140 resultados para phosphorescence imaging


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The Rapid Oscillations in the Solar Atmosphere (ROSA) instrument is a synchronized, six-camera high-cadence solar imaging instrument developed by Queen's University Belfast and recently commissioned at the Dunn Solar Telescope at the National Solar Observatory in Sunspot, New Mexico, USA, as a common-user instrument. Consisting of six 1k x 1k Peltier-cooled frame-transfer CCD cameras with very low noise (0.02 - 15 e/pixel/s), each ROSA camera is capable of full-chip readout speeds in excess of 30 Hz, and up to 200 Hz when the CCD is windowed. ROSA will allow for multi-wavelength studies of the solar atmosphere at a high temporal resolution. We will present the current instrument set-up and parameters, observing modes, and future plans, including a new high QE camera allowing 15 Hz for Halpha. Interested parties should see https://habu.pst.qub.ac.uk/groups/arcresearch/wiki/de502/ROSA.html

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This document describes best practice and evidence based recommendations for the use of FDG-PET/CT for the purposes of radiotherapy target volume delineation (TVD) for curative intent treatment of non-small cell lung cancer (NSCLC). These recommendations have been written by an expert advisory group, convened by the International Atomic Energy Agency (IAEA) to facilitate a Coordinated Research Project (CRP) aiming to improve the applications of PET based radiation treatment planning (RTP) in low and middle income countries. These guidelines can be applied in routine clinical practice of radiotherapy TVD, for NSCLC patients treated with concurrent chemoradiation or radiotherapy alone, where FDG is used, and where a calibrated PET camera system equipped for RTP patient positioning is available. Recommendations are provided for PET and CT image visualization and interpretation, and for tumor delineation using planning CT with and without breathing motion compensation.

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Efficient identification and follow-up of astronomical transients is hindered by the need for humans to manually select promising candidates from data streams that contain many false positives. These artefacts arise in the difference images that are produced by most major ground-based time-domain surveys with large format CCD cameras. This dependence on humans to reject bogus detections is unsustainable for next generation all-sky surveys and significant effort is now being invested to solve the problem computationally. In this paper, we explore a simple machine learning approach to real-bogus classification by constructing a training set from the image data of similar to 32 000 real astrophysical transients and bogus detections from the Pan-STARRS1 Medium Deep Survey. We derive our feature representation from the pixel intensity values of a 20 x 20 pixel stamp around the centre of the candidates. This differs from previous work in that it works directly on the pixels rather than catalogued domain knowledge for feature design or selection. Three machine learning algorithms are trained (artificial neural networks, support vector machines and random forests) and their performances are tested on a held-out subset of 25 per cent of the training data. We find the best results from the random forest classifier and demonstrate that by accepting a false positive rate of 1 per cent, the classifier initially suggests a missed detection rate of around 10 per cent. However, we also find that a combination of bright star variability, nuclear transients and uncertainty in human labelling means that our best estimate of the missed detection rate is approximately 6 per cent.

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Arguably the most ancient of the social media, wall paintings have been a persistent vehicle of cultural meaning management. The dynamics of myth markets are reflected in the sectarian murals of Northern Ireland. In this paper, we draw from consumer research literature on mythology and street art to explore the continuous revision of these wallscapes that seeks to address the enduring contradictions of civic ideology in contested political space. In particular, we focus on the use of classical, historical and pop-cultural mythologies to transform private space into public place. We examine the decommissioning of murals occurring in the wake of the Peace Accords, and speculate on the implications of the creation of a shared mythology for the future of mural painting and the state.

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A novel type of microwave probes based on the loaded aperture geometry has been proposed and experimentally evaluated for dielectrics characterisation and high-resolution near-field imaging. Experimental results demonstrate the possibility of very accurate microwave spectroscopic characterisation of thin lossy dielectric samples and biological materials containing water. High-resolution images of the subwavelength lossy dielectric strips and wet and dry leaves have been obtained with amplitude contrast around 10-20 dB and spatial resolution better than one-tenth of a wavelength in the near-field zone. A microwave imaging scenario for the early-stage skin cancer identification based on the artificial dielectric model has also been explored. This model study shows that the typical resolution of an artificial malignant tumour with a characteristic size of one-tenth of a wavelength can be discriminated with at least 6 dB amplitude and 50° phase contrast from the artificial healthy skin and with more than 3 dB contrast from a benign lesion of the same size. It has also been demonstrated that the proposed device can efficiently deliver microwave energy to very small, subwavelength, focal areas which is highly sought in the microwave hyperthermia applications.

