954 resultados para automated detection
Resumo:
Studies concerning the physiological significance of Ca2+ sparks often depend on the detection and measurement of large populations of events in noisy microscopy images. Automated detection methods have been developed to quickly and objectively distinguish potential sparks from noise artifacts. However, previously described algorithms are not suited to the reliable detection of sparks in images where the local baseline fluorescence and noise properties can vary significantly, and risk introducing additional bias when applied to such data sets. Here, we describe a new, conceptually straightforward approach to spark detection in linescans that addresses this issue by combining variance stabilization with local baseline subtraction. We also show that in addition to greatly increasing the range of images in which sparks can be automatically detected, the use of a more accurate noise model enables our algorithm to achieve similar detection sensitivities with fewer false positives than previous approaches when applied both to synthetic and experimental data sets. We propose, therefore, that it might be a useful tool for improving the reliability and objectivity of spark analysis in general, and describe how it might be further optimized for specific applications.
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The POINT-AGAPE (Pixel-lensing Observations with the Isaac Newton Telescope-Andromeda Galaxy Amplified Pixels Experiment) survey is an optical search for gravitational microlensing events towards the Andromeda galaxy (M31). As well as microlensing, the survey is sensitive to many different classes of variable stars and transients. Here we describe the automated detection and selection pipeline used to identify M31 classical novae (CNe) and we present the resulting catalogue of 20 CN candidates observed over three seasons. CNe are observed both in the bulge region as well as over a wide area of the M31 disc. Nine of the CNe are caught during the final rise phase and all are well sampled in at least two colours. The excellent light-curve coverage has allowed us to detect and classify CNe over a wide range of speed class, from very fast to very slow. Among the light curves is a moderately fast CN exhibiting entry into a deep transition minimum, followed by its final decline. We have also observed in detail a very slow CN which faded by only 0.01 mag d(-1) over a 150-d period. We detect other interesting variable objects, including one of the longest period and most luminous Mira variables. The CN catalogue constitutes a uniquely well-sampled and objectively-selected data set with which to study the statistical properties of CNe in M31, such as the global nova rate, the reliability of novae as standard-candle distance indicators and the dependence of the nova population on stellar environment. The findings of this statistical study will be reported in a follow-up paper.
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A fully automated procedure to extract and to image local fibre orientation in biological tissues from scanning X-ray diffraction is presented. The preferred chitin fibre orientation in the flow sensing system of crickets is determined with high spatial resolution by applying synchrotron radiation based X-ray microbeam diffraction in conjunction with advanced sample sectioning using a UV micro-laser. The data analysis is based on an automated detection of azimuthal diffraction maxima after 2D convolution filtering (smoothing) of the 2D diffraction patterns. Under the assumption of crystallographic fibre symmetry around the morphological fibre axis, the evaluation method allows mapping the three-dimensional orientation of the fibre axes in space. The resulting two-dimensional maps of the local fibre orientations - together with the complex shape of the flow sensing system - may be useful for a better understanding of the mechanical optimization of such tissues.
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Despite the importance of dust aerosol in the Earth system, state-of-the-art models show a large variety for North African dust emission. This study presents a systematic evaluation of dust emitting-winds in 30 years of the historical model simulation with the UK Met Office Earth-system model HadGEM2-ES for the Coupled Model Intercomparison Project Phase 5. Isolating the effect of winds on dust emission and using an automated detection for nocturnal low-level jets (NLLJs) allow an in-depth evaluation of the model performance for dust emission from a meteorological perspective. The findings highlight that NLLJs are a key driver for dust emission in HadGEM2-ES in terms of occurrence frequency and strength. The annually and spatially averaged occurrence frequency of NLLJs is similar in HadGEM2-ES and ERA-Interim from the European Centre for Medium-Range Weather Forecasts. Compared to ERA-Interim, a stronger pressure ridge over northern Africa in winter and the southward displaced heat low in summer result in differences in location and strength of NLLJs. Particularly the larger geostrophic winds associated with the stronger ridge have a strengthening effect on NLLJs over parts of West Africa in winter. Stronger NLLJs in summer may rather result from an artificially increased mixing coefficient under stable stratification that is weaker in HadGEM2-ES. NLLJs in the Bodélé Depression are affected by stronger synoptic-scale pressure gradients in HadGEM2-ES. Wintertime geostrophic winds can even be so strong that the associated vertical wind shear prevents the formation of NLLJs. These results call for further model improvements in the synoptic-scale dynamics and the physical parametrization of the nocturnal stable boundary layer to better represent dust-emitting processes in the atmospheric model. The new approach could be used for identifying systematic behavior in other models with respect to meteorological processes for dust emission. This would help to improve dust emission simulations and contribute to decreasing the currently large uncertainty in climate change projections with respect to dust aerosol.
