检索结果-内蒙古大学图书馆

Accurate pulse time distribution determination using mlem algorithm in integral experiments

NUCLEAR ENGINEERING AND TECHNOLOGY 2025年第2期57卷

作者： Zhang, S. Y. Nie, Y. B. Ding, Y. Y. Zhao, Q. Xu, K. Z. Pan, X. Y. Chen, H. T. Sun, Q. Wei, Z. China Inst Atom Energy Key Lab Nucl Data Beijing 102413 Peoples R China Lanzhou Univ Sch Nucl Sci & Technol Lanzhou 730000 Peoples R China

Integral experiments play a crucial role in advancing nuclear science and technology by providing critical data that validate theoretical models and enhance reactor designs. This study presents a novel approach to accurately determine pulse time distribution in integral experiments conducted with pulsed accelerators. By strategically placed monitors and shields at angles of 0 degrees and 90 degrees relative to the beam direction, neutron flight times from the target are measured, and a response matrix for neutron emission at different times is constructed through simulation. The Maximum Likelihood Expectation Maximization (mlem) algorithm is employed for pulse time reconstruction, with the gamma ray flight time spectrum from monitors used as the initial spectrum to streamline the computational process. Experimental validation using a standard polyethylene sample and n-p scattering cross-sections confirms the accuracy of the method. Results are compared across multiple nuclear databases such as CENDL-3.2, ENDF/B-VIII.0, JENDL-5.0, and JEFF-3.3 libraries. The developed method significantly enhances the precision of pulse time distribution determination, thereby improving the quality and reliability of experimental data obtained from integral experiments conducted with pulsed accelerators.

关键词： Pulse time distribution mlem algorithm Integral experiment

来源：评论

学校读者我要写书评

暂无评论

Accelerated strategy for the mlem algorithm

引用

JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY 2021年第1期29卷 135-149页

作者： Zheng, Xuan Qu, Gangrong Zhou, Jiajia Beijing Jiaotong Univ Sch Sci Beijing 100044 Peoples R China

BACKGROUND: A statistical method called maximum likelihood expectation maximization (mlem) is quite attractive, especially in PET/SPECT. However, the convergence rate of the iterative scheme of mlem is quite slow. OBJECTIVE: This study aims to develop and test a new method to speed up the convergence rate of the mlem algorithm. METHODS: We introduce a relaxation parameter in the conventional mlem iterative formula and propose the relaxation strategy on the condition that the spectral radius of the derived iterative matrix from the iterative scheme with the accelerated parameter reaches a minimum value. RESULTS: Experiments with Shepp-Logan phantom and an annual tree image demonstrate that the new computational strategy effectively accelerates computation time while maintains reasonable image quality. CONCLUSIONS: The proposed new computational method involving the relaxation strategy has a faster convergence speed than the original method.

关键词： mlem algorithm convergence rate relaxation strategy image reconstruction

来源：评论

学校读者我要写书评

暂无评论

Internal radiation dose estimation using multiple D-shuttle dosimeters for positron emission tomography (PET): A validation study using NEMA body phantom

引用

MEDICAL PHYSICS 2018年第10期45卷 4693-4703页

作者： Islam, Md. Shahidul Watanuki, Shoichi Tashiro, Manabu Watabe, Hiroshi Tohoku Univ Ctr Cyclotron & Radioisotope Div Radiat Protect & Safety Control Sendai Miyagi 9808578 Japan Bangladesh Atom Energy Regulatory Author Radiat Control Div Dhaka 1207 Bangladesh Bangladesh Atom Energy Commiss E-12-A Agargaon Dhaka 1207 Bangladesh Tohoku Univ Ctr Cyclotron & Radioisotope Div Cyclotron Nucl Med Sendai Miyagi 9808578 Japan

PurposeInternal radiation dosimetry plays an important role in ensuring the safe use of positron emission tomography (PET) technology and is a legal requirement in most countries. We propose a new technique to estimate the internal radiation dose in PET studies by means of multiple D-shuttle dosimeters attached on the body surface of the patient. MethodsRadioactivity in a source organ was estimated iteratively using measurements from multiple D-shuttle dosimeters with a maximum-likelihood expectation-maximization (mlem) algorithm with dose response from a source to a D-shuttle dosimeter computed by Monte Carlo simulation. To validate our technique, we performed a phantom study using a National Electrical Manufacturers Association (NEMA) body phantom. The fillable compartments (torso cavity and six spheres) of the phantom were filled with F-18-FDG mixed with pure water using an 800:1 sphere-to-background radioactivity concentration ratio. The radioactivity concentrations present in the torso cavity and six spheres were 0.00165 MBq/mL and 1.32 MBq/mL, respectively. The initial radioactivities of the torso cavity and six spheres (treated as source organs) were 15.9 MBq (torso cavity), 34.7 MBq (37 mm sphere), 15.1 MBq (28 mm sphere), 7.27 MBq (22 mm sphere), 3.26 MBq (17 mm sphere), 1.54 MBq (13 mm sphere), and 0.697 MBq (10 mm sphere). Eleven D-shuttle dosimeters were attached to the NEMA body phantom surface to obtain information on body surface dose and a mathematical NEMA body phantom has been modeled in the Heavy Ion Transport Code System (PHITS) Monte Carlo simulation code. ResultsRadioactivity was estimated in 2 min intervals over a 110-min total dose time using our proposed technique. A significant correlation (R-2 = 0.992) was found between actual radioactivity and estimated radioactivity at every 2 min interval for each source organ. The estimated initial radioactivity (mean with standard deviation) was 16.5 0.311 MBq (torso cavity), 33.0 +/- 0.624 MBq (37 mm

