999 resultados para Medical physics.
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The cyclotron laboratory for radioisotope production and multi-disciplinary research at the Bern University Hospital (Inselspital) is based on an 18-MeV proton accelerator, equipped with a specifically conceived 6-m long external beam line, ending in a separate bunker. This facility allows performing daily positron emission tomography (PET) radioisotope production and research activities running in parallel. Some of the latest developments on accelerator and detector physics are reported. They encompass novel detectors for beam monitoring and studies of low current beams.
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Mode of access: Internet.
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Not complete until the 6th ed., London, 1864-65.
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There are two men in the image
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Mode of access: Internet.
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Medical imaging is a powerful diagnostic tool. Consequently, the number of medical images taken has increased vastly over the past few decades. The most common medical imaging techniques use X-radiation as the primary investigative tool. The main limitation of using X-radiation is associated with the risk of developing cancers. Alongside this, technology has advanced and more centres now use CT scanners; these can incur significant radiation burdens compared with traditional X-ray imaging systems. The net effect is that the population radiation burden is rising steadily. Risk arising from X-radiation for diagnostic medical purposes needs minimising and one way to achieve this is through reducing radiation dose whilst optimising image quality. All ages are affected by risk from X-radiation however the increasing population age highlights the elderly as a new group that may require consideration. Of greatest concern are paediatric patients: firstly they are more sensitive to radiation; secondly their younger age means that the potential detriment to this group is greater. Containment of radiation exposure falls to a number of professionals within medical fields, from those who request imaging to those who produce the image. These staff are supported in their radiation protection role by engineers, physicists and technicians. It is important to realise that radiation protection is currently a major European focus of interest and minimum competence levels in radiation protection for radiographers have been defined through the integrated activities of the EU consortium called MEDRAPET. The outcomes of this project have been used by the European Federation of Radiographer Societies to describe the European Qualifications Framework levels for radiographers in radiation protection. Though variations exist between European countries radiographers and nuclear medicine technologists are normally the professional groups who are responsible for exposing screening populations and patients to X-radiation. As part of their training they learn fundamental principles of radiation protection and theoretical and practical approaches to dose minimisation. However dose minimisation is complex – it is not simply about reducing X-radiation without taking into account major contextual factors. These factors relate to the real world of clinical imaging and include the need to measure clinical image quality and lesion visibility when applying X-radiation dose reduction strategies. This requires the use of validated psychological and physics techniques to measure clinical image quality and lesion perceptibility.
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Taking the Royal College of Barcelona (1760 -1843) as a case study this paper shows the development of modern surgery in Spain initiated by Bourbon Monarchy founding new kinds of institutions through their academic activities of spreading scientific knowledge. Antoni Gimbernat was the most famousinternationally recognised Spanish surgeon. He was trained as a surgeon at the Royal College of Surgery in Cadiz and was later appointed as professor of theAnatomy in the College of Barcelona. He then became Royal Surgeon of King Carlos IV and with that esteemed position in Madrid he worked resiliently to improve the quality of the Royal colleges in Spain. Learning human bodystructure by performing hands-on dissections in the anatomical theatre has become a fundamental element of modern medical education. Gimbernat favoured the study of natural sciences, the new chemistry of Lavoisier and experimental physics in the academic programs of surgery. According to the study of a very relevant set of documents preserved in the library, the so-called “juntas literarias”, among the main subjects debated in the clinical sessions was the concept of human beings and diseases in relation to the development of the new experimental sciences. These documents showed that chemistry andexperimental physics were considered crucial tools to understand the unexplained processes that occurred in the diseased and healthy human bodyand in a medico-surgical context. It is important to stress that through these manuscripts we can examine the role and the reception of the new sciences applied to healing arts.
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In this article we present a hybrid approach for automatic summarization of Spanish medical texts. There are a lot of systems for automatic summarization using statistics or linguistics, but only a few of them combining both techniques. Our idea is that to reach a good summary we need to use linguistic aspects of texts, but as well we should benefit of the advantages of statistical techniques. We have integrated the Cortex (Vector Space Model) and Enertex (statistical physics) systems coupled with the Yate term extractor, and the Disicosum system (linguistics). We have compared these systems and afterwards we have integrated them in a hybrid approach. Finally, we have applied this hybrid system over a corpora of medical articles and we have evaluated their performances obtaining good results.
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El processament d'imatges mèdiques és una important àrea de recerca. El desenvolupament de noves tècniques que assisteixin i millorin la interpretació visual de les imatges de manera ràpida i precisa és fonamental en entorns clínics reals. La majoria de contribucions d'aquesta tesi són basades en Teoria de la Informació. Aquesta teoria tracta de la transmissió, l'emmagatzemament i el processament d'informació i és usada en camps tals com física, informàtica, matemàtica, estadística, biologia, gràfics per computador, etc. En aquesta tesi, es presenten nombroses eines basades en la Teoria de la Informació que milloren els mètodes existents en l'àrea del processament d'imatges, en particular en els camps del registre i la segmentació d'imatges. Finalment es presenten dues aplicacions especialitzades per l'assessorament mèdic que han estat desenvolupades en el marc d'aquesta tesi.
