897 resultados para Automatic segmentation
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Market segmentation is an important issue when estimating the implicit price for an environmental amenity from a surrogate market like property. This paper tests the hypothesis of a segmentation of the housing market between tourists and residents and computes the implicit price for natural landscape quality in Swiss alpine resorts. The results show a clear segmentation between both groups of consumers, although tests also show that the estimated coefficient for landscape is similar in the tourists' model and in the residents'. However, since the functional form is non linear, the nominal - rather than relative - value of a change in natural landscape quality is higher in the tourist housing market than in the residents'. Hence, considering the segmentation of the market between tourists and residents is essential in order to provide valid estimates of the nominal implicit price of natural landscape quality.
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Inference of Markov random field images segmentation models is usually performed using iterative methods which adapt the well-known expectation-maximization (EM) algorithm for independent mixture models. However, some of these adaptations are ad hoc and may turn out numerically unstable. In this paper, we review three EM-like variants for Markov random field segmentation and compare their convergence properties both at the theoretical and practical levels. We specifically advocate a numerical scheme involving asynchronous voxel updating, for which general convergence results can be established. Our experiments on brain tissue classification in magnetic resonance images provide evidence that this algorithm may achieve significantly faster convergence than its competitors while yielding at least as good segmentation results.
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Abstract
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Peer-reviewed
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The most adequate approach for benchmarking web accessibility is manual expert evaluation supplemented by automatic analysis tools. But manual evaluation has a high cost and is impractical to be applied on large websites. In reality, there is no choice but to rely on automated tools when reviewing large web sites for accessibility. The question is: to what extent the results from automatic evaluation of a web site and individual web pages can be used as an approximation for manual results? This paper presents the initial results of an investigation aimed at answering this question. He have performed both manual and automatic evaluations of the accessibility of web pages of two sites and we have compared the results. In our data set automatically retrieved results could most definitely be used as an approximation manual evaluation results.
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This paper proposes to enrich RBMTdictionaries with Named Entities(NEs) automatically acquired fromWikipedia. The method is appliedto the Apertium English-Spanishsystem and its performance comparedto that of Apertium with and withouthandtagged NEs. The system withautomatic NEs outperforms the onewithout NEs, while results vary whencompared to a system with handtaggedNEs (results are comparable forSpanish to English but slightly worstfor English to Spanish). Apart fromthat, adding automatic NEs contributesto decreasing the amount of unknownterms by more than 10%.
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The paper deals with the development and application of the methodology for automatic mapping of pollution/contamination data. General Regression Neural Network (GRNN) is considered in detail and is proposed as an efficient tool to solve this problem. The automatic tuning of isotropic and an anisotropic GRNN model using cross-validation procedure is presented. Results are compared with k-nearest-neighbours interpolation algorithm using independent validation data set. Quality of mapping is controlled by the analysis of raw data and the residuals using variography. Maps of probabilities of exceeding a given decision level and ?thick? isoline visualization of the uncertainties are presented as examples of decision-oriented mapping. Real case study is based on mapping of radioactively contaminated territories.
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We present a method to automatically segment red blood cells (RBCs) visualized by digital holographic microscopy (DHM), which is based on the marker-controlled watershed algorithm. Quantitative phase images of RBCs can be obtained by using off-axis DHM along to provide some important information about each RBC, including size, shape, volume, hemoglobin content, etc. The most important process of segmentation based on marker-controlled watershed is to perform an accurate localization of internal and external markers. Here, we first obtain the binary image via Otsu algorithm. Then, we apply morphological operations to the binary image to get the internal markers. We then apply the distance transform algorithm combined with the watershed algorithm to generate external markers based on internal markers. Finally, combining the internal and external markers, we modify the original gradient image and apply the watershed algorithm. By appropriately identifying the internal and external markers, the problems of oversegmentation and undersegmentation are avoided. Furthermore, the internal and external parts of the RBCs phase image can also be segmented by using the marker-controlled watershed combined with our method, which can identify the internal and external markers appropriately. Our experimental results show that the proposed method achieves good performance in terms of segmenting RBCs and could thus be helpful when combined with an automated classification of RBCs.