关键词： D-shuttle dosimeter internal radiation dose mlem algorithm Monte Carlo simulation PET

来源：评论

学校读者我要写书评

暂无评论

An efficiency calibration method of segmented gamma scanning in reconstructing radioactive waste drum activity

引用

JOURNAL OF THE KOREAN PHYSICAL SOCIETY 2024年第4期84卷 251-263页

作者： Zheng, Honglong Tuo, Xianguo Wang, Zhou Gou, Rui Liu, Qi Li, Qiang Shi, Rui Yang, Guang Sichuan Univ Sci & Engn Zigong 643000 Peoples R China Chengdu Univ Technol Chengdu 610059 Peoples R China

For measuring radioactive waste drum, the segmented gamma scanning (SGS) is a quick and effective procedure. The accuracy of reconstructed radioactivity in the drum is directly impacted by SGS efficiency matrix. To overcome the challenges of restricted experimental source and excessive workload in existing SGS efficiency calibration methods, a new SGS efficiency calibration method is presented. The point source efficiency function calculates the non-attenuation efficiency of each voxel in the calibrated segment. The voxel attenuation efficiency is corrected by the linear attenuation coefficient for segments' absorption. The attenuation efficiency for the segment is calculated as the weighted average of all voxel attenuation efficiencies in a segment. The waste drum sample is filled with a random mixture of 0.33 g center dot cm-3 aluminium silicate fibre, 0.64 g center dot cm-3 wood fibre, 1.84 g center dot cm-3 polyvinyl chloride plastic and a point source 60Co of 1.244 x 105 Bq. The SGS system and the waste drum sample are used to complete SGS experimental measurement, efficiency calibration and activity reconstruction. Result shows that the relative deviations of reconstructed activity are - 15.39-30.98% for the extreme case where just a point source 60Co is placed at 16 positions in the drum with different heights and eccentric distances. This relative deviation rang of reconstructed activity meets the needs of most users. Compared with other methods which have complicated computational processes, the main benefit of this work is to present a low-performance and easy-to-implement additional alternative to commercial software or existing approaches.

关键词： Radioactive waste drum Efficiency calibration Segmented gamma scanning mlem algorithm Reconstructed activity

来源：评论

学校读者我要写书评

暂无评论

PET image reconstruction based on Bayesian inference regularised maximum likelihood expectation maximisation (mlem) method

引用

INTERNATIONAL JOURNAL OF BIOMEDICAL ENGINEERING AND TECHNOLOGY 2018年第4期27卷 337-354页

作者： Boudjelal, Abdelwahhab Messali, Zoubeida Attallah, Bilal Univ Msila Dept Elect Msila 28000 Algeria Univ Caen Normandy GREYC Lab Image Team F-14050 Caen France Univ Mohamed El Bachir El Ibrahimi Bordj Bou Arre Dept Elect Bordj Bou Arreridj 34030 Algeria

A better quality of an image can be achieved through iterative image reconstruction for positron emission tomography (PET) as it employs spatial regularisation that minimises the difference of image intensity among adjacent pixels. In this paper, the Bayesian inference rule is applied to devise a novel approach to address the ill-posed inverse problem associated with the iterative maximum-likelihood Expectation-Maximisation (mlem) algorithm by proposing a regularised constraint probability model. The proposed algorithm is more robust than the standard mlem and in background noise removal with preserving edges to suppress the out of focus slice blur, which is the existent image artefact. The quality measurements and visual inspections show a significant improvement in image quality compared to conventional mlem and the state-of-the-art regularised algorithms.

关键词： image reconstruction positron emission tomography post-reconstruction pre-reconstruction mlem algorithm Bayesian inference iterative algorithms

来源：评论

学校读者我要写书评

暂无评论

Including Pair-Production Events in the System Response Function for Energy-Imaging Integrated Deconvolution algorithm

Including Pair-Production Events in the System Response Func...

