首页 > 最新文献

IEEE Transactions on Radiation and Plasma Medical Sciences最新文献

英文 中文
First Results of the 4D-PET Brain System 4D-PET 脑系统的首批成果
IF 4.6 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Pub Date : 2024-06-11 DOI: 10.1109/TRPMS.2024.3412798
Andrea Gonzalez-Montoro;Santiago Jiménez-Serrano;Jorge Álamo;Julio Barberá;Alejandro Lucero;Neus Cucarella;Karel Díaz;Marta Freire;Antonio J. Gonzalez;Laura Moliner;Álvaro Mondejar;Constantino Morera-Ballester;John Prior;David Sánchez;Jose M. Benlloch
Positron emission tomography (PET) imaging is the molecular technique of choice for studying many illnesses, including the ones related to the brain. Nevertheless, the use of PET scanners in neurology is limited by several factors, such as their limited availability for brain imaging due to the high oncology demand for PET and the low sensitivity and poor spatial resolution in the brain of the standard PET scanners. To expand the PET application in neurology, the brain-specific systems with increased clinical and physical sensitivities and higher spatial resolution are required. The present work reports on the design and development process of a compact dedicated PET scanner suitable for human brain imaging. This article includes the description and experimental validation of the detector components and their implementation in a full-size system called 4D-PET. The detector has been designed to simultaneously provide photon depth of interaction (DOI) and time of flight (TOF) information. It is based on the semi-monolithic LYSO modules optically coupled to silicon photomultipliers (SiPMs) and connected to a multiplexing readout. The analog output signals are fed to the PETsys TOFPET2 analog-specific integrated circuit circuits enabling scalability of the readout. The evaluation of the 4D-PET modules resulted in average detector resolutions of $2.1pm 1$ .0 mm, $3.4pm 1$ .8 mm, and $386pm 9$ ps for the y- (transaxial direction), DOI-, and coincidence time resolution TOF, respectively. The preliminary 4D-PET imaging performance is reported through the simulations and for the first time through the real reconstructed images (collected in the La Fe Hospital, Valencia).
正电子发射断层扫描(PET)成像是研究许多疾病(包括与脑有关的疾病)的首选分子技术。然而,PET 扫描仪在神经病学中的应用受到几个因素的限制,例如,由于肿瘤学对 PET 的需求很高,因此脑成像的可用性有限,以及标准 PET 扫描仪的灵敏度低、脑部空间分辨率差。为了扩大 PET 在神经学领域的应用,需要临床和物理灵敏度更高和空间分辨率更高的脑部专用系统。本研究报告介绍了适用于人脑成像的紧凑型专用 PET 扫描仪的设计和开发过程。这篇文章包括探测器组件的描述和实验验证,以及它们在名为 4D-PET 的全尺寸系统中的实施情况。探测器的设计目的是同时提供光子相互作用深度(DOI)和飞行时间(TOF)信息。它基于半单片式 LYSO 模块,与硅光电倍增管(SiPM)光学耦合,并连接到多路复用读出器。模拟输出信号被馈送到 PETsys TOFPET2 模拟专用集成电路电路,从而实现了读出的可扩展性。通过对 4D-PET 模块的评估,Y-(横轴方向)、DOI- 和重合时间分辨率 TOF 的平均探测器分辨率分别为 2.1/pm 1$ .0 mm、3.4/pm 1$ .8 mm 和 386/pm 9$ ps。通过模拟和首次通过真实重建图像(在巴伦西亚拉费医院采集)报告了初步的 4D-PET 成像性能。
{"title":"First Results of the 4D-PET Brain System","authors":"Andrea Gonzalez-Montoro;Santiago Jiménez-Serrano;Jorge Álamo;Julio Barberá;Alejandro Lucero;Neus Cucarella;Karel Díaz;Marta Freire;Antonio J. Gonzalez;Laura Moliner;Álvaro Mondejar;Constantino Morera-Ballester;John Prior;David Sánchez;Jose M. Benlloch","doi":"10.1109/TRPMS.2024.3412798","DOIUrl":"https://doi.org/10.1109/TRPMS.2024.3412798","url":null,"abstract":"Positron emission tomography (PET) imaging is the molecular technique of choice for studying many illnesses, including the ones related to the brain. Nevertheless, the use of PET scanners in neurology is limited by several factors, such as their limited availability for brain imaging due to the high oncology demand for PET and the low sensitivity and poor spatial resolution in the brain of the standard PET scanners. To expand the PET application in neurology, the brain-specific systems with increased clinical and physical sensitivities and higher spatial resolution are required. The present work reports on the design and development process of a compact dedicated PET scanner suitable for human brain imaging. This article includes the description and experimental validation of the detector components and their implementation in a full-size system called 4D-PET. The detector has been designed to simultaneously provide photon depth of interaction (DOI) and time of flight (TOF) information. It is based on the semi-monolithic LYSO modules optically coupled to silicon photomultipliers (SiPMs) and connected to a multiplexing readout. The analog output signals are fed to the PETsys TOFPET2 analog-specific integrated circuit circuits enabling scalability of the readout. The evaluation of the 4D-PET modules resulted in average detector resolutions of \u0000<inline-formula> <tex-math>$2.1pm 1$ </tex-math></inline-formula>\u0000.0 mm, \u0000<inline-formula> <tex-math>$3.4pm 1$ </tex-math></inline-formula>\u0000.8 mm, and \u0000<inline-formula> <tex-math>$386pm 9$ </tex-math></inline-formula>\u0000 ps for the y- (transaxial direction), DOI-, and coincidence time resolution TOF, respectively. The preliminary 4D-PET imaging performance is reported through the simulations and for the first time through the real reconstructed images (collected in the La Fe Hospital, Valencia).","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"8 7","pages":"839-849"},"PeriodicalIF":4.6,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10554551","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142143720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Performance Evaluation of a Mobile Digital Tomosynthesis System Using a Moving CNT-Based Tube Array for Extremity Scans 使用移动式 CNT 管阵列进行四肢扫描的移动式数字断层扫描系统性能评估
IF 4.6 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Pub Date : 2024-06-06 DOI: 10.1109/TRPMS.2024.3408870
Mikiko Ito;Dahea Han;Tae-Hyung Kim;Young-Tae Kim;Sungeun Lee;Jeongtae Soh;Young-Jun Jung;Byungkee Lee
Digital tomosynthesis (DTS) can enhance diagnostic accuracy by providing 3-D volume images with a remarkably low-X-ray dose. The aim of this study is to provide an initial assessment of the image quality and the X-ray dose for a mobile DTS system employing a moving carbon-nanotube (CNT)-based digital X-ray source array and a fixed detector for extremity scans. This design allows to reduce the source-to-detector distance (SDD) to only 400 mm, thereby enabling a compact and highly mobile system. We first measured the entrance surface dose (ESD), which is the sum of the X-ray dose irradiated from individual projections using a dosimeter placed at the center of the X-ray detector. The ESDs obtained for hand, foot, and knee scan configurations were 0.15, 0.22, and 0.43 mGy, respectively, which were comparable to those obtained from 2-D radiography exposures. For the evaluation of its reconstructed image quality, the in-plane modulation transfer function (MTF), Z-resolution, geometry distortion, and image homogeneity were assessed by utilizing a wire-phantom, sphere-phantom, and PMMA phantoms. The reconstructed images of hand, ankle and knee phantoms were evaluated qualitatively. The results of the evaluation demonstrate the successful development of the mobile DTS system proposed in this article.
