69 resultados para 3D dose distribution
Resumo:
O número de exposições à radiação com fins médicos têm vindo a aumentar drasticamente devido ao crescimento do número de exames de Tomografia Computorizada (TC) realizados anualmente em crianças, o que faz com que aumentem também os potenciais efeitos indesejados associados à radiação ionizante. Este assunto torna-se ainda mais crítico na população pediátrica pelo que é imprescindível a otimização dos protocolos de aquisição e adoção de boas práticas no que respeita à redução da dose de exposição. A aplicação dos protocolos em neurorradiologia pediátrica carece de estratégias eficazes, as quais visam uma eficaz redução de dose mantendo a qualidade de imagem. Comparativamente aos descritores de dose (CTIvol e DLP) e parâmetros técnicos (Kvp, mAs, tempo de exposição e espessura de corte), foi objetivo deste estudo avaliar a redução da dose nos exames de neurorradiologia pediátrica através da comparação entre 2012 e 2013, ou seja, antes e depois da intervenção de otimização efetuada aos protocolos de aquisição.
Resumo:
Objetivo do estudo - Comparar a dose calculada nos órgãos de risco (OR’s) e no volume alvo de planeamento (PTV), entre a tomoterapia helicoidal (TH) e a arcoterapia de intensidade modulada (RapidArc®), em glioblastomas multiformes (GBM).
Resumo:
Objectivo do estudo - Investigar se os fatores standard de aquisição de radiografias às órbitas estão otimizados para a deteção de corpos estranhos ferromagnéticos intraoculares em pacientes que irão ser submetidos a ressonâncias magnéticas.
Resumo:
Purpose: This study aims to investigate the influence of tube potential (kVp) variation in relation to perceptual image quality and effective dose for pelvis using automatic exposure control (AEC) and non-AEC in a computed radiography (CR) system. Methods and Materials: To determine the effects of using AEC and non-AEC by applying the 10 kVp rule in two experiments using an anthropomorphic pelvis phantom. Images were acquired using 10 kVp increments (60-120 kVp) for both experiments. The first experiment, based on seven AEC combinations, produced 49 images. The mean mAs from each kVp increment were used as a baseline for the second experiment producing 35 images. A total of 84 images were produced and a panel of 5 experienced observers participated for the image scoring using the 2 AFC visual grading software. PCXMC software was used to estimate the effective dose. Results: A decrease in perceptual image quality as the kVp increases was observed both in non-AEC and AEC experiments, however no significant statistical differences (p> 0.05) were found. Image quality scores from all observers at 10 kVp increments for all mAs values using non-AEC mode demonstrates a better score up to 90 kVp. Effective dose results show a statistical significant decrease (p=0.000) on the 75th quartile from 0.3 mSv at 60 kVp to 0.1 mSv at 120 kVp when applying the 10 kVp rule in non-AEC mode. Conclusion: No significant reduction in perceptual image quality is observed when increasing kVp whilst a marked and significant effective dose reduction is observed.
Resumo:
The design of magnetic cores can be carried out by taking into account the optimization of different parameters in accordance with the application requirements. Considering the specifications of the fast field cycling nuclear magnetic resonance (FFC-NMR) technique, the magnetic flux density distribution, at the sample insertion volume, is one of the core parameters that needs to be evaluated. Recently, it has been shown that the FFC-NMR magnets can be built on the basis of solenoid coils with ferromagnetic cores. Since this type of apparatus requires magnets with high magnetic flux density uniformity, a new type of magnet using a ferromagnetic core, copper coils, and superconducting blocks was designed with improved magnetic flux density distribution. In this paper, the designing aspects of the magnet are described and discussed with emphasis on the improvement of the magnetic flux density homogeneity (Delta B/B-0) in the air gap. The magnetic flux density distribution is analyzed based on 3-D simulations and NMR experimental results.
Resumo:
A 70Co-30Ni dendritic alloy was produced on stainless steel by pulse electrodeposition in the cathodic domain, and oxidized by potential cycling. X-ray diffraction (XRD) identified the presence of two phases and scanning electron microscopy (SEM) evidenced an open 3D highly branched dendritic morphology. After potential cycling in 1 M KOH, SEM and X-ray photoelectron spectroscopy (XPS) revealed, respectively, the presence of thin nanoplates, composed of Co and Ni oxi-hydroxides and hydroxides over the original dendritic film. Cyclic voltammetry tests showd the presence of redox peaks assigned to the oxidation and reduction of Ni and Co centres in the surface film. Charge/discharge measurements revealed capacity values of 121 mAh g(1) at 1 mA cm(2). The capacity retention under 8000 cycles was above 70%, stating the good reversibility of these redox materials and its suitability to be used as charge storage electrodes. Electrochemical impedance spectroscopy (EIS) spectra, taken under different applied bias, showed that the capacitance increased when the electrode was fully oxidized and decreased when the electrode was reduced, reflecting different states-of-charge of the electrode. (C) 2015 Elsevier Ltd. All rights reserved.
Resumo:
We present results, obtained by means of an analytic study and a numerical simulation, about the resonant condition necessary to produce a Localized Surface Plasmonic Resonance (LSPR) effect at the surface of metal nanospheres embedded in an amorphous silicon matrix. The study is based on a Lorentz dispersive model for a-Si:H permittivity and a Drude model for the metals. Considering the absorption spectra of a-Si:H, the best choice for the metal nanoparticles appears to be aluminium, indium or magnesium. No difference has been observed when considering a-SiC:H. Finite-difference time-domain (FDTD) simulation of an Al nanosphere embedded into an amorphous silicon matrix shows an increased scattering radius and the presence of LSPR induced by the metal/semiconductor interaction under green light (560 nm) illumination. Further results include the effect of the nanoparticles shape (nano-ellipsoids) in controlling the wavelength suitable to produce LSPR. It has been shown that is possible to produce LSPR in the red part of the visible spectrum (the most critical for a-Si:H solar cells applications in terms of light absorption enhancement) with aluminium nano-ellipsoids. As an additional results we may conclude that the double Lorentz-Lorenz model for the optical functions of a-Si:H is numerically stable in 3D simulations and can be used safely in the FDTD algorithm. A further simulation study is directed to determine an optimal spatial distribution of Al nanoparticles, with variable shapes, capable to enhance light absorption in the red part of the visible spectrum, exploiting light trapping and plasmonic effects. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Resumo:
In this work, plasticizer agents were incorporated in a chitosan based formulation, as a strategy to improve the fragile structure of chitosan based-materials. Three different plasticizers: ethylene glycol, glycerol and sorbitol, were blended with chitosan to prepare 3D dense chitosan specimens. The properties of the obtained structures were assessed for mechanical, microstructural, physical and biocompatibility behavior. The results obtained revealed that from the different specimens prepared, the blend of chitosan with glycerol has superior mechanical properties and good biological behavior, making this chitosan based formulation a good candidate to improve robust chitosan structures for the construction of bioabsorbable orthopedic implants.
Resumo:
This paper addresses the estimation of surfaces from a set of 3D points using the unified framework described in [1]. This framework proposes the use of competitive learning for curve estimation, i.e., a set of points is defined on a deformable curve and they all compete to represent the available data. This paper extends the use of the unified framework to surface estimation. It o shown that competitive learning performes better than snakes, improving the model performance in the presence of concavities and allowing to desciminate close surfaces. The proposed model is evaluated in this paper using syntheticdata and medical images (MRI and ultrasound images).