- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
Pattern recognition of messily grown nanowire morphologies applying multi-layer connected self-organized feature maps
摘要： Multi-layer connected self-organizing feature maps (SOFMs) and the associated learning procedure were proposed to achieve efficient recognition and clustering of messily grown nanowire morphologies. The network is made up by several paratactic 2-D SOFMs with inter-layer connections. By means of Monte Carlo simulations, virtual morphologies were generated to be the training samples. With the unsupervised inner-layer and inter-layer learning, the neural network can cluster different morphologies of messily grown nanowires and build connections between the morphological microstructure and geometrical features of nanowires within. Then, the as-proposed networks were applied on recognitions and quantitative estimations of the experimental morphologies. Results show that the as-trained SOFMs are able to cluster the morphologies and recognize the average length and quantity of the messily grown nanowires within. The inter-layer connections between winning neurons on each competitive layer have significant influence on the relations between the microstructure of the morphology and physical parameters of the nanowires within.
关键词： Messily grown nanowire morphologies,Artificial neural networks,Monte Carlo simulation,Pattern recognition,Self-organizing feature maps
更新于2025-09-09 09:28:46
-
[IEEE 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) - Atlanta, GA (2017.10.21-2017.10.28)] 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) - Deep residual learning in CT physics: scatter correction for spectral CT
摘要： Recently, spectral CT has been drawing a lot of attention in a variety of clinical applications primarily due to its capability of providing quantitative information about material properties. The quantitative integrity of the reconstructed data depends on the accuracy of the data corrections applied to the measurements. Scatter correction is a particularly sensitive correction in spectral CT as it depends on system effects as well as the object being imaged and any residual scatter is amplified during the non-linear material decomposition. An accurate way of removing scatter is subtracting the scatter estimated by Monte Carlo simulation. However, to get sufficiently good scatter estimates, extremely large numbers of photons are required, which may lead to unexpectedly high computational costs. Other approaches model scatter as a convolution operation using kernels derived using empirical methods. These techniques have been found to be insufficient in spectral CT due to their inability to sufficiently capture object dependence. In this work, we develop a deep residual learning framework to address both issues of computation simplicity and object dependency. A deep convolution neural network is trained to determine the scatter distribution from the projection content in training sets. In test cases of a digital anthropomorphic phantom and real water phantom, we demonstrate that with much lower computing costs, the proposed network provides sufficiently accurate scatter estimation.
关键词： convolutional neural network,deep residual learning,Monte Carlo simulation,scatter correction,spectral CT
更新于2025-09-09 09:28:46
-
[IEEE 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) - Atlanta, GA (2017.10.21-2017.10.28)] 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) - Deep Learning Models for PET Scatter Estimations
摘要： Projection data acquired from a positron emission tomography (PET) scanner consist of true, scattered and random events. Scattered events can cause severe artifacts and quantitation errors in reconstructed PET images unless corrected for properly. A scatter correction algorithm is required to predict scattered events from the measurement. Scatter correction requires estimation of both single scatter and multiple scatter profiles. Usually, single scatter profiles are calculated by model-based simulation and multiple scatter profiles are estimated by a kernel-based convolution method. However, design of the convolution kernels for multiple scatter estimation is sophisticated and requires fine parameter tuning. In this work, we adopt deep learning techniques for scatter estimation. We propose two convolutional neural networks. The first network estimates multiple scatter profiles from single scatter profiles, replacing the kernel-based convolution method. The second network is designed to predict the total scatter profiles (including single and multiple scatters) directly from the input of emission and attenuation sinograms. Initial results from both networks show a promise with the potential for more accurate and faster scatter correction for PET.