数字断层扫描(DTS)能以极低的 X 射线剂量提供三维容积图像,从而提高诊断的准确性。本研究的目的是对采用移动碳纳米管(CNT)数字 X 射线源阵列和固定探测器进行四肢扫描的移动 DTS 系统的图像质量和 X 射线剂量进行初步评估。这种设计可将光源到探测器的距离(SDD)缩短到仅 400 毫米,从而实现了系统的紧凑性和高度移动性。我们首先测量了入口表面剂量(ESD),即使用放置在 X 射线探测器中心的剂量计测量从单个投影照射的 X 射线剂量的总和。手部、足部和膝部扫描配置获得的 ESD 分别为 0.15、0.22 和 0.43 mGy,与二维放射摄影曝光获得的 ESD 相当。为了评估其重建图像的质量,利用线状模型、球状模型和 PMMA 模型对平面内调制传递函数(MTF)、Z 分辨率、几何失真和图像均匀性进行了评估。对手部、踝关节和膝关节模型的重建图像进行了定性评估。评估结果表明,本文提出的移动 DTS 系统开发成功。
{"title":"Performance Evaluation of a Mobile Digital Tomosynthesis System Using a Moving CNT-Based Tube Array for Extremity Scans","authors":"Mikiko Ito;Dahea Han;Tae-Hyung Kim;Young-Tae Kim;Sungeun Lee;Jeongtae Soh;Young-Jun Jung;Byungkee Lee","doi":"10.1109/TRPMS.2024.3408870","DOIUrl":"https://doi.org/10.1109/TRPMS.2024.3408870","url":null,"abstract":"Digital tomosynthesis (DTS) can enhance diagnostic accuracy by providing 3-D volume images with a remarkably low-X-ray dose. The aim of this study is to provide an initial assessment of the image quality and the X-ray dose for a mobile DTS system employing a moving carbon-nanotube (CNT)-based digital X-ray source array and a fixed detector for extremity scans. This design allows to reduce the source-to-detector distance (SDD) to only 400 mm, thereby enabling a compact and highly mobile system. We first measured the entrance surface dose (ESD), which is the sum of the X-ray dose irradiated from individual projections using a dosimeter placed at the center of the X-ray detector. The ESDs obtained for hand, foot, and knee scan configurations were 0.15, 0.22, and 0.43 mGy, respectively, which were comparable to those obtained from 2-D radiography exposures. For the evaluation of its reconstructed image quality, the in-plane modulation transfer function (MTF), \u0000<italic>Z</i>\u0000-resolution, geometry distortion, and image homogeneity were assessed by utilizing a wire-phantom, sphere-phantom, and PMMA phantoms. The reconstructed images of hand, ankle and knee phantoms were evaluated qualitatively. The results of the evaluation demonstrate the successful development of the mobile DTS system proposed in this article.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"8 7","pages":"826-838"},"PeriodicalIF":4.6,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142143750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Pyramid Convolutional Recurrent Network for Serial Medical Image Registration With Adaptive Motion Regularizations 利用自适应运动正则化实现串行医学图像配准的金字塔卷积递归网络
IF 4.6 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Pub Date : 2024-06-05 DOI: 10.1109/TRPMS.2024.3410021
Jiayi Lu;Renchao Jin;Enmin Song
Objective: Serial medical image registration plays an important role in radiation therapy treatment planning. However, current deep learning-based deformable registration models suffer from excessive resource consumption and suboptimal precision issues. Moreover, the global regularization term may result in unrealistic deformations due to displacement field noise and intertissue sliding motion omission. Methods: This article proposes a patch-based pyramid convolutional recurrent neural network (pyramid CRNet) for serial medical image registration. Patch-wise training is employed to alleviate resource constraints. Incorporating spatiotemporal features across multiple scales is beneficial for focusing on more details to improve accuracy. Moreover, two motion adaptive techniques are introduced to provide anatomically plausible displacement fields. The first uses a guided filter to reduce noise and maintain motion continuity within organs. The second involves a pixel-wise weight regularization term within the loss function to provide a tailored solution for distinctive tissue characteristics, especially for sliding motion at organ boundaries. Results: Experiments were conducted on lung 4DCT images and cardiac cine MR images. Quantitative and qualitative results have demonstrated that our method can align anatomical structures across multiple images in a physiologically sensible manner. Conclusion: The significance of this work lies in its potential to address pressing challenges in clinical applications, and further investigations could be extended to explore different modalities and dimensions.
