IEEE Transactions on Radiation and Plasma Medical Sciences最新文献_第7页

Development and Evaluation of a Portable MVT-Based All-Digital Helmet PET Scanner 开发和评估基于 MVT 的便携式全数字头盔 PET 扫描仪

IF 4.4

IEEE Transactions on Radiation and Plasma Medical Sciences Pub Date : 2024-01-23 DOI: 10.1109/TRPMS.2024.3357571

Feng Zhou;Nicola D’Ascenzo;Bo Zhang;Emanuele Antonecchia;Lei Fang;Li Ba;Min Zhang;Xiaohua Zhu;Qiong Liu;Jiazuan Ni;Giacomo Frati;Michael Kreissl;Xun Chen;Jiang Wu;Qingguo Xie

{"title":"Development and Evaluation of a Portable MVT-Based All-Digital Helmet PET Scanner","authors":"Feng Zhou;Nicola D’Ascenzo;Bo Zhang;Emanuele Antonecchia;Lei Fang;Li Ba;Min Zhang;Xiaohua Zhu;Qiong Liu;Jiazuan Ni;Giacomo Frati;Michael Kreissl;Xun Chen;Jiang Wu;Qingguo Xie","doi":"10.1109/TRPMS.2024.3357571","DOIUrl":"https://doi.org/10.1109/TRPMS.2024.3357571","url":null,"abstract":"Novel design solutions for dedicated portable brain positron emission tomography systems with improved performance facilitate emergency and interventional image-guided surgery as well as advanced diagnostics of clinically impaired patients with neurodegenerative diseases. We report a novel portable MVT-based All-Digital helmet PET system with a hemispherical detector arrangement based on the Multi Voltage Threshold technology. It has a transverse and axial field of view (FOV) of 200 and 124 mm, respectively. It allows to scan subjects in a standing, sitting, and lying position. We evaluated the performance of the system according to NEMA standards. The scanner exhibits a noise equivalent count rate peak of \u0000<inline-formula> <tex-math>$mathbf {(151pm 2)}$ </tex-math></inline-formula>\u0000 kcps at the activity of 40.65 kBq/mL, a sensitivity of \u0000<inline-formula> <tex-math>$mathbf {(55.24pm 0.05)}$ </tex-math></inline-formula>\u0000 cps/kBq, and a spatial resolution at the center of the FOV of approximately 3.3 mm (FWHM), when using the filtered back projection algorithm. For a mini Derenzo phantom, rods of 2.0-mm diameter can be clearly separated. Time-dynamic [\u0000<inline-formula> <tex-math>$mathbf {^{18}}text{F}$ </tex-math></inline-formula>\u0000]-Fluorodeoxyglucose human brain imaging was performed, showing the distinctive traits of cortex and thalamus uptake, as well as of the arterial and venous flow with 30 s time frames. We finally verified the usability of the device in the diagnostics of Alzheimer’s Disease by imaging human subjects with [\u0000<inline-formula> <tex-math>$mathbf {^{18}}text{F}$ </tex-math></inline-formula>\u0000]-Florbetapir.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140031603","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

Bidirectional Condition Diffusion Probabilistic Models for PET Image Denoising 用于 PET 图像去噪的双向条件扩散概率模型

IF 4.4

IEEE Transactions on Radiation and Plasma Medical Sciences Pub Date : 2024-01-17 DOI: 10.1109/TRPMS.2024.3355247

Chenyu Shen;Changjun Tie;Ziyuan Yang;Na Zhang;Yi Zhang

{"title":"Bidirectional Condition Diffusion Probabilistic Models for PET Image Denoising","authors":"Chenyu Shen;Changjun Tie;Ziyuan Yang;Na Zhang;Yi Zhang","doi":"10.1109/TRPMS.2024.3355247","DOIUrl":"https://doi.org/10.1109/TRPMS.2024.3355247","url":null,"abstract":"Low-count positron emission tomography (PET) imaging is an effective way to reduce the radiation risk of PET at the cost of a low-signal-to-noise ratio. Our study aims to denoise low-count PET images in an unsupervised mode since the mainstream methods rely on paired data, which is not always feasible in clinical practice. We adopt the diffusion probabilistic model in consideration of its strong generation ability. Our model consists of two stages. In the training stage, we learn a score function network via evidence lower-bound (ELBO) optimization. In the sampling stage, the trained score function and low-count image are employed to generate the corresponding high-count image under two handcrafted conditions. One is based on restoration in latent space, and the other is based on noise insertion in latent space. Thus, our model is named the bidirectional condition diffusion probabilistic model (BC-DPM). The Zubal phantom and real patient whole-body data are utilized to evaluate our model. The experiments show that our model achieves better performance in both qualitative and quantitative respects compared to several traditional and recently proposed learning-based methods.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10401984","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140342742","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