引用

IEEE Nuclear Science Symposium/Medical Imaging Conference (NSS/MIC)/18th International Workshop on Room-Temperature Semiconductor X-Ray and Gamma-Ray Detectors

作者： Wang, Weiyi He, Zhong Univ Michigan Dept Nucl Engn & Radiol Sci Ann Arbor MI 48109 USA

ISBN: (纸本)9781467301206

In previous research, our group developed a gamma-ray image reconstruction method using Compton events from a 3-D position-sensitive CdZnTe detector, which is capable of deconvolving the source image at any specific energy, as well as the incident spectrum at any specific direction. T his gamma-ray energy-imaging integrated deconvolution method takes place in integrated spatial and energy space using the maximum-likelihood expectation maximization (mlem) algorithm. By including Compton scattering events in the system model, the mlem solution estimates the incident gamma-ray spectrum in the source direction free of the Compton continuum for source energies lower than 1.02 MeV. In order to correctly reconstruct images for higher energy events, pair-production effect needs to be included in the system model. Since it is impossible to pre-calculate the system response function due to the huge number of possible recorded events, analytic formulas are derived to allow the calculation of the system response function during the reconstruction. After including pair-production events in the system response function, the deconvolved spectrum reflects the incident spectrum and is free of single and double escape peaks.

关键词： 3D position sensitive detector Acceleration Compton effect Compton scattering mlem algorithm deconvolution energy imaging integrated deconvolution algorithm expectation-maximisation algorithm gamma-ray applications gamma-ray image reconstruction gamma-rays image reconstruction maximum likelihood expectation maximization pair production event position sensitive particle detectors system response function

来源：评论

学校读者我要写书评

暂无评论

Maximum likelihood algorithm for PET image reconstruction based on fuzzy random variable

Maximum likelihood algorithm for PET image reconstruction ba...

引用

26th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society

作者： Zhu, HQ Shu, HZ Zhou, J Luo, LM Southeast Univ Dept Biol Sci & Med Engn Nanjing 210096 Peoples R China

ISBN: (纸本)0780384393

This paper presents a new iterative method for reconstructing positron emission tomography (PET) images. Unlike conventional maximum likelihood-expectation maximization (mlem), this method intends to introduce the fuzzy set principle to mlem algorithm. In this work, the non-cognitive uncertainty of the observed projection data are described by their probability density function;whereas the cognitive uncertainty of a random variable can be described by the membership function for its fuzziness. The mean of the observed projection data are regard as fuzzy random variables because of the complexity of system. The fuzzy random variable can be represented by a triangular membership function. We establish a joint probability density function that includes the effects of both fuzziness and randomness. The maximum likelihood approach is used to estimate the image vector. The order subset (OS), rescaled block-iterative (RBI), and row-action (RA) techniques are applied to our PET reconstructed method to speed up the convergence rate and to decrease the iteration numbers.

关键词： image reconstruction fuzzy random variables positron emission tomography mlem algorithm

来源：评论

学校读者我要写书评

暂无评论

A PDE based Expectation Maximization algorithm adapted to Poisson noise for Medical Image Reconstruction

A PDE based Expectation Maximization algorithm adapted to Po...

引用

IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)

作者： Tiwari, Shailendra Srivastava, Rajeev Banaras Hindu Univ Indian Inst Technol Dept Comp Sci & Engn Varanasi 221005 Uttar Pradesh India

ISBN: (纸本)9781479918119

Computerized Tomography and Positron Emission Tomography (CT/PET) is an effective and indispensable imaging tool for the application of medical image reconstruction. The noise contained in the data measured by imaging instruments is primarily Poisson type and decreasing the noise has the potential to optimize the quality of CT/PET images. But the traditional iterative reconstruction algorithms of CT/PET cannot effectively filter the noise. Recently anisotropic diffusion (AD) based nonlinear filter is introduced into tomography reconstruction that purports to filter the noise without blurring edges. This paper introduces and evaluates a hybrid approach to regularized maximum likelihood expectation maximization (mlem) iterative reconstruction technique with Poisson variability. Regularization is achieved by penalizing mlem with Anisotropic diffusion (AD) filter to form hybrid method for CT/PET image reconstruction using partial differential equation (PDE) based variational framework. The aim of this paper is to impose an effective edge preserving and noise removing to optimize the quality of CT/PET reconstructed images. A comparative analysis of the proposed model with some other existing standard methods in literature is presented both qualitatively and quantitatively using simulated test phantom and standard digital image. An experimental result indicates that the proposed method yields significantly improvements in quality of reconstructed images from the projection data. The obtained results justify the applicability of the proposed method.