目的:序列医疗图像配准在放射治疗规划中发挥着重要作用。然而,目前基于深度学习的可变形配准模型存在资源消耗过多和精度不理想的问题。此外,由于位移场噪声和组织间滑动运动遗漏,全局正则化项可能会导致不切实际的变形。方法:本文提出了一种基于补丁的金字塔卷积递归神经网络(pyramid CRNet),用于序列医学图像配准。为了缓解资源限制,采用了片段式训练。纳入多个尺度的时空特征有利于关注更多细节,从而提高准确性。此外,还引入了两种运动自适应技术,以提供解剖学上可信的位移场。第一种技术使用引导滤波器来减少噪声,并保持器官内部运动的连续性。第二种是在损失函数中加入像素权重正则化项,为独特的组织特征,尤其是器官边界的滑动运动提供量身定制的解决方案。实验结果对肺部 4DCT 图像和心脏椎体磁共振图像进行了实验。定量和定性结果表明,我们的方法能以生理学上合理的方式对准多幅图像上的解剖结构。结论这项工作的意义在于它有可能解决临床应用中的紧迫挑战,进一步的研究可以扩展到探索不同的模式和维度。
{"title":"Pyramid Convolutional Recurrent Network for Serial Medical Image Registration With Adaptive Motion Regularizations","authors":"Jiayi Lu;Renchao Jin;Enmin Song","doi":"10.1109/TRPMS.2024.3410021","DOIUrl":"https://doi.org/10.1109/TRPMS.2024.3410021","url":null,"abstract":"<italic>Objective:</i>\u0000 Serial medical image registration plays an important role in radiation therapy treatment planning. However, current deep learning-based deformable registration models suffer from excessive resource consumption and suboptimal precision issues. Moreover, the global regularization term may result in unrealistic deformations due to displacement field noise and intertissue sliding motion omission. \u0000<italic>Methods:</i>\u0000 This article proposes a patch-based pyramid convolutional recurrent neural network (pyramid CRNet) for serial medical image registration. Patch-wise training is employed to alleviate resource constraints. Incorporating spatiotemporal features across multiple scales is beneficial for focusing on more details to improve accuracy. Moreover, two motion adaptive techniques are introduced to provide anatomically plausible displacement fields. The first uses a guided filter to reduce noise and maintain motion continuity within organs. The second involves a pixel-wise weight regularization term within the loss function to provide a tailored solution for distinctive tissue characteristics, especially for sliding motion at organ boundaries. \u0000<italic>Results:</i>\u0000 Experiments were conducted on lung 4DCT images and cardiac cine MR images. Quantitative and qualitative results have demonstrated that our method can align anatomical structures across multiple images in a physiologically sensible manner. \u0000<italic>Conclusion:</i>\u0000 The significance of this work lies in its potential to address pressing challenges in clinical applications, and further investigations could be extended to explore different modalities and dimensions.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"8 7","pages":"800-813"},"PeriodicalIF":4.6,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142143653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Data Augmentation Using the Hierarchical Encoding of Deformation Fields Between CT Images 利用 CT 图像间变形场的分层编码进行数据扩增
IF 4.6 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Pub Date : 2024-06-03 DOI: 10.1109/TRPMS.2024.3408818
Yuya Kuriyama;Mitsuhiro Nakamura;Megumi Nakao
The field of medical machine learning has encountered the challenge of constructing a large-scale image database that includes both the anatomical variability and teaching labels because there are often not sufficient cases of a specific disease. Adversarial learning has been studied for nonlinear data augmentation. However, deep learning models may produce anatomically unrealistic structures or inaccurate pixel values when applied to small sets of computed tomography (CT) images. To overcome this issue, we propose a data augmentation method that uses the hierarchical encoding of deformation fields between the CT images. This allows for the generation of synthetic CT images with shape variability while preserving the patient-specific CT values. Our framework encodes the spatial features of deformation fields into hierarchical latent variables, and generates the synthetic deformation fields by updating the values in specific layers. To implement this concept, we applied the StyleGAN2 and its encoder pixel2style2pixel to the deformation fields and added the ability to control the level of detail in the deformation through the Style Mixing. Our experiments demonstrated that our framework produced high-quality synthetic CT images compared with a conventional framework. Additionally, we applied the augmented datasets with teaching labels to semantic segmentation tasks targeting the liver and stomach, and found that accuracy improved by 1.3% and 7.9%, respectively, which surpassed the results obtained by the existing data augmentation methods.
