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":"8 3","pages":"263-268"},"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}
{"title":"IEEE Transactions on Radiation and Plasma Medical Sciences Information for Authors","authors":"","doi":"10.1109/TRPMS.2023.3342597","DOIUrl":"https://doi.org/10.1109/TRPMS.2023.3342597","url":null,"abstract":"","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"8 1","pages":"C3-C3"},"PeriodicalIF":4.4,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10379498","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139081258","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}
{"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":"8 1","pages":"C2-C2"},"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}
{"title":"A Review on Low-Dose Emission Tomography Post-Reconstruction Denoising With Neural Network Approaches","authors":"Alexandre Bousse;Venkata Sai Sundar Kandarpa;Kuangyu Shi;Kuang Gong;Jae Sung Lee;Chi Liu;Dimitris Visvikis","doi":"10.1109/TRPMS.2023.3349194","DOIUrl":"10.1109/TRPMS.2023.3349194","url":null,"abstract":"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.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"8 4","pages":"333-347"},"PeriodicalIF":4.4,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10379513","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139138824","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}
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":"8 4","pages":"391-401"},"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}
{"title":"A Scalable Dynamic TOT Circuit for a 100 ps TOF-PET Detector Design to Improve Energy Linearity and Dynamic Range","authors":"Shirin Pourashraf;Joshua W. Cates;Craig S. Levin","doi":"10.1109/TRPMS.2023.3344399","DOIUrl":"https://doi.org/10.1109/TRPMS.2023.3344399","url":null,"abstract":"This article focuses on adapting linearization strategies for annihilation photon energy measurement for a time-of-flight (TOF) positron emission tomography (PET) system that achieves \u0000<inline-formula> <tex-math>$sim 100$ </tex-math></inline-formula>\u0000 picosecond (ps) full-width at half maximum (FWHM) coincidence time resolution (CTR). We have adapted the method of dynamic TOT (DynTOT) for our scalable TOF-PET detector readout electronics to linearize the energy spectra while maintaining \u0000<inline-formula> <tex-math>$sim 100$ </tex-math></inline-formula>\u0000 ps FWHM CTR. The linear response of the resulting DynTOT circuit facilitates improved energy performance compared with conventional time-over-threshold (TOT). Our detector design has the capability to position the 3-D coordinates of one or more 511-keV photon interactions. To facilitate this goal, DynTOT’s linearity across the entire energy range enables accurate measurement of low-energy interactions that is required for more accurate positioning of intercrystal scatter events. This DynTOT block is implemented by off-the-shelf discrete components and consumes only 11 mW power per detector layer unit design comprising 24:1 multiplexed energy and timing channels. We first validated the performance of DynTOT using single \u0000<inline-formula> <tex-math>$3times 3times10$ </tex-math></inline-formula>\u0000 mm3 LGSO scintillation crystals side-coupled to arrays of three \u0000<inline-formula> <tex-math>$3times3$ </tex-math></inline-formula>\u0000 mm2 SiPMs which achieved 511-keV photopeak energy resolutions of 13.6 ± 0.4%, 13.0 ± 0.8%, and 17.1 ± 0.6% for conventional pulse height, DynTOT, and conventional TOT methods, respectively. Then, we stretched by roughly 7-fold the DynTOT digital pulses (energy) generated from side-coupling \u0000<inline-formula> <tex-math>$2times4$ </tex-math></inline-formula>\u0000 array of \u0000<inline-formula> <tex-math>$3times 3times10$ </tex-math></inline-formula>\u0000 mm3 crystals to 24 SiPMs, and achieved 511-keV photopeak energy resolutions of 11.8 ± 0.7% with a dynamic range from less than 60 to 1274 keV, making that suitable for methods of accurate 3-D positioning of intercrystal-scatter interactions. Moreover, CTR with a highly multiplexed timing circuit was measured using these extended DynTOT pulses for energy gating, resulting in an average 108 ± 1.3 ps FWHM CTR.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"8 3","pages":"237-247"},"PeriodicalIF":4.4,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140031610","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}
Fellype do Nascimento;Aline da Graça Sampaio;Noala Vicensoto Moreira Milhan;Aline Vidal Lacerda Gontijo;Philipp Mattern;Torsten Gerling;Eric Robert;Cristiane Yumi Koga-Ito;Konstantin Georgiev Kostov
{"title":"A Low Cost, Flexible Atmospheric Pressure Plasma Jet Device With Good Antimicrobial Efficiency","authors":"Fellype do Nascimento;Aline da Graça Sampaio;Noala Vicensoto Moreira Milhan;Aline Vidal Lacerda Gontijo;Philipp Mattern;Torsten Gerling;Eric Robert;Cristiane Yumi Koga-Ito;Konstantin Georgiev Kostov","doi":"10.1109/TRPMS.2023.3342709","DOIUrl":"10.1109/TRPMS.2023.3342709","url":null,"abstract":"Plasma sources suitable to generate low-temperature plasmas has been fundamental for the advances in plasma medicine. In this research field, plasma sources must comply with stringent conditions for clinical applications. The main requirement to be met is the patient and operator’s safety and the ethical requirement of effectivity, which encompasses the electrical regulations, potential device toxicity, and effectiveness in relation to the desired treatment. All these issues are addressed by the German prestandard DIN SPEC 91315:2014–06 (DINSpec), which deals with the safety limits, risk assessment, and biological efficacy of plasma sources aimed for medical applications. In this work, a low cost, user-friendly, and flexible atmospheric pressure plasma jet (APPJ) device was characterized following the DINSpec guidelines. The device, which is still under development, proved to be safe for medical applications. It is capable of producing an APPJ with low patient leakage current and ultraviolet emission, gas temperature lower than 40 °C, production of harmful gases within the safety limits and low cytotoxicity. The most differentiating feature is that the device presented good antimicrobial efficacy even operating at frequency of the order of just a few hundred Hz, a value below that of most devices reported in the literature.