evolution of regional imbalances over the long-run. In the lack of active modernization, Southern Italy converged thanks to passive modernization, i.e., State intervention: however, this was more effective in life expectancy, less successful in education, expensive and as a whole ineffective in GDP. As a consequence, convergence in the HDI occurred from the late XIX century to the 1970s, but came to a sudden halt in the last decades of the XX century.

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This study aims at analyzing the determinants of FDI (foreign direct investment) inflows for a group of European regions. The originality of this approach lies in the use of disaggregated regional data. First, we develop a qualitative description of our database and discuss the importance of the macroeconomic determinants in attracting FDI. Then, we provide an econometric exercise to identify the potential determinants of FDI. In spite of choosing regions presenting economic similarities, we show that regional FDI inflows rely on a combination of factors that differs from one region to another.

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This paper surveys the recent literature on convergence across countries and regions. I discuss the main convergence and divergence mechanisms identified in the literature and develop a simple model that illustrates their implications for income dynamics. I then review the existing empirical evidence and discuss its theoretical implications. Early optimism concerning the ability of a human capital-augmented neoclassical model to explain productivity differences across economies has been questioned on the basis of more recent contributions that make use of panel data techniques and obtain theoretically implausible results. Some recent research in this area tries to reconcile these findings with sensible theoretical models by exploring the role of alternative convergence mechanisms and the possible shortcomings of panel data techniques for convergence analysis.

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This paper analyzes the growth and employment effects of the 1994-99 Community Support Framework (CSF) for the Objective 1 Spanish regions using a simple supply-side model estimated with a panel of regional data. The results suggest that the impact of the Structural Funds in Spain has been quite sizable, adding around a percentage point to annual output growth in the average Objective 1 region and 0.4 points to employment growth. Over the period 1994-2000, the Framework has resulted in the creation of over 300,000 new jobs and has eliminated 20% of the initial gap in income per capita between the assisted regions and the rest of the country.

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Maybe because of the inconclusive nature of the results on the impact of public capital on output at the regional level, the issue of the possible existence of the regional spillovers from public capital formation has received little attention. The objective of this paper is to provide evidence on the possible existence of such spillovers. We consider the case of Spain and its seventeen regions. Our methodological approach consists in estimating an aggregate VAR model for Spain as well as seventeen region-specific VAR models in which both capital installed in the region and capital installed outside the region are allowed to play a role in enhancing regional output. The estimation results can be summarized as follows. The aggregate effects of public capital formation in Spain are important. They cannot, however, be captured in their entirety by the direct effects in each region from public capital installed in the region itself. When for each region both the capital installed in the region and the capital installed outside the region are considered the total disaggregated effect from the seventeen regional models are very much in line with the aggregate results. Furthermore, the aggregate effect seems to be due in almost equal parts to the direct and spillover effects of public capital formation. Ultimately, this paper establishes the relevance of both capital installed in each region and spillover effects in the understanding of the regional decomposition of the aggregate effects of public capital formation. In doing so it opens the door to some tantalizing and potentially highly charged research issues in terms of the determination of the optimal location of public investment projects.

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The present paper aims at analyzing the sources of productivity in Europe to account for its recent underperformance and identify potential geographic idiosyncracies. We study the productivity performance and its sources in a sample of ten European regions belonging to four countries (France, Germany, Italy and Spain). Exploiting the increasing availability of disaggregated data at regional level in Europe, we propose both a descriptive statistics and an econometric analysis of productivity sources since 1995. Our main finding is that the sources of labor productivity are rather heterogeneous across our sample but may be associated with regional or national idiosyncracies.

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We evaluate the presence of effects from joining one of four active labour market programs in Romania in the late 1990s compared to the no-program state. Using rich follow-up survey data and propensity score matching, we find that three programs (training and retraining, self-employment assistance, and employment and relocation services) had success in improving participants' economic outcomes and were cost-beneficial from society's perspective. In contrast, public employment was found detrimental for the employment prospects of its participants.