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A new type of focal-palne array made of a nanoscale metal screen mimics the function of a lens, focuses light (and plasmons) into subwavelength hot spots, and achieves high-resolution imaging of complex sources.

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X-ray backscatter imaging can be used for a wide range of imaging applications, in particular for industrial inspection and portal security. Currently, the application of this imaging technique to the detection of landmines is limited due to the surrounding sand or soil strongly attenuating the 10s to 100s of keV X-rays required for backscatter imaging. Here, we introduce a new approach involving a 140 MeV short-pulse (< 100 fs) electron beam generated by laser wakefield acceleration to probe the sample, which produces Bremsstrahlung X-rays within the sample enabling greater depths to be imaged. A variety of detector and scintillator configurations are examined, with the best time response seen from an absorptive coated BaF2 scintillator with a bandpass filter to remove the slow scintillation emission components. An X-ray backscatter image of an array of different density and atomic number items is demonstrated. The use of a compact laser wakefield accelerator to generate the electron source, combined with the rapid development of more compact, efficient and higher repetition rate high power laser systems will make this system feasible for applications in the field.

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BACKGROUND: Detection of pre-neoplastic gastric mucosal changes and early gastric cancer (EGC) by white-light endoscopy (WLE) is often difficult. In this study we investigated whether combined autofluorescence imaging (AFI) and narrow band imaging (NBI) can improve detection of pre-neoplastic lesions and early gastric cancer in high-risk patients.

PATIENTS AND METHODS: Chinese patients who were 50-years-old or above with dyspepsia were examined by both high-resolution WLE and combined AFI followed by NBI (AFI-NBI), consecutively in a prospective randomized cross-over setting, by two experienced endoscopists. The primary outcome was diagnostic ability of the two methods for patients with pre-neoplastic lesions such as intestinal metaplasia (IM) and mucosal atrophy.

RESULTS: Sixty-five patients were recruited. One patient with large advanced gastric cancer was found and excluded from the analysis. Among the remaining 64 patients, 38 (59%) had IM; of these, 26 (68%) were correctly identified by AFI-NBI (sensitivity 68%, specificity 23%) and only 13 (34%) by WLE (sensitivity 34%, specificity 65%). AFI-NBI detected more patients with IM than did WLE (p=0.011). Thirty-one patients (48%) had mucosal atrophy. Ten patients (32%) were identified by AFI-NBI (sensitivity 32%, specificity 79%) and four patients (13%) by WLE (sensitivity 13%, specificity 88%) (p=0.100). No dysplasia or EGC was found.

CONCLUSION: AFI-NBI identified significantly more patients with IM than did WLE. Our result warrants further studies to define the role of combined AFI-NBI endoscopy for detection of precancerous conditions.

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Gold nanoparticle radiosensitization represents a novel technique in enhancement of ionising radiation dose and its effect on biological systems. Variation between theoretical predictions and experimental measurement is significant enough that the mechanism leading to an increase in cell killing and DNA damage is still not clear. We present the first experimental results that take into account both the measured biodistribution of gold nanoparticles at the cellular level and the range of the product electrons responsible for energy deposition. Combining synchrotron-generated monoenergetic X-rays, intracellular gold particle imaging and DNA damage assays, has enabled a DNA damage model to be generated that includes the production of intermediate electrons. We can therefore show for the first time good agreement between the prediction of biological outcomes from both the Local Effect Model and a DNA damage model with experimentally observed cell killing and DNA damage induction via the combination of X-rays and GNPs. However, the requirement of two distinct models as indicated by this mechanistic study, one for short-term DNA damage and another for cell survival, indicates that, at least for nanoparticle enhancement, it is not safe to equate the lethal lesions invoked in the local effect model with DNA damage events.

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Studies have been carried out to recognize individuals from a frontal view using their gait patterns. In previous work, gait sequences were captured using either single or stereo RGB camera systems or the Kinect 1.0 camera system. In this research, we used a new frontal view gait recognition method using a laser based Time of Flight (ToF) camera. In addition to the new gait data set, other contributions include enhancement of the silhouette segmentation, gait cycle estimation and gait image representations. We propose four new gait image representations namely Gait Depth Energy Image (GDE), Partial GDE (PGDE), Discrete Cosine Transform GDE (DGDE) and Partial DGDE (PDGDE). The experimental results show that all the proposed gait image representations produce better accuracy than the previous methods. In addition, we have also developed Fusion GDEs (FGDEs) which achieve better overall accuracy and outperform the previous methods.