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Vegetation growing on railway trackbeds and embankments present potential problems. The presence of vegetation threatens the safety of personnel inspecting the railway infrastructure. In addition vegetation growth clogs the ballast and results in inadequate track drainage which in turn could lead to the collapse of the railway embankment. Assessing vegetation within the realm of railway maintenance is mainly carried out manually by making visual inspections along the track. This is done either on-site or by watching videos recorded by maintenance vehicles mainly operated by the national railway administrative body. A need for the automated detection and characterisation of vegetation on railways (a subset of vegetation control/management) has been identified in collaboration with local railway maintenance subcontractors and Trafikverket, the Swedish Transport Administration (STA). The latter is responsible for long-term planning of the transport system for all types of traffic, as well as for the building, operation and maintenance of public roads and railways. The purpose of this research project was to investigate how vegetation can be measured and quantified by human raters and how machine vision can automate the same process. Data were acquired at railway trackbeds and embankments during field measurement experiments. All field data (such as images) in this thesis work was acquired on operational, lightly trafficked railway tracks, mostly trafficked by goods trains. Data were also generated by letting (human) raters conduct visual estimates of plant cover and/or count the number of plants, either on-site or in-house by making visual estimates of the images acquired from the field experiments. Later, the degree of reliability of(human) raters’ visual estimates were investigated and compared against machine vision algorithms. The overall results of the investigations involving human raters showed inconsistency in their estimates, and are therefore unreliable. As a result of the exploration of machine vision, computational methods and algorithms enabling automatic detection and characterisation of vegetation along railways were developed. The results achieved in the current work have shown that the use of image data for detecting vegetation is indeed possible and that such results could form the base for decisions regarding vegetation control. The performance of the machine vision algorithm which quantifies the vegetation cover was able to process 98% of the im-age data. Investigations of classifying plants from images were conducted in in order to recognise the specie. The classification rate accuracy was 95%.Objective measurements such as the ones proposed in thesis offers easy access to the measurements to all the involved parties and makes the subcontracting process easier i.e., both the subcontractors and the national railway administration are given the same reference framework concerning vegetation before signing a contract, which can then be crosschecked post maintenance.A very important issue which comes with an increasing ability to recognise species is the maintenance of biological diversity. Biological diversity along the trackbeds and embankments can be mapped, and maintained, through better and robust monitoring procedures. Continuously monitoring the state of vegetation along railways is highly recommended in order to identify a need for maintenance actions, and in addition to keep track of biodiversity. The computational methods or algorithms developed form the foundation of an automatic inspection system capable of objectively supporting manual inspections, or replacing manual inspections.
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Spreadsheets are widely used but often contain faults. Thus, in prior work we presented a data-flow testing methodology for use with spreadsheets, which studies have shown can be used cost-effectively by end-user programmers. To date, however, the methodology has been investigated across a limited set of spreadsheet language features. Commercial spreadsheet environments are multiparadigm languages, utilizing features not accommodated by our prior approaches. In addition, most spreadsheets contain large numbers of replicated formulas that severely limit the efficiency of data-flow testing approaches. We show how to handle these two issues with a new data-flow adequacy criterion and automated detection of areas of replicated formulas, and report results of a controlled experiment investigating the feasibility of our approach.