医学机器学习领域面临的挑战是,如何构建一个既包含解剖变异又包含教学标签的大规模图像数据库,因为特定疾病往往没有足够的病例。对抗学习已被研究用于非线性数据增强。然而,当深度学习模型应用于小型计算机断层扫描(CT)图像集时,可能会产生不切实际的解剖结构或不准确的像素值。为了克服这一问题,我们提出了一种数据增强方法,该方法使用 CT 图像之间的变形场分层编码。这样就能生成具有形状可变性的合成 CT 图像,同时保留患者特定的 CT 值。我们的框架将形变场的空间特征编码为分层潜变量,并通过更新特定层中的值生成合成形变场。为了实现这一概念,我们将 StyleGAN2 及其编码器 pixel2style2pixel 应用于形变场,并通过样式混合(Style Mixing)添加了控制形变细节级别的功能。实验证明,与传统框架相比,我们的框架能生成高质量的合成 CT 图像。此外,我们还将带有教学标签的增强数据集应用于针对肝脏和胃的语义分割任务,结果发现准确率分别提高了 1.3% 和 7.9%,超过了现有数据增强方法的结果。
{"title":"Data Augmentation Using the Hierarchical Encoding of Deformation Fields Between CT Images","authors":"Yuya Kuriyama;Mitsuhiro Nakamura;Megumi Nakao","doi":"10.1109/TRPMS.2024.3408818","DOIUrl":"https://doi.org/10.1109/TRPMS.2024.3408818","url":null,"abstract":"The field of medical machine learning has encountered the challenge of constructing a large-scale image database that includes both the anatomical variability and teaching labels because there are often not sufficient cases of a specific disease. Adversarial learning has been studied for nonlinear data augmentation. However, deep learning models may produce anatomically unrealistic structures or inaccurate pixel values when applied to small sets of computed tomography (CT) images. To overcome this issue, we propose a data augmentation method that uses the hierarchical encoding of deformation fields between the CT images. This allows for the generation of synthetic CT images with shape variability while preserving the patient-specific CT values. Our framework encodes the spatial features of deformation fields into hierarchical latent variables, and generates the synthetic deformation fields by updating the values in specific layers. To implement this concept, we applied the StyleGAN2 and its encoder pixel2style2pixel to the deformation fields and added the ability to control the level of detail in the deformation through the Style Mixing. Our experiments demonstrated that our framework produced high-quality synthetic CT images compared with a conventional framework. Additionally, we applied the augmented datasets with teaching labels to semantic segmentation tasks targeting the liver and stomach, and found that accuracy improved by 1.3% and 7.9%, respectively, which surpassed the results obtained by the existing data augmentation methods.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"8 8","pages":"939-949"},"PeriodicalIF":4.6,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142587626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Intercrystal Optical Crosstalk in Radiation Detectors: Monte Carlo Modeling and Experimental Validation 辐射探测器中的晶体间光学串扰:蒙特卡罗建模与实验验证
IF 4.6 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Pub Date : 2024-04-29 DOI: 10.1109/TRPMS.2024.3395131
Carlotta Trigila;N. Kratochwil;B. Mehadji;G. Ariño-Estrada;E. Roncali
High-performance radiation detectors often employ crystal arrays where light can leak between them, a phenomenon called intercrystal crosstalk, which demands mitigation for optimal detector performance. The complexity of measuring optical crosstalk in conventional detector geometries makes optical Monte Carlo simulation essential to study and reduce crosstalk through better designs. Addressing the absence of validated transmission models in Monte Carlo toolkits, we developed and integrated a new simulation model into the look-up table Davis Model, aiming at simulating optical photon refraction at the crystal interfaces using GATE. For the first time, we validated the intercrystal optical crosstalk model with experiments in two optically coupled Lutetium-yttrium oxyorthosilicate crystals read by two SiPMs, testing three thicknesses and four interfaces (air, glue, Teflon, and ESR). Simulated and experimental crosstalk agreed within one FWHM for all configurations. These results show the possibility of predicting optical photon transmission in detector designs with multiple crystal elements. Indeed, although validated using only two crystals, the model can be used in more complex geometries. The model, available to GATE users upon request, provides a valuable resource for researchers when optimizing detector geometry where optical crosstalk needs to be considered, i.e., ensuring optical isolation between the photodetector’s responses.
高性能辐射探测器通常采用晶体阵列,晶体间可能存在漏光现象,这种现象被称为晶体间串扰。测量传统探测器几何结构中光学串扰的复杂性使得光学蒙特卡罗模拟成为研究和通过更好的设计减少串扰的关键。针对蒙特卡罗工具包中缺乏经过验证的传输模型的问题,我们开发了一种新的模拟模型,并将其集成到查找表戴维斯模型中,旨在利用 GATE 模拟晶体界面上的光学光子折射。我们首次在两个光学耦合镥钇氧硅酸盐晶体中通过两个 SiPM 读取实验验证了晶体间光学串扰模型,测试了三种厚度和四种界面(空气、胶水、聚四氟乙烯和 ESR)。在所有配置中,模拟串扰和实验串扰都在一个 FWHM 范围内。这些结果表明,在具有多个晶体元件的探测器设计中,预测光学光子传输是可能的。事实上,虽然该模型仅使用两个晶体进行了验证,但可用于更复杂的几何结构。该模型可应要求提供给 GATE 用户,为研究人员优化需要考虑光学串扰的探测器几何结构(即确保光探测器响应之间的光学隔离)提供了宝贵的资源。
{"title":"Intercrystal Optical Crosstalk in Radiation Detectors: Monte Carlo Modeling and Experimental Validation","authors":"Carlotta Trigila;N. Kratochwil;B. Mehadji;G. Ariño-Estrada;E. Roncali","doi":"10.1109/TRPMS.2024.3395131","DOIUrl":"https://doi.org/10.1109/TRPMS.2024.3395131","url":null,"abstract":"High-performance radiation detectors often employ crystal arrays where light can leak between them, a phenomenon called intercrystal crosstalk, which demands mitigation for optimal detector performance. The complexity of measuring optical crosstalk in conventional detector geometries makes optical Monte Carlo simulation essential to study and reduce crosstalk through better designs. Addressing the absence of validated transmission models in Monte Carlo toolkits, we developed and integrated a new simulation model into the look-up table Davis Model, aiming at simulating optical photon refraction at the crystal interfaces using GATE. For the first time, we validated the intercrystal optical crosstalk model with experiments in two optically coupled Lutetium-yttrium oxyorthosilicate crystals read by two SiPMs, testing three thicknesses and four interfaces (air, glue, Teflon, and ESR). Simulated and experimental crosstalk agreed within one FWHM for all configurations. These results show the possibility of predicting optical photon transmission in detector designs with multiple crystal elements. Indeed, although validated using only two crystals, the model can be used in more complex geometries. The model, available to GATE users upon request, provides a valuable resource for researchers when optimizing detector geometry where optical crosstalk needs to be considered, i.e., ensuring optical isolation between the photodetector’s responses.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"8 7","pages":"734-742"},"PeriodicalIF":4.6,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10510415","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142143679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Dual-Ended Readout PET Detector Based on Multivoltage Threshold Sampling Combined With Convolutional Neural Network for Energy Calculation 基于多电压阈值采样的双端读出 PET 检测器与用于能量计算的卷积神经网络相结合
IF 4.6 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Pub Date : 2024-04-24 DOI: 10.1109/TRPMS.2024.3393235
Ran Cheng;Mingchen Sun;Fei Wang;Dengyun Mu;Yu Liu;Qingguo Xie;Bensheng Qiu;Xun Chen;Peng Xiao
To minimize parallax errors and achieve high spatial resolution positron emission tomography (PET) systems, developing depth-of-Interaction (DOI) encoding detectors has become a significant research topic. In this article, we investigated a dual-ended readout PET detector based on the multivoltage threshold (MVT) sampling method combined with a convolutional neural network (CNN) to calculate the pulse’s energy (MVT-CNN method). The MVT sampling method was used to acquire time-threshold samples and digitize scintillation pulses. The CNN model was employed to establish an accurate mapping between MVT sampling points and energy information. The dual-ended readout detector’s energy, DOI, and timing performance were evaluated with two irradiation configurations. The results demonstrated that the performance of the MVT-CNN method was close to that of the integration method based on oscilloscope sampling. Using the MVT-CNN method, the average energy resolution of the tested crystals over all depths was $14.5 , pm , 1.2$ %, and the average DOI resolution was $2.81 , pm , 0$ .70 mm. In the side irradiation configuration, the average coincidence timing resolution of the tested crystals at 2 mm depth was 435 ps. The performance of the dual-ended readout DOI-PET detector basedon the MVT-CNN method suggested that it could develop small animal and organ-dedicated PET systems with high sensitivity and uniform spatial resolutionxs.