关键词： Computerized Tomography (CT) Positron Emission Tomography (PET) mlem algorithm Iterative reconstruction Anisotropic Diffusion (AD) Partial differential Equation (PDE)

来源：评论

学校读者我要写书评

暂无评论

New reconstruction algorithm, distance dependent exact, with reduced statistical α error, dedicated to emission tomography using a collimator with large and long holes

New reconstruction algorithm, distance dependent exact, with...

引用

32nd Annual International Conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBC 10)

作者： Jeanguillaume, Christian Simonnet, Richard Rakotonirina, Herve Loeb, Jean Jacques Loeb, J. J. Univ Angers Lab Ingn Syst Automatises 62 Ave Notre Dame Lac F-49000 Angers France CHU Angers Serv Med Nucl F-49933 Angers France LAREMA Lab Angevin REcherche MAth F-49045 Angers France

ISBN: (纸本)9781424441242

SPECT (single photon emission computerized tomography) is physically one of the worst medical imaging modalities. Despite a considerable and still increasing medical impact, its spatial resolution (beyond 1 cm) and its sensitivity (less than 10(-4)) are both awful. This situation is mainly due to the use of a thin parallel hole collimator. In addition the application of the unfitted radon-transform worsens the figure. We already suggested a different approach of collimation called CACAO in French standing for computer aided collimation gamma camera. This approach uses a large and long hole collimator, a different sequence of acquisition with a linear scanning motion and a dedicated reconstruction program taking full account of the depth dependent response function. Up to now, however, the CACAO project has failed to convince the scientific community of its superiority over the conventional thin hole collimator. This is due of a lack of a good reconstruction algorithm. In this paper we depict a new tomographic reconstruction algorithm for the CACAO problem. In addition to the former cited advantages, this new algorithm is exact, it takes full account of the finite geometry of the collimator holes, it reduces the type 1 statistical error (false positive) and reduces the hindering effect of points with large errors (outliers). Example of reconstruction with exact data and with a limited number of detected photons are provided. Comparison with mlem algorithm is provided.

关键词： CACAO mlem algorithm SPECT collimators computer aided collimation gamma camera depth dependent response function distance dependent exact emission tomography expectation-maximisation algorithm image reconstruction large hole collimator linear scanning motion long hole collimator medical image processing medical imaging reconstruction algorithm reduced statistical Î± error single photon emission computed tomography single photon emission computerized tomography statistical analysis

来源：评论

学校读者我要写书评

暂无评论

Dictionary-based software for proton dose reconstruction and submilimetric range verification

引用

PHYSICS IN MEDICINE AND BIOLOGY 2022年第4期67卷 045002-045002页

作者： Onecha, V. V. Galve, P. Ibanez, P. Freijo, C. Arias-Valcayo, F. Sanchez-Parcerisa, D. Espana, S. Fraile, L. M. Udias, J. M. Univ Complutense Madrid CEI Moncloa EMFTEL & IPARCOS Grp Fis Nucl Madrid Spain Inst Invest Hosp Clin San Carlos IdISSC Ciudad Univ Madrid Spain Ctr Nacl Invest Cardiovasc CNIC Madrid Spain

Objective. This paper presents a new method for fast reconstruction (compatible with in-beam use) of deposited dose during proton therapy using data acquired from a PET scanner. The most innovative feature of this novel method is the production of noiseless reconstructed dose distributions from which proton range can be derived with high precision. Approach. A new mlem & simulated annealing (MSA) algorithm, developed especially in this work, reconstructs the deposited dose distribution from a realistic pre-calculated activity-dose dictionary. This dictionary contains the contribution of each beam in the plan to the 3D activity and dose maps, as calculated by a Monte Carlo simulation. The MSA algorithm, using a priori information of the treatment plan, seeks for the linear combination of activities of the precomputed beams that best fits the observed PET data, obtaining at the same time the deposited dose. Main results. the method has been tested using simulated data to determine its performance under 4 different test cases: (1) dependency of range detection accuracy with delivered dose, (2) in-beam versus offline verification, (3) ability to detect anatomical changes and (4) reconstruction of a realistic spread-out Bragg peak. The results show the ability of the method to accurately reconstruct doses from PET data corresponding to 1 Gy irradiations, both in intra-fraction and inter-fraction verification scenarios. For this dose level (1 Gy) the method was able to spot range variations as small as 0.6 mm. Significance. out method is able to reconstruct dose maps with remarkable accuracy from clinically relevant dose levels down to 1 Gy. Furthermore, due to the noiseless nature of reconstructed dose maps, an accuracy better than one millimeter was obtained in proton range estimates. These features make of this method a realistic option for range verification in proton therapy.

关键词： proton therapy proton dose reconstruction proton range verification PET imaging mlem algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：