Evaluation of an MRI-Guided PET Image Reconstruction Approach With Adaptive Penalization Strength 评估具有自适应惩罚强度的 MRI 引导 PET 图像重建方法

IF 4.4

IEEE Transactions on Radiation and Plasma Medical Sciences Pub Date : 2024-01-11 DOI: 10.1109/TRPMS.2024.3352983

Jorge Cabello;Michael T. Jurkiewicz;Andrea Andrade;Tammie L. S. Benzinger;Hongyu An;Udunna C. Anazodo

{"title":"Evaluation of an MRI-Guided PET Image Reconstruction Approach With Adaptive Penalization Strength","authors":"Jorge Cabello;Michael T. Jurkiewicz;Andrea Andrade;Tammie L. S. Benzinger;Hongyu An;Udunna C. Anazodo","doi":"10.1109/TRPMS.2024.3352983","DOIUrl":"https://doi.org/10.1109/TRPMS.2024.3352983","url":null,"abstract":"MRI-guided (MRIg) positron emission tomography (PET) reconstruction can potentially reduce noise and increase spatial resolution compared to standard clinical ordered-subsets expectation-maximization (OSEM) image quality. However, to adjust for the desired image quality, the balance between measured data and prior information usually requires manual tuning. This work presents an adaptive method to automatically control the influence of the magnetic resonance imaging (MRI) information on the PET emission data using maximum a posteriori (MAP) image reconstruction, robust against a wide range of counts. The method was evaluated on different static brain PET datasets using [18F]-FDG, [18F]-Florbetapir and [11C]-PiB, acquired in a simultaneous PET/MRI scanner and a PET/CT scanner, followed by an MRI scan. Noise in gray and white matter was measured for a wide range of statistics. Furthermore, noise and quantification accuracy were analyzed in different cortical and subcortical brain regions with different levels of tracer uptake, and at different levels of counts. Results demonstrated consistent improved image quality in terms of noise and spatial resolution with MRI-guided MAP PET (MRIg-MAP) reconstruction compared to OSEM. Additionally, it was shown that the number of collected counts could be reduced by ~1.6–\u0000<inline-formula> <tex-math>$2.3times $ </tex-math></inline-formula>\u0000 using MRIg-MAP reconstruction compared to OSEM, without increasing the noise significantly, either by reducing the scan time or injected activity. In conclusion, we presented a novel method to adaptively balance the influence of the anatomical information on the emission data for MRIg-MAP reconstruction, which showed image quality improvements compared to OSEM for different radiotracers, at different levels of counts, and applicable to simultaneous and sequential PET-MRI scans.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140031660","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

Infrared Spectroscopy for Tracking Changes in Proteins Secondary Structure and Lipids During Wound Healing Process of Diabetic Mice After Treated by a Cold Atmospheric Plasma Jet 利用红外光谱追踪糖尿病小鼠伤口愈合过程中蛋白质二级结构和脂质在冷大气等离子体射流作用下的变化

IF 4.4

IEEE Transactions on Radiation and Plasma Medical Sciences Pub Date : 2024-01-09 DOI: 10.1109/TRPMS.2024.3351743

Qingdong Wang;Qun Zhou;Lu-Xiang Zhao;Tao He;Xinyi Chen;Na Zhang;Hao Chen;Heng-Xin Zhao;Yongjian Li;Yu Zhang;He-Ping Li