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"8 3","pages":"307-322"},"PeriodicalIF":4.4,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139310856","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}
{"title":"CT Image Denoising and Deblurring With Deep Learning: Current Status and Perspectives","authors":"Yiming Lei;Chuang Niu;Junping Zhang;Ge Wang;Hongming Shan","doi":"10.1109/TRPMS.2023.3341903","DOIUrl":"https://doi.org/10.1109/TRPMS.2023.3341903","url":null,"abstract":"This article reviews the deep learning methods for computed tomography image denoising and deblurring separately and simultaneously. Then, we discuss promising directions in this field, such as a combination with large-scale pretrained models and large language models. Currently, deep learning is revolutionizing medical imaging in a data-driven manner. With rapidly evolving learning paradigms, related algorithms and models are making rapid progress toward clinical applications.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"8 2","pages":"153-172"},"PeriodicalIF":4.4,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139676142","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}
{"title":"Rotational Augmented Noise2Inverse for Low-Dose Computed Tomography Reconstruction","authors":"Hang Xu;Alessandro Perelli","doi":"10.1109/TRPMS.2023.3340955","DOIUrl":"10.1109/TRPMS.2023.3340955","url":null,"abstract":"In this work, we present a novel self-supervised method for low-dose computed tomography (LDCT) reconstruction. Reducing the radiation dose to patients during a computed tomography (CT) scan is a crucial challenge since the quality of the reconstruction highly degrades because of low photons or limited measurements. Supervised deep learning DL methods have shown the ability to remove noise in images but require accurate ground truth which can be obtained only by performing additional high-radiation CT scans. Therefore, we propose a novel self-supervised framework for LDCT, in which ground truth is not required for training the convolutional neural network (CNN). Based on the noise2inverse (N2I) method, we enforce in the training loss the equivariant property of rotation transformation, which is induced by the CT imaging system, to improve the quality of the CT image in a lower dose. Numerical and experimental results show that the reconstruction accuracy of N2I with sparse views is degrading while the proposed rotational augmented noise2inverse (RAN2I) method keeps better-image quality over a different range of sampling angles. Finally, the quantitative results demonstrate that RAN2I achieves higher-image quality compared to N2I, and experimental results of RAN2I on real projection data show comparable performance to supervised learning.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"8 2","pages":"208-221"},"PeriodicalIF":4.4,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138959144","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}
{"title":"Temperature Control Strategies of Atmospheric Plasma Jet for Tissue Treatment","authors":"Bingkai Wang;Xu Yan;Zilan Xiong","doi":"10.1109/TRPMS.2023.3340154","DOIUrl":"https://doi.org/10.1109/TRPMS.2023.3340154","url":null,"abstract":"Besides the charged particles and neutral reactive species, the temperature effect is another significant issue needs to concern during the plasma treatment of biological tissue, which has effects on therapeutic efficacy and the risk of burns. Due to the influence of multiple factors on the temperature effect, it’s a complex nonlinear problem. In this study, temperature rise and distribution uniformity under different parameters and moving trajectories on porcine skin were investigated, and then a surface temperature control strategy was proposed. A 3-D electric motor control platform was constructed for the jet moving during the treatment. First, the effects of factors, such as distance, voltage, and flow rate on temperature variation over porcine skin surface, were analyzed, and the trends of temperature variation under single-factor influence were summarized. Then, the temperature distribution of fixed-point treatment and the temperature superposition effect on the tissue surface under different trajectories were explored, and a trajectory scheme for achieving homogeneous temperature distribution was proposed. Finally, a closed-loop control model was designed to achieve the control objectives of constant temperature holding over a certain surface area and resistance to high-temperature interference in real time. This control scheme also has reference significance for other surface treatments such as material processing.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"8 1","pages":"105-112"},"PeriodicalIF":4.4,"publicationDate":"2023-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139081229","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}