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Objective: To characterize optic nerve head (ONH) anatomy related to the clinical optic disc margin with spectral domain-optical coherence tomography (SD-OCT). Design: Cross-sectional study. Participants: Patients with open-angle glaucoma with focal, diffuse, and sclerotic optic disc damage, and age-matched normal controls. Methods: High-resolution radial SD-OCT B-scans centered on the ONH were analyzed at each clock hour. For each scan, the border tissue of Elschnig was classified for obliqueness (internally oblique, externally oblique, or nonoblique) and the presence of Bruch's membrane overhanging the border tissue. Optic disc stereophotographs were co-localized to SD-OCT data with customized software. The frequency with which the disc margin identified in stereophotographs coincided with (1) Bruch's membrane opening (BMO), defined as the innermost edge of Bruch's membrane; (2) Bruch's membrane/border tissue, defined as any aspect of either outside BMO or border tissue; or (3) border tissue, defined as any aspect of border tissue alone, in the B-scans was computed at each clock hour. Main Outcome Measures: The SD-OCT structures coinciding with the disc margin in stereophotographs. Results: There were 30 patients (10 with each type of disc damage) and 10 controls, with a median (range) age of 68.1 (42-86) years and 63.5 (42-77) years, respectively. Although 28 patients (93%) had 2 or more border tissue configurations, the most predominant one was internally oblique, primarily superiorly and nasally, frequently with Bruch's membrane overhang. Externally oblique border tissue was less frequent, observed mostly inferiorly and temporally. In controls, there was predominantly internally oblique configuration around the disc. Although the configurations were not statistically different between patients and controls, they were among the 3 glaucoma groups. At most locations, the SD-OCT structure most frequently identified as the disc margin was some aspect of Bruch's membrane and border tissue external to BMO. Bruch's membrane overhang was regionally present in the majority of patients with glaucoma and controls; however, in most cases it was not visible as the disc margin. Conclusions: The clinically perceived disc margin is most likely not the innermost edge of Bruch's membrane detected by SD-OCT. These findings have important implications for the automated detection of the disc margin and estimates of the neuroretinal rim. Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references. Ophthalmology 2012;119:738-747 (C) 2012 by the American Academy of Ophthalmology.
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The Radarsat-1 Antarctic Mapping Project (RAMP) compiled a mosaic of Antarctica and the adjacent ocean zone from more than 3000 high-resolution Synthetic Aperture Radar (SAR) images acquired in September and October 1997. The mosaic with a pixel size of 100 m was used to determine iceberg size distributions around Antarctica, combining an automated detection with a visual control of all icebergs larger than 5 km**2 and correction of recognized false detections. For icebergs below 5 km**2 in size, the numbers of false detections and accuracies of size retrievals were analyzed for three test sites. Nearly 7000 icebergs with horizontal areas between 0.3 and 4717.7 km**2 were identified in a near-coastal zone of varying width between 20 and 300 km. The spatial distributions of icebergs around Antarctica were calculated for zonal segments of 20° angular width and related to the types of the calving fronts in the respective section. Results reveal that regional variations of the size distributions cannot be neglected. The highest ice mass accumulations were found at positions of giant icebergs (> 18.5 km) but also in front of ice shelves from which larger numbers of smaller icebergs calve almost continuously. Although the coastal oceanic zone covered by RAMP is too narrow compared to the spatial coverage needed for oceanographic research, this study nevertheless demonstrates the usefulness of SAR images for iceberg research and the need for repeated data acquisitions extending ocean-wards over distances of 500 km and more from the coast to monitor iceberg melt and disintegration and the related freshwater input into the ocean.
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O Monitoramento Acústico Passivo (PAM) submarino refere-se ao uso de sistemas de escuta e gravação subaquática, com o intuito de detectar, monitorar e identificar fontes sonoras através das ondas de pressão que elas produzem. Se diz que é passivo já que tais sistemas unicamente ouvem, sem perturbam o meio ambiente acústico existente, diferentemente de ativos, como os sonares. O PAM submarino tem diversas áreas de aplicação, como em sistemas de vigilância militar, seguridade portuária, monitoramento ambiental, desenvolvimento de índices de densidade populacional de espécies, identificação de espécies, etc. Tecnologia nacional nesta área é praticamente inexistente apesar da sua importância. Neste contexto, o presente trabalho visa contribuir com o desenvolvimento de tecnologia nacional no tema através da concepção, construção e operação de equipamento autônomo de PAM e de métodos de processamento de sinais para detecção automatizada de eventos acústicos submarinos. Foi desenvolvido um equipamento, nomeado OceanPod, que possui características como baixo custo de fabrica¸c~ao, flexibilidade e facilidade de configuração e uso, voltado para a pesquisa científica, industrial e para controle ambiental. Vários protótipos desse equipamento foram construídos e utilizados em missões no mar. Essas jornadas de monitoramento permitiram iniciar a criação de um banco de dados acústico, o qual permitiu fornecer a matéria prima para o teste de detectores de eventos acústicos automatizados e em tempo real. Adicionalmente também é proposto um novo método de detecção-identificação de eventos acústicos, baseado em análise estatística da representação tempo-frequência dos sinais acústicos. Este novo método foi testado na detecção de cetáceos, presentes no banco de dados gerado pelas missões de monitoramento.