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Many Spanish destinations are now considering low cost airlines (LCA) important for attracting tourists. However, there is little evidence on the characteristics travelers using low cost airlines and their flight preferences. Typical segmentation of air travelers are business versus leisure travelers and business versus tourist fares. The aim of this paper is to obtain a deeper understanding of the demand of LCA through a segmentation analysis, based on 808 foreign travelers who used Girona airport, that focuses on low cost travelers’ valuations of different flight attributes and trip related characteristics
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This paper presents the evaluation results of the methods submitted to Challenge US: Biometric Measurements from Fetal Ultrasound Images, a segmentation challenge held at the IEEE International Symposium on Biomedical Imaging 2012. The challenge was set to compare and evaluate current fetal ultrasound image segmentation methods. It consisted of automatically segmenting fetal anatomical structures to measure standard obstetric biometric parameters, from 2D fetal ultrasound images taken on fetuses at different gestational ages (21 weeks, 28 weeks, and 33 weeks) and with varying image quality to reflect data encountered in real clinical environments. Four independent sub-challenges were proposed, according to the objects of interest measured in clinical practice: abdomen, head, femur, and whole fetus. Five teams participated in the head sub-challenge and two teams in the femur sub-challenge, including one team who tackled both. Nobody attempted the abdomen and whole fetus sub-challenges. The challenge goals were two-fold and the participants were asked to submit the segmentation results as well as the measurements derived from the segmented objects. Extensive quantitative (region-based, distance-based, and Bland-Altman measurements) and qualitative evaluation was performed to compare the results from a representative selection of current methods submitted to the challenge. Several experts (three for the head sub-challenge and two for the femur sub-challenge), with different degrees of expertise, manually delineated the objects of interest to define the ground truth used within the evaluation framework. For the head sub-challenge, several groups produced results that could be potentially used in clinical settings, with comparable performance to manual delineations. The femur sub-challenge had inferior performance to the head sub-challenge due to the fact that it is a harder segmentation problem and that the techniques presented relied more on the femur's appearance.
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Recent years have been characterized by a series of publications in the field of firearms investigation questioning the reliability and objectivity of such examination. This research investigates new solutions to decrease the subjective component affecting the evaluation that follows the comparison of impressions left by a firearm on the surface of spent cartridge cases. An automatic comparison system based on 3D measurements has been developed and coupled to a bivariate evaluative model allowing assigning likelihood ratios. Based on a dataset of 79 pistols (all SIG Sauer 9 mm Luger caliber), the system shows a very high discriminating power and the LRs that it provides are very indicative of the true state under both the prosecution and the defense propositions. For example, likelihood ratios exceeding a billion are predominantly obtained when impressions originating from the same source are compared. The system is also characterized by relatively low rates (≤1%) of misleading evidence depending on the firearm considered.
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En aquest projecte fem un estudi de diferents mètodes per a la segmentació i extracció de línies de mapes de metro com a suport per a daltònics. Hem aplicat dos mètodes amb intervenció de l’usuari i cinc mètodes automàtics on fem servir K-means per a la segmentació de color i Hough per a l’extracció de línies. Dels mètodes amb intervenció obtenim millors resultats amb un mètode d’assignació aproximada del color, i entre els autoàatics tenim com a millor una solució ad-hoc sense paràmetres aplicada sobre l’espai RGB. D’acord amb els resultats experimentals, aquests mètodes ens permeten fer una bona segmentació i extracció de les línies de metro.
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BACKGROUND: Chronic kidney disease (CKD) accelerates vascular stiffening related to age. Arterial stiffness may be evaluated measuring the carotid-femoral pulse wave velocity (PWV) or more simply, as recommended by KDOQI, monitoring pulse pressure (PP). Both correlate to survival and incidence of cardiovascular disease. PWV can also be estimated on the brachial artery using a Mobil-O-Graph; a non-operator dependent automatic device. The aim was to analyse whether, in a dialysis population, PWV obtained by Mobil-O-Graph (MogPWV) is more sensitive for vascular aging than PP. METHODS: A cohort of 143 patients from 4 dialysis units has been followed measuring MogPWV and PP every 3 to 6 months and compared to a control group with the same risk factors but an eGFR > 30 ml/min. RESULTS: MogPWV contrarily to PP did discriminate the dialysis population from the control group. The mean difference translated in age between the two populations was 8.4 years. The increase in MogPWV, as a function of age, was more rapid in the dialysis group. 13.3% of the dialysis patients but only 3.0% of the control group were outliers for MogPWV. The mortality rate (16 out of 143) was similar in outliers and inliers (7.4 and 8.0%/year). Stratifying patients according to MogPWV, a significant difference in survival was seen. A high parathormone (PTH) and to be dialysed for a hypertensive nephropathy were associated to a higher baseline MogPWV. CONCLUSIONS: Assessing PWV on the brachial artery using a Mobil-O-Graph is a valid and simple alternative, which, in the dialysis population, is more sensitive for vascular aging than PP. As demonstrated in previous studies PWV correlates to mortality. Among specific CKD risk factors only PTH is associated with a higher baseline PWV. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02327962.