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 $mathbf {(151pm 2)}$ kcps at the activity of 40.65 kBq/mL, a sensitivity of $mathbf {(55.24pm 0.05)}$ 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 [ $mathbf {^{18}}text{F}$ ]-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 [ $mathbf {^{18}}text{F}$ ]-Florbetapir.
{"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}
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.
低计数正电子发射断层扫描（PET）成像是降低 PET 辐射风险的有效方法，但代价是低信噪比。我们的研究旨在以无监督模式对低计数 PET 图像进行去噪，因为主流方法依赖于配对数据，而配对数据在临床实践中并不总是可行的。考虑到扩散概率模型的强大生成能力，我们采用了扩散概率模型。我们的模型由两个阶段组成。在训练阶段，我们通过证据下限（ELBO）优化学习分数函数网络。在采样阶段，利用训练好的分数函数和低计数图像，在两种手工条件下生成相应的高计数图像。一种是基于潜空间的还原，另一种是基于潜空间的噪声插入。因此，我们的模型被命名为双向条件扩散概率模型（BC-DPM）。我们利用 Zubal 模型和真实病人的全身数据来评估我们的模型。实验表明，与几种传统的和最近提出的基于学习的方法相比，我们的模型在定性和定量方面都取得了更好的性能。
{"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}
Pub Date : 2024-01-11DOI: 10.1109/TRPMS.2024.3352983
Jorge Cabello;Michael T. Jurkiewicz;Andrea Andrade;Tammie L. S. Benzinger;Hongyu An;Udunna C. Anazodo
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– $2.3times $ 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.
与标准临床有序子集期望最大化（OSEM）图像质量相比，磁共振成像引导（MRIg）正电子发射断层扫描（PET）重建有可能减少噪声并提高空间分辨率。然而，为了调整所需的图像质量，通常需要手动调整测量数据和先验信息之间的平衡。这项研究提出了一种自适应方法，利用最大后验（MAP）图像重建技术，自动控制磁共振成像（MRI）信息对 PET 发射数据的影响，对各种计数具有鲁棒性。该方法在使用[18F]-FDG、[18F]-Florbetapir和[11C]-PiB的不同静态脑PET数据集上进行了评估，这些数据集是在PET/MRI同步扫描仪和PET/CT扫描仪上获得的，随后进行了MRI扫描。对灰质和白质的噪声进行了广泛的统计测量。此外，还分析了不同皮质和皮质下脑区在不同示踪剂摄取水平和不同计数水平下的噪声和量化准确性。结果表明，与 OSEM 相比，MRI 引导的 MAP PET（MRIg-MAP）重建在噪声和空间分辨率方面的图像质量得到了持续改善。此外，研究还表明，与OSEM相比，使用MRIg-MAP重建可将收集到的计数数量减少约1.6-2.3倍，而不会显著增加噪声，无论是通过减少扫描时间还是注射活性都是如此。总之，我们提出了一种新方法来适应性地平衡MRIg-MAP重建中解剖信息对发射数据的影响，与OSEM相比，该方法在不同放射性核素、不同计数水平下的图像质量都有所改善，并且适用于同步和顺序PET-MRI扫描。
{"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}
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 $alpha $ -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 $alpha $ -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.
{"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}
Pub Date : 2024-01-04DOI: 10.1109/TRPMS.2024.3349571
Kolawole Adesina;Ta-Chun Lin;Yue-Wern Huang;Marek Locmelis;Daoru Han
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.
{"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}
Pub Date : 2024-01-04DOI: 10.1109/TRPMS.2024.3349563
A. Sarno;R. M. Tucciariello;M. E. Fantacci;A. C. Traino;C. Valero;M. Stasi
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.