关键词： Monte Carlo Simulation,Deep Learning,Scatter Estimation,Convolutional Neural Networks,PET
更新于2025-09-09 09:28:46
-
[IEEE 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) - Honolulu, HI, USA (2018.7.18-2018.7.21)] 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) - Study of the photoneutron generation caused by a LinAc Beryllium window with a 6 MeV treatment beam
摘要： In most conventional radiation therapy treatments, special attention is payed for neutron contamination when working with energy beams above 8 MeV and generally it is only considered for shielding requirements, not for dose study in patients or employees. The present work is focused on studying the unwanted generated photoneutrons in a Medical Linear Accelerator (LinAc) Varian TrueBeam using a 6 MeV radiation treatment beam. To that, Monte Carlo (MC) simulation code MCNP6.1.1 was used. This version of the code allows the use of unstructured mesh geometries as a novelty, offering more reliable results and higher speed computation. The particularity of the studied LinAc is the presence of a beryllium filter at the treatment head. Since Beryllium causes photonuclear reactions (γ, n) at energies much lower than other LinAc composing materials, this work aims to analyze if this type of units, when using low energy treatment beams (6 MeV), produce neutron pollution and to ensure that this unwanted radiation can be considered negligible.
关键词： Monte Carlo simulation,Medical Linear Accelerator,radiation therapy,photoneutrons,Beryllium filter
更新于2025-09-09 09:28:46
-
A model for charge transport in semicrystalline polymer thin films
摘要： A model for simulating the charge transport properties of semicrystalline polymer (SCrP) using Monte Carlo simulation is reinvented. The model is validated by reproducing the experimentally observed ?eld and temperature dependence of mobility in Poly(3-hexylthiophene-2,5-diyl) (P3HT) thin ?lms. This study also provides a new physical insight to the origin of much debated negative ?eld dependence of mobility (NFDM) observed at low electric ?eld strengths in P3HT thin ?lms. The observed NFDM, which is not explainable with the mechanisms proposed earlier, is attributed to the weak dependence of transit time on the applied electric ?eld strengths. In the semicrystalline ?lms, the charge transport takes place mostly through the crystalline regions, in which the charge transport is weakly dependent on the strength of the applied electric ?eld. In addition, a possible explanation for the origin of Arrhenius temperature dependence of mobility (lnμ / 1/T) commonly observed in SCrP thin ?lms is also proposed.
关键词： Monte Carlo simulation,charge transport,poly(3-hexylthiophene-2,5-diyl),semicrystalline polymers,negative ?eld dependence of mobility
更新于2025-09-09 09:28:46
-
[IEEE 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) - Atlanta, GA (2017.10.21-2017.10.28)] 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) - Monte Carlo Simulation and Collimator optimization for Tomographic Gamma Scanning
摘要： We present the design and optimization of a Tomographic Gamma Scanning (TGS) collimator using Monte Carlo methods. In these simulations, an accurate TGS model was built and the radius, depth and shape of the TGS collimator were optimized. The simulation results reveal that the optimal collimator aperture radius and depth for this system are 3.1 cm and 18.6 cm, respectively, achieved when the full width at half-maximum (FWHM) is 26.7 cm. Also, a rotated 30° hexagon is found to be the optimal shape. Our TGS design shows significantly improved performance.
关键词： collimator optimization,Monte Carlo simulation,sensitivity,spatial resolution,Tomographic Gamma Scanning
更新于2025-09-04 15:30:14
-
[Institution of Engineering and Technology 12th European Conference on Antennas and Propagation (EuCAP 2018) - London, UK (9-13 April 2018)] 12th European Conference on Antennas and Propagation (EuCAP 2018) - Efficient Uncertainty Evaluation of Vector Network Analyser Measurements Using Two-Tier Bayesian Analysis and Monte Carlo Method
摘要： Antennas are a key element in any communication system and vector network analyser (VNA) is popular tool for charactering antenna impedance bandwidth. In this paper, an efficient uncertainty evaluation method is proposed for VNA measurement based on its uncertainty propagation mechanism using Bayesian analysis and Monte Carlo method. The proposed method is generic and can be applied to VNA with arbitrary number of ports. In order to obtain the complete information of measurement uncertainty distribution, a two-tier Bayesian analytic process is carried out. The proposed method contains three steps. In the first step, the posterior distribution of each uncertainty source of VNA calibrations is deduced by the use of prior and current sample information through the first-tier Bayesian analysis. In the second step, the obtained posterior distributions of uncertainty sources are taken into the Monte Carlo simulation of one-port VNA measurement uncertainties. In the last step, the results obtained in the second step are used as the prior distribution of the secondary Bayesian evaluation, then the evaluation results of the measurement uncertainty can be obtained with the means, variances and skewness of the probabilistic distribution. The numerical analysis using an antenna measurement results demonstrate the high-efficiency and reliability of this proposed method.