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Methods have recently been developed that make use of electromagnetic radiation at terahertz (THz) frequencies, the region of the spectrum between millimetre wavelengths and the infrared, for imaging purposes. Radiation at these wavelengths is non-ionizing and subject to far less Rayleigh scatter than visible or infrared wavelengths, making it suitable for medical applications. This paper introduces THz pulsed imaging and discusses its potential for in vivo medical applications in comparison with existing modalities.
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Biological models of an apoptotic process are studied using models describing a system of differential equations derived from reaction kinetics information. The mathematical model is re-formulated in a state-space robust control theory framework where parametric and dynamic uncertainty can be modelled to account for variations naturally occurring in biological processes. We propose to handle the nonlinearities using neural networks.
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Silver/alanine nanocomposites with varying mass percentage of silver have been produced. The size of the silver nanoparticles seems to drive the formation of the nanocomposite, yielding a homogeneous dispersion of the silver nanoparticles in the alanine matrix or flocs of silver nanoparticles segregated from the alanine crystals. The alanine crystalline orientation is modified according to the particle size of the silver nanoparticles. Concerning a mass percentage of silver below 0.1%, the nanocomposites are homogeneous, and there is no particle aggregation. As the mass percentage of silver is increased, the system becomes unstable, and there is particle flocculation with subsequent segregation of the alanine crystals. The nanocomposites have been analyzed by transmission electron microscopy (TEM), UV-Vis absorption spectroscopy, X-ray diffraction (XRD), and Fourier transform infrared (FTIR) spectroscopy and they have been tested as radiation detectors by means of electron spin resonance (ESR) spectroscopy in order to detect the paramagnetic centers created by the radiation. In fact, the sensitivity of the radiation detectors is optimized in the case of systems containing small particles (30 nm) that are well dispersed in the alanine matrix. As the agglomeration increases, particle growth (up to 1.5 mu m) and segregation diminish the sensitivity. In conclusion, nanostructured materials can be used for optimization of alanine sensitivity, by taking into account the influence of the particles size of the silver nanoparticles on the detection properties of the alanine radiation detectors, thus contributing to the construction of small-sized detectors.
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The subject of this thesis is in the area of Applied Mathematics known as Inverse Problems. Inverse problems are those where a set of measured data is analysed in order to get as much information as possible on a model which is assumed to represent a system in the real world. We study two inverse problems in the fields of classical and quantum physics: QCD condensates from tau-decay data and the inverse conductivity problem. Despite a concentrated effort by physicists extending over many years, an understanding of QCD from first principles continues to be elusive. Fortunately, data continues to appear which provide a rather direct probe of the inner workings of the strong interactions. We use a functional method which allows us to extract within rather general assumptions phenomenological parameters of QCD (the condensates) from a comparison of the time-like experimental data with asymptotic space-like results from theory. The price to be paid for the generality of assumptions is relatively large errors in the values of the extracted parameters. Although we do not claim that our method is superior to other approaches, we hope that our results lend additional confidence to the numerical results obtained with the help of methods based on QCD sum rules. EIT is a technology developed to image the electrical conductivity distribution of a conductive medium. The technique works by performing simultaneous measurements of direct or alternating electric currents and voltages on the boundary of an object. These are the data used by an image reconstruction algorithm to determine the electrical conductivity distribution within the object. In this thesis, two approaches of EIT image reconstruction are proposed. The first is based on reformulating the inverse problem in terms of integral equations. This method uses only a single set of measurements for the reconstruction. The second approach is an algorithm based on linearisation which uses more then one set of measurements. A promising result is that one can qualitatively reconstruct the conductivity inside the cross-section of a human chest. Even though the human volunteer is neither two-dimensional nor circular, such reconstructions can be useful in medical applications: monitoring for lung problems such as accumulating fluid or a collapsed lung and noninvasive monitoring of heart function and blood flow.
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This thesis work aims to find a procedure for isolating specific features of the current signal from a plasma focus for medical applications. The structure of the current signal inside a plasma focus is exclusive of this class of machines and a specific analysis procedure has to be developed. The hope is to find one or more features that shows a correlation with the dose erogated. The study of the correlation between the current discharge signal and the dose delivered by a plasma focus could be of some importance not only for the practical application of dose prediction but also for expanding the knowledge anbout the plasma focus physics. Vatious classes of time-frequency analysis tecniques are implemented in order to solve the problem.
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MRI-based medical image analysis for brain tumor studies is gaining attention in recent times due to an increased need for efficient and objective evaluation of large amounts of data. While the pioneering approaches applying automated methods for the analysis of brain tumor images date back almost two decades, the current methods are becoming more mature and coming closer to routine clinical application. This review aims to provide a comprehensive overview by giving a brief introduction to brain tumors and imaging of brain tumors first. Then, we review the state of the art in segmentation, registration and modeling related to tumor-bearing brain images with a focus on gliomas. The objective in the segmentation is outlining the tumor including its sub-compartments and surrounding tissues, while the main challenge in registration and modeling is the handling of morphological changes caused by the tumor. The qualities of different approaches are discussed with a focus on methods that can be applied on standard clinical imaging protocols. Finally, a critical assessment of the current state is performed and future developments and trends are addressed, giving special attention to recent developments in radiological tumor assessment guidelines.