为了最大限度地减少视差误差并实现高空间分辨率的正电子发射断层扫描(PET)系统,开发交互深度(DOI)编码探测器已成为一个重要的研究课题。在本文中,我们研究了一种基于多电压阈值(MVT)采样法的双端读出 PET 检测器,该检测器与计算脉冲能量的卷积神经网络(CNN)相结合(MVT-CNN 法)。多电压阈值采样法用于获取时间阈值样本并将闪烁脉冲数字化。CNN 模型用于在 MVT 采样点和能量信息之间建立精确的映射关系。利用两种辐照配置对双端读出探测器的能量、DOI 和定时性能进行了评估。结果表明,MVT-CNN 方法的性能接近于基于示波器采样的集成方法。使用 MVT-CNN 方法,测试晶体在所有深度上的平均能量分辨率为 14.5 美元 (pm ,1.2 美元 %),平均 DOI 分辨率为 2.81 美元 (pm ,0 美元 .70 毫米)。在侧辐照配置中,测试晶体在 2 毫米深度的平均重合定时分辨率为 435 ps。基于 MVT-CNN 方法的双端读出 DOI-PET 探测器的性能表明,它可以开发具有高灵敏度和均匀空间分辨率的小动物和器官专用 PET 系统。
{"title":"Dual-Ended Readout PET Detector Based on Multivoltage Threshold Sampling Combined With Convolutional Neural Network for Energy Calculation","authors":"Ran Cheng;Mingchen Sun;Fei Wang;Dengyun Mu;Yu Liu;Qingguo Xie;Bensheng Qiu;Xun Chen;Peng Xiao","doi":"10.1109/TRPMS.2024.3393235","DOIUrl":"https://doi.org/10.1109/TRPMS.2024.3393235","url":null,"abstract":"To minimize parallax errors and achieve high spatial resolution positron emission tomography (PET) systems, developing depth-of-Interaction (DOI) encoding detectors has become a significant research topic. In this article, we investigated a dual-ended readout PET detector based on the multivoltage threshold (MVT) sampling method combined with a convolutional neural network (CNN) to calculate the pulse’s energy (MVT-CNN method). The MVT sampling method was used to acquire time-threshold samples and digitize scintillation pulses. The CNN model was employed to establish an accurate mapping between MVT sampling points and energy information. The dual-ended readout detector’s energy, DOI, and timing performance were evaluated with two irradiation configurations. The results demonstrated that the performance of the MVT-CNN method was close to that of the integration method based on oscilloscope sampling. Using the MVT-CNN method, the average energy resolution of the tested crystals over all depths was \u0000<inline-formula> <tex-math>$14.5 , pm , 1.2$ </tex-math></inline-formula>\u0000%, and the average DOI resolution was \u0000<inline-formula> <tex-math>$2.81 , pm , 0$ </tex-math></inline-formula>\u0000.70 mm. In the side irradiation configuration, the average coincidence timing resolution of the tested crystals at 2 mm depth was 435 ps. The performance of the dual-ended readout DOI-PET detector basedon the MVT-CNN method suggested that it could develop small animal and organ-dedicated PET systems with high sensitivity and uniform spatial resolutionxs.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"8 7","pages":"709-717"},"PeriodicalIF":4.6,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142143651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Analyze Methodology of ToF Spectrum on Cherenkov and Scintillation Emission in BGO Scintillator 分析 ToF 光谱对 BGO 闪烁器中切伦科夫和闪烁发射的影响方法
IF 4.6 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Pub Date : 2024-04-22 DOI: 10.1109/TRPMS.2024.3391944
Go Kawata;M. Teshigawara
A time-of-flight (ToF) spectrum model has been developed to quantitatively understand the emission sequences in realistic scintillation detectors. This model is used to carefully investigate the Cherenkov and scintillation photon emission processes. To construct this model, we initially identified several primary physical processes occurring within scintillators and selected those that significantly contribute to the spectrum. The characteristics of each process were statistically incorporated into the model. Importantly, the model also takes into account the variance in the interaction point between the incident gamma photon and the electron, which serves as a contributing factor. To confirm the model’s validity, an experiment was conducted. A pair of 20-mm long bismuth germanate oxide detectors, paired with a silicon photomultiplier, used for this purpose. Experimental results provided the number of scintillation photons and the scintillation decay time constants. The time constant for Cherenkov emission was derived from the existing literature, and approximately one Cherenkov photon was used to fit the ToF spectrum obtained by the experiment. The model successfully reproduced the experimental ToF spectra with validity using the parameter values obtained in the experiment. However, the estimated number of scintillation photons in our experiment was about half of the yield number reported in literatures, while the number of Cherenkov photons utilized in the validation process was in line with those reported by other groups. Our results suggest that a combined analysis of the phenomenological model that accepts the behavior of the real system and particle-based Monte-Carlo simulation that treats the ideal system deductively is a meaningful approach for detector development based on an accurate understanding of the real system.