关键词： Bayesian analysis,VNA,uncertainty,Monte Carlo simulation,measurement
更新于2025-09-04 15:30:14
-
AN ALGORITHM TO DETERMINE THE NANODOSIMETRIC IMPACT OF GOLD NANOPARTICLES ON CELL MODELS
摘要： High-Z nanomaterials, e.g. gold nanoparticles (GNPs), are being investigated worldwide for potential application in radiation imaging and therapy. Photon irradiation of cells containing GNP was shown to produce enhanced DNA damage which is believed to be related to the increased secondary electron (SE) yield and ionization density. In this work, an algorithm was developed for simulating the physical radiation damage inside the nucleus of a spherical cell model for the case of uniformly distributed GNPs within the cytoplasm. Previously calculated energy spectra of SE emerging from a single NP irradiated with different photon sources are used as input to obtain the SE energy spectrum at the surface of the cell nucleus. In a second step, the SE transport inside the cell nucleus is simulated with a track structure Monte Carlo code to obtain the spatial distribution of ionizations. The preliminary results presented here show that the developed algorithm allows for a fast calculation of the SE spectra at the cell nucleus surface, thus enabling a more realistic assessment of the ionization density inside the cell nucleus than that obtained by the simulation of a single GNP. Furthermore, the algorithm can be easily adapted to investigate both the effect of GNP clustering and the impact of GNP–GNP interactions on SE spectra.
关键词： radiation therapy,secondary electrons,gold nanoparticles,Monte Carlo simulation,ionization density
更新于2025-09-04 15:30:14
-
Experimental Measurement and Monte Carlo Simulation the Correction Factor for the Medium-Energy X-ray Free-air Ionization Chamber
摘要： A key comparison has been made between the air-kerma standards of the National Institute of Metrology (NIM), China, and other Asia Pacific Metrology Programme (APMP) members in the medium-energy X-ray. This paper reviews the primary standard Free-air ionization chamber correction factor experimental method and Monte Carlo simulation method in the NIM. The experimental method and the Monte Carlo simulation method are adopted to obtain the correction factor for the medium-energy X-ray primary standard free-air ionization chamber at 100 kV, 135 kV, 180 kV, 250 kV four CCRI reference qualities. The correction factor has already been submitted to the APMP as key comparison data and the results are in good agreement with those obtained in previous studies. This study shows that the experimental method and the EGSnrc simulation method are usually used in the measurement of the correction factor. In particular, the application of the simulation methods is more common.
关键词： Correction factor,Air-kerma,Experimental method,Free-air ionization chamber,Monte Carlo simulation
更新于2025-09-04 15:30:14
-
Analysis of Secondary Photons Emergent from Combined Material Slab as a Function of Slab Thickness
摘要： Material science is very important for developing the linear accelerator. Determination and understanding of material behavior face to X-rays is a basic study for photon beam modifiers improvements. In this study, the 6 MV photon beams produced by Varian Clinac 2100 was modelled by Monte Carlo simulation using BEAMnrc code and thereafter the flattening filter was replaced by a slab of aluminum and copper separately and by slab of both materials combined together with different thickness of 2.5, 5, 7.5, and 10 mm. The purpose of this study is to investigate the scattered photons with thickness of combined material slab as a function of off-axis distance. The scattered photons increased with thickness of copper alone slab, combined aluminum-copper slab and copper-aluminum slab, but for aluminum alone slab they decreased with slab thickness. The stacking order of these two materials affects the characterization of scattered photons emergent from material slab with thickness. The combination of materials and the manner that the stacking was done affects the scattered photons production. The material combination could improve the radiotherapy efficiency in beam modifier development using more than two materials.
关键词： Monte Carlo simulation,BEAMnrc code,scattered photons,copper slab,aluminum slab,BEAMDP code
更新于2025-09-04 15:30:14