{"title":"Infrared Spectroscopy for Tracking Changes in Proteins Secondary Structure and Lipids During Wound Healing Process of Diabetic Mice After Treated by a Cold Atmospheric Plasma Jet","authors":"Qingdong Wang;Qun Zhou;Lu-Xiang Zhao;Tao He;Xinyi Chen;Na Zhang;Hao Chen;Heng-Xin Zhao;Yongjian Li;Yu Zhang;He-Ping Li","doi":"10.1109/TRPMS.2024.3351743","DOIUrl":"https://doi.org/10.1109/TRPMS.2024.3351743","url":null,"abstract":"The attenuated total reflection Fourier transform infrared spectroscopy attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FT-IR) detection was used to investigate the mechanisms of cold atmospheric plasma (CAP) treatment in wound healing. The peaks of ester carbonyl and \u0000<inline-formula> <tex-math>$alpha $ </tex-math></inline-formula>\u0000-helix in proteins, serving as the spectral fingerprints in the original infrared spectra and their second derivative spectra, of the wound samples were analyzed. The experimental results showed that the CAP treatment resulted in the reduction of the ester carbonyl contents, and the increase of the contents of \u0000<inline-formula> <tex-math>$alpha $ </tex-math></inline-formula>\u0000-helix in the proteins. This indicates that the CAP treatment accelerated the lipid metabolism to provide required energy for the protein production, which was also supported by the fact that the fibrin deposition in the wounds was more obvious in the plasma group than that in the control group.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140031568","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

A Review of Dielectric Barrier Discharge Cold Atmospheric Plasma for Surface Sterilization and Decontamination 用于表面消毒和去污的介质阻挡放电冷大气等离子体综述

IF 4.4

IEEE Transactions on Radiation and Plasma Medical Sciences Pub Date : 2024-01-04 DOI: 10.1109/TRPMS.2024.3349571

Kolawole Adesina;Ta-Chun Lin;Yue-Wern Huang;Marek Locmelis;Daoru Han

{"title":"A Review of Dielectric Barrier Discharge Cold Atmospheric Plasma for Surface Sterilization and Decontamination","authors":"Kolawole Adesina;Ta-Chun Lin;Yue-Wern Huang;Marek Locmelis;Daoru Han","doi":"10.1109/TRPMS.2024.3349571","DOIUrl":"https://doi.org/10.1109/TRPMS.2024.3349571","url":null,"abstract":"Numerous investigations have shown that nonequilibrium discharges at atmospheric pressure, also known as “cold atmospheric plasma” (CAP), are efficient to remove biological contaminants from surfaces of a variety of materials. Recently, CAP has quickly advanced as a technique for microbial cleaning, wound healing, and cancer therapy due to the chemical and biologically active radicals it produces, known collectively as reactive oxygen and nitrogen species (RONS). This article reviews studies pertaining to one of the atmospheric plasma sources known as dielectric barrier discharge (DBD) which has been widely used to treat materials with microbes for sterilization, disinfection, and decontamination purposes. To advance research in CAP applications, this review discusses various types and configurations of barrier discharge, the role played by reactive species and other DBD-CAP agents leading to its antimicrobial efficacy, a few collection of DBD-CAP past studies specifically on surface, and emerging applications of DBD-CAP technology. Our review showed that nonthermal/equilibrium plasma generated from DBD could sterilize or disinfect surface of materials without causing any thermal damage or environmental contamination.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140031647","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

A Model for a Linear a-Se Detector in Simulated X-Ray Breast Imaging With Monte Carlo Software 利用蒙特卡洛软件模拟 X 射线乳腺成像中的线性 a-Se 探测器模型

IF 4.4

IEEE Transactions on Radiation and Plasma Medical Sciences Pub Date : 2024-01-04 DOI: 10.1109/TRPMS.2024.3349563