为了定量了解现实闪烁探测器中的发射序列,我们开发了飞行时间(ToF)光谱模型。该模型用于仔细研究切伦科夫和闪烁光子发射过程。为了构建这个模型,我们首先确定了闪烁体中发生的几个主要物理过程,并选择了对光谱有重大影响的过程。每个过程的特征都被统计到模型中。重要的是,该模型还考虑到了入射伽马光子与电子之间相互作用点的差异,这也是一个影响因素。为了证实模型的有效性,我们进行了一次实验。一对 20 毫米长的锗酸铋氧化物探测器与一个硅光电倍增管配对使用。实验结果提供了闪烁光子的数量和闪烁衰减时间常数。切伦科夫发射的时间常数是从现有文献中推导出来的,大约一个切伦科夫光子被用来拟合实验获得的 ToF 光谱。利用实验中获得的参数值,该模型成功地再现了实验 ToF 光谱。不过,我们实验中估计的闪烁光子数量约为文献报道的产量的一半,而验证过程中使用的切伦科夫光子数量与其他研究小组报道的数量一致。我们的结果表明,将接受真实系统行为的现象学模型与演绎处理理想系统的粒子蒙特卡洛模拟相结合进行分析,是在准确理解真实系统的基础上开发探测器的有效方法。
{"title":"Analyze Methodology of ToF Spectrum on Cherenkov and Scintillation Emission in BGO Scintillator","authors":"Go Kawata;M. Teshigawara","doi":"10.1109/TRPMS.2024.3391944","DOIUrl":"https://doi.org/10.1109/TRPMS.2024.3391944","url":null,"abstract":"A time-of-flight (ToF) spectrum model has been developed to quantitatively understand the emission sequences in realistic scintillation detectors. This model is used to carefully investigate the Cherenkov and scintillation photon emission processes. To construct this model, we initially identified several primary physical processes occurring within scintillators and selected those that significantly contribute to the spectrum. The characteristics of each process were statistically incorporated into the model. Importantly, the model also takes into account the variance in the interaction point between the incident gamma photon and the electron, which serves as a contributing factor. To confirm the model’s validity, an experiment was conducted. A pair of 20-mm long bismuth germanate oxide detectors, paired with a silicon photomultiplier, used for this purpose. Experimental results provided the number of scintillation photons and the scintillation decay time constants. The time constant for Cherenkov emission was derived from the existing literature, and approximately one Cherenkov photon was used to fit the ToF spectrum obtained by the experiment. The model successfully reproduced the experimental ToF spectra with validity using the parameter values obtained in the experiment. However, the estimated number of scintillation photons in our experiment was about half of the yield number reported in literatures, while the number of Cherenkov photons utilized in the validation process was in line with those reported by other groups. Our results suggest that a combined analysis of the phenomenological model that accepts the behavior of the real system and particle-based Monte-Carlo simulation that treats the ideal system deductively is a meaningful approach for detector development based on an accurate understanding of the real system.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"8 8","pages":"867-875"},"PeriodicalIF":4.6,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10506219","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142587513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
One-Sample Diffusion Modeling in Projection Domain for Low-Dose CT Imaging 低剂量 CT 成像投影域中的单样本扩散建模
IF 4.6 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Pub Date : 2024-04-22 DOI: 10.1109/TRPMS.2024.3392248
Bin Huang;Shiyu Lu;Liu Zhang;Boyu Lin;Weiwen Wu;Qiegen Liu
Low-dose computed tomography (CT) is crucial in clinical applications for reducing radiation risks. However, lowering the radiation dose will significantly degrade the image quality. In the meanwhile, common deep learning methods require large data, which are short for privacy leaking, expensive, and time-consuming. Therefore, we propose a fully unsupervised one-sample diffusion modeling (OSDM) in projection domain for low-dose CT reconstruction. To extract sufficient prior information from a single sample, the Hankel matrix formulation is employed. Besides, the penalized weighted least-squares and total variation are introduced to achieve superior image quality. First, we train a score-based diffusion model on one sinogram to capture the prior distribution with input tensors extracted from the structural-Hankel matrix. Then, at inference, we perform iterative stochastic differential equation solver and data-consistency steps to obtain sinogram data, followed by the filtered back-projection algorithm for image reconstruction. The results approach normal-dose counterparts, validating OSDM as an effective and practical model to reduce artifacts while preserving image quality.