在测试 X 射线乳腺成像设备时，利用患者数字模型和模拟设备进行的模拟临床试验是一种替代昂贵而漫长的患者群体临床试验的方法。在这项工作中，我们模拟了作为 X 射线吸收器的线性响应 a-Se 探测器，忽略了一些物理过程，如电孔跟踪和热噪声。为了将模拟图像的特性调整为临床扫描仪的特性，我们在临床乳腺 X 射线照相设备上测量了探测器响应曲线、调制传递函数（MTF）和归一化噪声功率谱（NNPS）。为了定义一个合适的模型来修改模拟图像，并获得真实的像素值、噪声和空间分辨率，我们通过定制的蒙特卡洛代码在实验室中复制了相同的测试。所提出的方法使模拟图像中 NNPS 的斜率和幅度恢复到临床扫描仪上评估的曲线。同样，所提出的在模拟图像中调整噪声和空间分辨率的策略使在定制模型上评估的对比度-噪声比（CNR）与测量图像中的对比度-噪声比绝对值相差不到 16%。
{"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}
Pub Date : 2024-01-02DOI: 10.1109/TRPMS.2023.3342597
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Pub Date : 2024-01-02DOI: 10.1109/TRPMS.2023.3342599
{"title":"IEEE Transactions on Radiation and Plasma Medical Sciences Publication Information","authors":"","doi":"10.1109/TRPMS.2023.3342599","DOIUrl":"https://doi.org/10.1109/TRPMS.2023.3342599","url":null,"abstract":"","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10379474","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139081285","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}
Low-dose emission tomography (ET) plays a crucial role in medical imaging, enabling the acquisition of functional information for various biological processes while minimizing the patient dose. However, the inherent randomness in the photon counting process is a source of noise which is amplified in low-dose ET. This review article provides an overview of existing post-processing techniques, with an emphasis on deep neural network (NN) approaches. Furthermore, we explore future directions in the field of NN-based low-dose ET. This comprehensive examination sheds light on the potential of deep learning in enhancing the quality and resolution of low-dose ET images, ultimately advancing the field of medical imaging.
低剂量发射断层扫描（ET）在医学成像中起着至关重要的作用，它能获取各种生物过程的功能信息，同时最大限度地减少病人的剂量。然而，光子计数过程中固有的随机性是噪声的来源之一，而低剂量 ET 会放大这种噪声。这篇综述文章概述了现有的后处理技术，重点介绍了深度神经网络 (NN) 方法。此外，我们还探讨了基于 NN 的低剂量 ET 领域的未来发展方向。这一全面研究揭示了深度学习在提高低剂量 ET 图像质量和分辨率方面的潜力，最终推动医学成像领域的发展。
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Pub Date : 2023-12-27DOI: 10.1109/TRPMS.2023.3347602
Jiale Wang;Rui Guo;Ying Miao;Song Xue;Yu Zhang;Kuangyu Shi;Guoyan Zheng;Biao Li
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.
深度学习模型通过从相应的低剂量（LD）图像中估计全剂量（FD）图像，在减少低剂量（LD）正电子发射断层扫描（PET）图像噪声方面显示出巨大的潜力。然而，当这些模型在来自源扫描仪的成对 LD-FD PET 图像上进行训练时，由于一种称为 "域漂移 "的现象，当应用到来自目标扫描仪的 LD PET 图像时，这些模型不能很好地泛化。在这项研究中，我们提出了一种跨扫描仪 LD PET 图像降噪方法。该方法通过一个自组装框架来实现，该框架使用数量有限的配对 LD-FD PET 图像和大量来自目标扫描仪的 LD PET 图像。自组装框架利用两台扫描仪的配对二维切片来学习回归模型。此外，它还在目标扫描仪的 LD PET 图像上加入了一致性损失，以增强模型的泛化能力。我们在三个数据集上进行了实验，这三个数据集分别来自三个不同的扫描仪，包括 GE Discovery MI（DMI）扫描仪、Siemens Biograph Vision 450（Vision）扫描仪和 UI uMI 780（uMI）扫描仪。综合实验结果证明了我们方法的通用能力。
{"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}
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