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This Thesis addresses the problem of automated false-positive free detection of epileptic events by the fusion of information extracted from simultaneously recorded electro-encephalographic (EEG) and the electrocardiographic (ECG) time-series. The approach relies on a biomedical case for the coupling of the Brain and Heart systems through the central autonomic network during temporal lobe epileptic events: neurovegetative manifestations associated with temporal lobe epileptic events consist of alterations to the cardiac rhythm. From a neurophysiological perspective, epileptic episodes are characterised by a loss of complexity of the state of the brain. The description of arrhythmias, from a probabilistic perspective, observed during temporal lobe epileptic events and the description of the complexity of the state of the brain, from an information theory perspective, are integrated in a fusion-of-information framework towards temporal lobe epileptic seizure detection. The main contributions of the Thesis include the introduction of a biomedical case for the coupling of the Brain and Heart systems during temporal lobe epileptic seizures, partially reported in the clinical literature; the investigation of measures for the characterisation of ictal events from the EEG time series towards their integration in a fusion-of-knowledge framework; the probabilistic description of arrhythmias observed during temporal lobe epileptic events towards their integration in a fusion-of-knowledge framework; and the investigation of the different levels of the fusion-of-information architecture at which to perform the combination of information extracted from the EEG and ECG time-series. The performance of the method designed in the Thesis for the false-positive free automated detection of epileptic events achieved a false-positives rate of zero on the dataset of long-term recordings used in the Thesis.
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Objectives: To determine the best photographic surrogate markers for detecting sight-threatening macular oedema (MO) in people with diabetes attending UK national screening programmes. Design: A multicentre, prospective, observational cohort study of 3170 patients with photographic signs of diabetic retinopathy visible within the macular region [exudates within two disc diameters, microaneurysms/dot haemorrhages (M/DHs) and blot haemorrhages (BHs)] who were recruited from seven study centres. Setting: All patients were recruited and imaged at one of seven study centres in Aberdeen, Birmingham, Dundee, Dunfermline, Edinburgh, Liverpool and Oxford. Participants: Subjects with features of diabetic retinopathy visible within the macular region attending one of seven diabetic retinal screening programmes. Interventions: Alternative referral criteria for suspected MO based on photographic surrogate markers; an optical coherence tomographic examination in addition to the standard digital retinal photograph. Main outcome measures: (1) To determine the best method to detect sight-threatening MO in people with diabetes using photographic surrogate markers. (2) Sensitivity and specificity estimates to assess the costs and consequences of using alternative strategies. (3) Modelled long-term costs and quality-adjusted life-years (QALYs). Results: Prevalence of MO was strongly related to the presence of lesions and was roughly five times higher in subjects with exudates or BHs or more than two M/DHs within one disc diameter. Having worse visual acuity was associated with about a fivefold higher prevalence of MO. Current manual screening grading schemes that ignore visual acuity or the presence of M/DHs could be improved by taking these into account. Health service costs increase substantially with more sensitive/less specific strategies. A fully automated strategy, using the automated detection of patterns of photographic surrogate markers, is superior to all current manual grading schemes for detecting MO in people with diabetes. The addition of optical coherence tomography (OCT) to each strategy, prior to referral, results in a reduction in costs to the health service with no decrement in the number of MO cases detected. Conclusions: Compared with all current manual grading schemes, for the same sensitivity, a fully automated strategy, using the automated detection of patterns of photographic surrogate markers, achieves a higher specificity for detecting MO in people with diabetes, especially if visual acuity is included in the automated strategy. Overall, costs to the health service are likely to increase if more sensitive referral strategies are adopted over more specific screening strategies for MO, for only very small gains in QALYs. The addition of OCT to each screening strategy, prior to referral, results in a reduction in costs to the health service with no decrement in the number of MO cases detected. © Queen's Printer and Controller of HMSO 2013.