低剂量计算机断层扫描(CT)在临床应用中对于降低辐射风险至关重要。然而,降低辐射剂量会大大降低图像质量。与此同时,常见的深度学习方法需要大量数据,而这些数据对于隐私泄露来说是短板,且成本高、耗时长。因此,我们提出了一种投影域的完全无监督单样本扩散建模(OSDM),用于低剂量 CT 重建。为了从单个样本中提取足够的先验信息,我们采用了 Hankel 矩阵公式。此外,我们还引入了惩罚性加权最小二乘法和总变异,以获得更高的图像质量。首先,我们在一个正弦曲线上训练一个基于分数的扩散模型,利用从结构-汉克尔矩阵中提取的输入张量来捕捉先验分布。然后,在推理过程中,我们执行迭代随机微分方程求解器和数据一致性步骤来获取正弦曲线数据,接着使用滤波后投影算法进行图像重建。结果接近正常剂量对应模型,验证了 OSDM 是一种有效、实用的模型,可在保持图像质量的同时减少伪影。
{"title":"One-Sample Diffusion Modeling in Projection Domain for Low-Dose CT Imaging","authors":"Bin Huang;Shiyu Lu;Liu Zhang;Boyu Lin;Weiwen Wu;Qiegen Liu","doi":"10.1109/TRPMS.2024.3392248","DOIUrl":"https://doi.org/10.1109/TRPMS.2024.3392248","url":null,"abstract":"Low-dose computed tomography (CT) is crucial in clinical applications for reducing radiation risks. However, lowering the radiation dose will significantly degrade the image quality. In the meanwhile, common deep learning methods require large data, which are short for privacy leaking, expensive, and time-consuming. Therefore, we propose a fully unsupervised one-sample diffusion modeling (OSDM) in projection domain for low-dose CT reconstruction. To extract sufficient prior information from a single sample, the Hankel matrix formulation is employed. Besides, the penalized weighted least-squares and total variation are introduced to achieve superior image quality. First, we train a score-based diffusion model on one sinogram to capture the prior distribution with input tensors extracted from the structural-Hankel matrix. Then, at inference, we perform iterative stochastic differential equation solver and data-consistency steps to obtain sinogram data, followed by the filtered back-projection algorithm for image reconstruction. The results approach normal-dose counterparts, validating OSDM as an effective and practical model to reduce artifacts while preserving image quality.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"8 8","pages":"902-915"},"PeriodicalIF":4.6,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10506793","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142587522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Structure-Enhanced Unsupervised Domain Adaptation for CT Whole-Brain Segmentation 用于 CT 全脑分割的结构增强型无监督领域自适应技术
IF 4.6 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Pub Date : 2024-04-19 DOI: 10.1109/TRPMS.2024.3391285
Yixin Chen;Yajun Gao;Lei Zhu;Jianan Li;Yan Wang;Jiakui Hu;Hongbin Han;Yanye Lu;Zhaoheng Xie
Early and accurate identification of intracranial hemorrhage (ICH) is crucial for treatment, but the inherently low-contrast resolution of computed tomography (CT) imaging poses challenges in identification of specific cerebral regions, impacting effective and timely clinical decision-making. We propose brain structure-enhanced domain adaptation (BraSEDA), a CT-based unsupervised domain adaptation (UDA) model designed to assist in the identification of brain regions. BraSEDA framework utilizes a cross-modal instance normalization (CMIN) module for enhancing CT image structural features and creating high-quality pseudo magnetic resonance (MR) images. A multilevel CMIN architecture is also introduced for further improvement. The BraSEDA framework improved the quality of pseudo MR images in head CT to MR domain adaptation task, as reflected by the lowest-Fréchet inception distance scores $95.0pm 12.1$ (p-value < 0.001) with and highest-BC scores $0.915pm 0.396$ (p-value <0.01),>https://github.com/YixinChen-AI/BraSEDA.
早期准确识别颅内出血(ICH)对治疗至关重要,但计算机断层扫描(CT)成像固有的低对比分辨率给识别特定脑区带来了挑战,影响了有效及时的临床决策。我们提出了脑结构增强域适配(BraSEDA),这是一种基于 CT 的无监督域适配(UDA)模型,旨在帮助识别脑区。BraSEDA 框架利用跨模态实例归一化(CMIN)模块来增强 CT 图像的结构特征,并创建高质量的伪磁共振(MR)图像。为了进一步改进,还引入了多级 CMIN 架构。BraSEDA框架提高了头部CT到MR域适应任务中伪MR图像的质量,具体表现为最低弗雷谢特起始距离得分$95.0pm 12.1$(p值<0.001),最高BC得分$0.915pm 0.396$(p值https://github.com/YixinChen-AI/BraSEDA)。
{"title":"Structure-Enhanced Unsupervised Domain Adaptation for CT Whole-Brain Segmentation","authors":"Yixin Chen;Yajun Gao;Lei Zhu;Jianan Li;Yan Wang;Jiakui Hu;Hongbin Han;Yanye Lu;Zhaoheng Xie","doi":"10.1109/TRPMS.2024.3391285","DOIUrl":"https://doi.org/10.1109/TRPMS.2024.3391285","url":null,"abstract":"Early and accurate identification of intracranial hemorrhage (ICH) is crucial for treatment, but the inherently low-contrast resolution of computed tomography (CT) imaging poses challenges in identification of specific cerebral regions, impacting effective and timely clinical decision-making. We propose brain structure-enhanced domain adaptation (BraSEDA), a CT-based unsupervised domain adaptation (UDA) model designed to assist in the identification of brain regions. BraSEDA framework utilizes a cross-modal instance normalization (CMIN) module for enhancing CT image structural features and creating high-quality pseudo magnetic resonance (MR) images. A multilevel CMIN architecture is also introduced for further improvement. The BraSEDA framework improved the quality of pseudo MR images in head CT to MR domain adaptation task, as reflected by the lowest-Fréchet inception distance scores \u0000<inline-formula> <tex-math>$95.0pm 12.1$ </tex-math></inline-formula>\u0000 (p-value < 0.001) with and highest-BC scores \u0000<inline-formula> <tex-math>$0.915pm 0.396$ </tex-math></inline-formula>\u0000 (p-value <0.01),>https://github.com/YixinChen-AI/BraSEDA</uri>\u0000.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"8 8","pages":"926-938"},"PeriodicalIF":4.6,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142587584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Quantum Entanglement Filtering: A PET Feasibility Study in Imaging Dual-Positron and Prompt Gamma Emission via Monte Carlo Simulation 量子纠缠过滤:通过蒙特卡罗模拟对双正电子和伽马射线发射成像的 PET 可行性研究
IF 4.6 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Pub Date : 2024-04-15 DOI: 10.1109/TRPMS.2024.3388872
Gregory Romanchek;Greyson Shoop;Kimia Gholami;Emily Enlow;Shiva Abbaszadeh
In this article, we investigate quantum entanglement (QE) filtering to address the challenges in multi-isotope positron emission tomography (PET) or in PET studies utilizing radiotracers with dual-positron and prompt gamma emissions. Via GATE simulation, we demonstrate the efficacy of QE filtering using a one-of-a-kind cadmium–zinc–telluride (CZT) PET system—establishing its viability as a multimodal scanner and ability to perform QE filtering. We show the high Compton scattering probability in this CZT-based scanner with 44.2% of gammas undergoing a single scatter prior to absorption. Additionally, the overall system sensitivity as a standard PET scanner (11.29%), QE-PET scanner (6.81%), and Compton camera (10.05%) is quantified. Further, we find a 23% decrease in the double Compton scatter (DCSc) frequency needed for QE filtering for each mm decrease in crystal resolution and an increase in mean absolute error (MAE) of their $Delta phi $ s from 6.8° for 1 mm resolution to 9.5°, 12.2°, and 15.3° for 2, 4, and 8 mm resolution, respectively. These results reinforce the potential of CZT detectors to lead next-generation PET systems by fully leveraging QE information of positron annihilation photons.
