ABSTRACT
BACKGROUND: PET scan stands as a valuable diagnostic tool in nuclear medicine, enabling the observation of metabolic and physiological changes at a molecular level. However, PET scans have a number of drawbacks, such as poor spatial resolution, noisy images, scattered radiation, artifacts, and radiation exposure. These challenges demonstrate the need for optimization in image processing techniques. OBJECTIVES: Our objective is to identify the evolving trends and impacts of publication in this field, as well as the most productive and influential countries, institutions, authors, themes, and articles. METHODS: A bibliometric study was conducted using a comprehensive query string such as "positron emission tomography" AND "image processing" AND optimization to retrieve 1,783 publications from 1981 to 2022 found in the Scopus database related to this field of study. RESULTS: The findings revealed that the most influential country, institution, and authors are from the USA, and the most prevalent theme is TOF PET image reconstruction. CONCLUSION: The increasing trend in publication in the field of optimization of image processing in PET scans would address the challenges in PET scan by reducing radiation exposure, faster scanning speed, as well as enhancing lesion identification.
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BACKGROUND: For almost three decades, computed tomography (CT) has been extensively used in medical diagnosis, which led researchers to conduct linking of CT dose exposure with image quality. METHODS: In this study, a systematic review and a meta-analysis study were conducted on CT phantom for resolution study especially based on the low contrast detectability (LCD). Furthermore, the association between the CT parameter such as tube voltage and the type of reconstruction algorithm, the amount of phantom scanning affecting the image quality and the exposure dose were also investigated in this study. We utilize PubMed, ScienceDirect, Google Scholar and Scopus databases to search related published articles from the year 2011 until 2020. The notable keywords comprise "computed tomography", "CT phantom", and "low contrast detectability". Of 52 articles, 20 articles are within the inclusion criteria in this systematic review. RESULTS: The dichotomous outcomes were chosen to represent the results in terms of risk ratio as per meta-analysis study. Notably, the noise in iterative reconstruction (IR) reduced by 24%, 33% and 36% with the use of smooth, medium and sharp filters, respectively. Furthermore, adaptive iterative dose reduction (AIDR 3D) improved image quality and the visibility of smaller less dense objects compared to filtered back-projection. Most of the researchers used 120 kVp tube voltage to scan phantom for quality assurance study. CONCLUSION: Hence, optimizing primary factors such as tube potential reduces the dose exposure significantly, and the optimized IR technique could substantially reduce the radiation dose while maintaining the image quality.
Subject(s)
Algorithms , Tomography, X-Ray Computed , Humans , Radiation Dosage , Tomography, X-Ray Computed/methods , Phantoms, Imaging , Radiographic Image Interpretation, Computer-Assisted/methodsABSTRACT
Structural transformation and magnetic ordering interplays for emergence as well as suppression of superconductivity in 122-iron-based superconducting materials. Electron and hole doping play a vital role in structural transition and magnetism suppression and ultimately enhance the room pressure superconducting critical temperature of the compound. This work models the superconducting critical temperature of 122-iron-based superconductor using tetragonal to orthorhombic lattice (LAT) structural transformation during low-temperature cooling and ionic radii of the dopants as descriptors through hybridization of support vector regression (SVR) intelligent algorithm with particle swarm (PS) parameter optimization method. The developed PS-SVR-RAD model, which utilizes ionic radii (RAD) and the concentrations of dopants as descriptors, shows better performance over the developed PS-SVR-LAT model that employs lattice parameters emanated from structural transformation as descriptors. Using the root mean square error (RMSE), coefficient of correlation (CC) and mean absolute error as performance measuring criteria, the developed PS-SVR-RAD model performs better than the PS-SVR-LAT model with performance improvement of 15.28, 7.62 and 72.12%, on the basis of RMSE, CC and Mean Absolute Error (MAE), respectively. Among the merits of the developed PS-SVR-RAD model over the PS-SVR-LAT model is the possibility of electrons and holes doping from four different dopants, better performance and ease of model development at relatively low cost since the descriptors are easily fetched ionic radii. The developed intelligent models in this work would definitely facilitate quick and precise determination of critical transition temperature of 122-iron-based superconductor for desired applications at low cost with experimental stress circumvention.
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A rapid, sustainable, and ecologically sound approach is urgently needed for the production of semiconductor nanomaterials. CuSe nanoparticles (NPs) were synthesized via a microwave-assisted technique using CuCl2·2H2O and Na2SeO3 as the starting materials. The role of the irradiation time was considered as the primary concern to regulate the size and possibly the shape of the synthesized nanoparticles. A range of characterization techniques was used to elucidate the structural and optical properties of the fabricated nanoparticles, which included X-ray diffraction, energy-dispersive X-ray spectroscopy (EDX), atomic force microscopy, field emission scanning electron microscopy, Raman spectroscopy (Raman), UV-Visible diffuse reflectance spectroscopy (DRS), and photoluminescence spectroscopy (PL). The mean crystallite size of the CuSe hexagonal (Klockmannite) crystal structure increased from 21.35 to 99.85 nm with the increase in irradiation time. At the same time, the microstrain and dislocation density decreased from 7.90 × 10-4 to 1.560 × 10-4 and 4.68 × 10-2 to 1.00 × 10-2 nm-2, respectively. Three Raman vibrational bands attributed to CuSe NPs have been identified in the Raman spectrum. Irradiation time was also seen to play a critical role in the NP optical band gap during the synthesis. The decrease in the optical band gap from 1.85 to 1.60 eV is attributed to the increase in the crystallite size when the irradiation time was increased. At 400 nm excitation wavelength, a strong orange emission centered at 610 nm was observed from the PL measurement. The PL intensity is found to increase with an increase in irradiation time, which is attributed to the improvement in crystallinity at higher irradiation time. Therefore, the results obtained in this study could be of great benefit in the field of photonics, solar cells, and optoelectronic applications.
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YBa2Cu3O7-δ (Y-123) bulk superconductors with the addition of (0.0, 0.2, 0.4, 0.6, 0.8, and 1.0 wt.%) SnO2 nanoparticles were synthesised via a thermal treatment method. The influence of SnO2 addition on the superconducting properties by means of critical temperature, Tc, AC susceptibility, phase formation and microstructures, including its elemental composition analysis, were studied. Sharp superconducting transition, ∆Tc, and diamagnetic transition were obtained for all SnO2-added samples. It was observed that sample x = 0.4 with a Y-123 phase percentage of 95.8% gives the highest Tc, smallest ∆Tc, and the sharpest diamagnetic transition in the normalised susceptibility curves. The microstructure also showed an excess of Sn precipitates on the sample's surface at x = 0.8 and above. As such, the best superconducting properties were observed at x = 0.4 SnO2 addition inside the Y-123 host sample.