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Abstract Purpose – To study the possibility of using a NIR hardware solution to photograph individuals in a private vehicle as well as an analysis of its images. Method – A study of existing theories around the NIR-method’s performance in selected conditions and individual tests were performed to examine if the literature statements were valid for this study. Two empirical tests have been carried out, the first was carried out at Kapsch test track and the other outside the test track in a single stationary test. An interview which formed the basis for the assessment on the quality of empirical data with a focus on computer-based detection of the number of individuals in the vehicle. Findings – The results have demonstrated the potential of the NIR method’s performance in a fully automated detection system for the number of individuals inside the vehicle. Empirical data indicates that the method can depict individuals inside vehicles of sufficiently high quality, but it is greatly affected by reflections, weather and light conditions. Implications – Result supports the assumption that the NIR method using an external light source can be used to image the interior through a varying number of weather and lightning conditions. The study originated until the results suggested that a NIR-based hardware setup can create images with high enough quality for the human eye to be able to detect the number of individuals inside the vehicle.If the overall performance into account, it suggests that the main problem with the use of the hardware set is to maintain the quality of the whole sample and that the crucial variables for the method’s performance is the influence of light and reflection conditions. Limitations – The major limitations have been that we limited ourselves to a subjective analysis of the selection and assessment on the image features for computer-based detection of the number of individuals in the vehicle. We were limited to two tests, one in tough conditions where only the driver was in the vehicle and the second stationary test, where the focus was on the number of people in vehicles and light sources impact on the result.
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El presente trabajo tuvo como objetivo evaluar la existencia de la relación entre la atrofia cortical difusa objetivada por neuroimagenes cerebrales y desempeños cognitivos determinados mediante la aplicación de pruebas neuropsicológicas que evalúan memoria de trabajo, razonamiento simbólico verbal y memoria anterógrada declarativa. Participaron 114 sujetos reclutados en el Hospital Universitario Mayor Méderi de la ciudad de Bogotá mediante muestreo de conveniencia. Los resultados arrojaron diferencias significativas entre los dos grupos (pacientes con diagnóstico de atrofia cortical difusa y pacientes con neuroimagenes interpretadas como dentro de los límites normales) en todas las pruebas neuropsicológicas aplicadas. Respecto a las variables demográficas se pudo observar que el grado de escolaridad contribuye como factor neuroprotector de un posible deterioro cognitivo. Tales hallazgos son importantes para determinar protocoles tempranos de detección de posible instalación de enfermedades neurodegenerativas primarias.
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Road features extraction from remote sensed imagery has been a long-term topic of great interest within the photogrammetry and remote sensing communities for over three decades. The majority of the early work only focused on linear feature detection approaches, with restrictive assumption on image resolution and road appearance. The widely available of high resolution digital aerial images makes it possible to extract sub-road features, e.g. road pavement markings. In this paper, we will focus on the automatic extraction of road lane markings, which are required by various lane-based vehicle applications, such as, autonomous vehicle navigation, and lane departure warning. The proposed approach consists of three phases: i) road centerline extraction from low resolution image, ii) road surface detection in the original image, and iii) pavement marking extraction on the generated road surface. The proposed method was tested on the aerial imagery dataset of the Bruce Highway, Queensland, and the results demonstrate the efficiency of our approach.
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This paper presents two algorithms to automate the detection of marine species in aerial imagery. An algorithm from an initial pilot study is presented in which morphology operations and colour analysis formed the basis of its working principle. A second approach is presented in which saturation channel and histogram-based shape profiling were used. We report on performance for both algorithms using datasets collected from an unmanned aerial system at an altitude of 1000 ft. Early results have demonstrated recall values of 48.57% and 51.4%, and precision values of 4.01% and 4.97%.