A. Sarno;R. M. Tucciariello;M. E. Fantacci;A. C. Traino;C. Valero;M. Stasi

{"title":"A Model for a Linear a-Se Detector in Simulated X-Ray Breast Imaging With Monte Carlo Software","authors":"A. Sarno;R. M. Tucciariello;M. E. Fantacci;A. C. Traino;C. Valero;M. Stasi","doi":"10.1109/TRPMS.2024.3349563","DOIUrl":"https://doi.org/10.1109/TRPMS.2024.3349563","url":null,"abstract":"In-silico clinical trials with digital patient models and simulated devices are an alternative to expensive and long clinical trials on patient population for testing X-ray breast imaging apparatuses. In this work, we simulated a linear-response a-Se detector as an X-ray absorber, neglecting some physical processes, such as electro-hole tracking and thermal noise. In order to tune characteristics of the simulated images toward those of the clinical scanners, the detector response curve, modulation transfer function (MTF), and normalized noise power spectrum (NNPS) were measured on a clinical mammographic unit. The same tests were replicated in-silico via a custom-made Monte Carlo code in order to define a suitable model to modify simulated images and to have realistic pixel values, noise, and spatial resolution. The proposed approach resulted to restore the slope and the magnitude of the NNPS in simulated images toward curves evaluated on a clinical scanner. Similarly, the proposed strategy for tuning noise and spatial resolution in simulated images led to a contrast-to-noise ratio (CNR) evaluated on a custom-made phantom which differed from those in measured images less than 16% in absolute value.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10380795","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140031665","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

IEEE Transactions on Radiation and Plasma Medical Sciences Information for Authors 电气和电子工程师学会《辐射与等离子体医学科学杂志》作者须知

IF 4.4

IEEE Transactions on Radiation and Plasma Medical Sciences Pub Date : 2024-01-02 DOI: 10.1109/TRPMS.2023.3342597

引用次数: 0

IEEE Transactions on Radiation and Plasma Medical Sciences Publication Information 电气和电子工程师学会辐射与等离子体医学科学杂志》（IEEE Transactions on Radiation and Plasma Medical Sciences）出版信息

IF 4.4

IEEE Transactions on Radiation and Plasma Medical Sciences Pub Date : 2024-01-02 DOI: 10.1109/TRPMS.2023.3342599

引用次数: 0

A Review on Low-Dose Emission Tomography Post-Reconstruction Denoising With Neural Network Approaches 利用神经网络方法对低剂量发射断层扫描重建后去噪的综述

IF 4.4

IEEE Transactions on Radiation and Plasma Medical Sciences Pub Date : 2024-01-02 DOI: 10.1109/TRPMS.2023.3349194

Alexandre Bousse;Venkata Sai Sundar Kandarpa;Kuangyu Shi;Kuang Gong;Jae Sung Lee;Chi Liu;Dimitris Visvikis

引用次数: 0

Cross-Scanner Low-Dose Brain-PET Image Noise Reduction With Self-Ensembling 利用自组装技术降低跨扫描仪低剂量脑 PET 图像噪声

IF 4.4

IEEE Transactions on Radiation and Plasma Medical Sciences Pub Date : 2023-12-27 DOI: 10.1109/TRPMS.2023.3347602

Jiale Wang;Rui Guo;Ying Miao;Song Xue;Yu Zhang;Kuangyu Shi;Guoyan Zheng;Biao Li

{"title":"Cross-Scanner Low-Dose Brain-PET Image Noise Reduction With Self-Ensembling","authors":"Jiale Wang;Rui Guo;Ying Miao;Song Xue;Yu Zhang;Kuangyu Shi;Guoyan Zheng;Biao Li","doi":"10.1109/TRPMS.2023.3347602","DOIUrl":"https://doi.org/10.1109/TRPMS.2023.3347602","url":null,"abstract":"Deep learning models have shown great potential in reducing low-dose (LD) positron emission tomography (PET) image noise by estimating full-dose (FD) images from the corresponding LD images. Those models, however, when trained on paired LD-FD PET images from a source scanner, fail to generalize well when applied to LD PET images from a target scanner, due to a phenomenon called “domain drift.” In this study, we present a method for cross-scanner LD PET image noise reduction. This is done via a self-ensembling framework using a limited number of paired LD-FD PET images and a large number of LD PET images from the target scanner. The self-ensembling framework leverages the paired 2-D slices from both scanners to learn a regression model. It additionally incorporates a consistency loss on the LD PET images from the target scanner to enhance the model’s generalization capability. We conduct experiments on three datasets, respectively, acquired from three different scanners, including a GE Discovery MI (DMI) scanner, a Siemens Biograph Vision 450 (Vision) scanner, and a UI uMI 780 (uMI) scanner. Results from our comprehensive experiments demonstrate the generalization capability of our method.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2023-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140342654","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