在这篇文章中,我们研究了量子纠缠(QE)滤波,以解决多同位素正电子发射断层扫描(PET)或利用具有双正电子和瞬时伽马射线发射的放射性同位素进行 PET 研究时所面临的挑战。通过 GATE 仿真,我们利用独一无二的碲锌镉(CZT)正电子发射计算机断层成像系统展示了 QE 滤波的功效,证明了该系统作为多模态扫描仪的可行性以及执行 QE 滤波的能力。我们展示了这种基于 CZT 的扫描仪的高康普顿散射概率,44.2% 的伽马在吸收前发生一次散射。此外,我们还量化了标准 PET 扫描仪(11.29%)、QE-PET 扫描仪(6.81%)和康普顿相机(10.05%)的整体系统灵敏度。此外,我们还发现晶体分辨率每降低一毫米,QE 滤波所需的双康普顿散射 (DCSc) 频率就会降低 23%,其 $Delta phi $ s 的平均绝对误差 (MAE) 也会从 1 毫米分辨率的 6.8° 分别增加到 2、4 和 8 毫米分辨率的 9.5°、12.2° 和 15.3°。这些结果加强了 CZT 探测器通过充分利用正电子湮灭光子的 QE 信息引领下一代 PET 系统的潜力。
{"title":"Quantum Entanglement Filtering: A PET Feasibility Study in Imaging Dual-Positron and Prompt Gamma Emission via Monte Carlo Simulation","authors":"Gregory Romanchek;Greyson Shoop;Kimia Gholami;Emily Enlow;Shiva Abbaszadeh","doi":"10.1109/TRPMS.2024.3388872","DOIUrl":"https://doi.org/10.1109/TRPMS.2024.3388872","url":null,"abstract":"In this article, we investigate quantum entanglement (QE) filtering to address the challenges in multi-isotope positron emission tomography (PET) or in PET studies utilizing radiotracers with dual-positron and prompt gamma emissions. Via GATE simulation, we demonstrate the efficacy of QE filtering using a one-of-a-kind cadmium–zinc–telluride (CZT) PET system—establishing its viability as a multimodal scanner and ability to perform QE filtering. We show the high Compton scattering probability in this CZT-based scanner with 44.2% of gammas undergoing a single scatter prior to absorption. Additionally, the overall system sensitivity as a standard PET scanner (11.29%), QE-PET scanner (6.81%), and Compton camera (10.05%) is quantified. Further, we find a 23% decrease in the double Compton scatter (DCSc) frequency needed for QE filtering for each mm decrease in crystal resolution and an increase in mean absolute error (MAE) of their \u0000<inline-formula> <tex-math>$Delta phi $ </tex-math></inline-formula>\u0000s from 6.8° for 1 mm resolution to 9.5°, 12.2°, and 15.3° for 2, 4, and 8 mm resolution, respectively. These results reinforce the potential of CZT detectors to lead next-generation PET systems by fully leveraging QE information of positron annihilation photons.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"8 8","pages":"916-925"},"PeriodicalIF":4.6,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10499999","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142587523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
期刊
IEEE Transactions on Radiation and Plasma Medical Sciences
全部 Acc. Chem. Res. ACS Applied Bio Materials ACS Appl. Electron. Mater. ACS Appl. Energy Mater. ACS Appl. Mater. Interfaces ACS Appl. Nano Mater. ACS Appl. Polym. Mater. ACS BIOMATER-SCI ENG ACS Catal. ACS Cent. Sci. ACS Chem. Biol. ACS Chemical Health & Safety ACS Chem. Neurosci. ACS Comb. Sci. ACS Earth Space Chem. ACS Energy Lett. ACS Infect. Dis. ACS Macro Lett. ACS Mater. Lett. ACS Med. Chem. Lett. ACS Nano ACS Omega ACS Photonics ACS Sens. ACS Sustainable Chem. Eng. ACS Synth. Biol. Anal. Chem. BIOCHEMISTRY-US Bioconjugate Chem. BIOMACROMOLECULES Chem. Res. Toxicol. Chem. Rev. Chem. Mater. CRYST GROWTH DES ENERG FUEL Environ. Sci. Technol. Environ. Sci. Technol. Lett. Eur. J. Inorg. Chem. IND ENG CHEM RES Inorg. Chem. J. Agric. Food. Chem. J. Chem. Eng. Data J. Chem. Educ. J. Chem. Inf. Model. J. Chem. Theory Comput. J. Med. Chem. J. Nat. Prod. J PROTEOME RES J. Am. Chem. Soc. LANGMUIR MACROMOLECULES Mol. Pharmaceutics Nano Lett. Org. Lett. ORG PROCESS RES DEV ORGANOMETALLICS J. Org. Chem. J. Phys. Chem. J. Phys. Chem. A J. Phys. Chem. B J. Phys. Chem. C J. Phys. Chem. Lett. Analyst Anal. Methods Biomater. Sci. Catal. Sci. Technol. Chem. Commun. Chem. Soc. Rev. CHEM EDUC RES PRACT CRYSTENGCOMM Dalton Trans. Energy Environ. Sci. ENVIRON SCI-NANO ENVIRON SCI-PROC IMP ENVIRON SCI-WAT RES Faraday Discuss. Food Funct. Green Chem. Inorg. Chem. Front. Integr. Biol. J. Anal. At. Spectrom. J. Mater. Chem. A J. Mater. Chem. B J. Mater. Chem. C Lab Chip Mater. Chem. Front. Mater. Horiz. MEDCHEMCOMM Metallomics Mol. Biosyst. Mol. Syst. Des. Eng. Nanoscale Nanoscale Horiz. Nat. Prod. Rep. New J. Chem. Org. Biomol. Chem. Org. Chem. Front. PHOTOCH PHOTOBIO SCI PCCP Polym. Chem.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1