Article
Computer Science, Information Systems
Hao Yu, Nnubia Pascal Nnamdi, Aria Seo, Jinkyeong Park, Yunsik Son
Summary: The diaphragm plays a crucial role in respiration, and a novel approach using thoracic computed tomography scans has been introduced to assess diaphragm function in patients with COPD. This approach is highly accurate and beneficial in respiratory disorders, offering a quantitative evaluation of its effectiveness in detecting diaphragmatic dysfunction.
Article
Radiology, Nuclear Medicine & Medical Imaging
Mineka Sato, Yasutaka Ichikawa, Kensuke Domae, Kazuya Yoshikawa, Yoshinori Kanii, Akio Yamazaki, Naoki Nagasawa, Motonori Nagata, Masaki Ishida, Hajime Sakuma
Summary: Compared to hybrid iterative reconstruction (IR), deep learning image reconstruction (DLIR) improves vessel conspicuity, contrast-to-noise ratio (CNR), and lesion conspicuity of virtual monochromatic and iodine density images in abdominal contrast-enhanced dual-energy computed tomography (DECT).
EUROPEAN RADIOLOGY
(2022)
Review
Radiology, Nuclear Medicine & Medical Imaging
Norbert J. Pelc, David A. Chesler
Summary: This paper aims to describe the early introduction of CT imaging at Massachusetts General Hospital (MGH), with the installation of the first CT scanner in 1973, and the preceding CT research work and related accomplishments.
Article
Engineering, Multidisciplinary
Sophia B. Coban, William R. B. Lionheart, Philip J. Withers
Summary: The paper discusses the performance assessment of CT reconstruction algorithms and introduces a evaluation technique called physical quantification, which measures the features of the test object to assess the reconstruction efficacy. The study highlights the importance of choosing the optimal reconstruction strategy based on the features extracted from the scan.
MEASUREMENT SCIENCE AND TECHNOLOGY
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Le Cao, Xiang Liu, Tingting Qu, Yannan Cheng, Jianying Li, Yanan Li, Lihong Chen, Xinyi Niu, Qian Tian, Jianxin Guo
Summary: This study evaluated the use of thin slices and deep learning image reconstruction (DLIR) in contrast-enhanced abdominal CT. The results showed that DLIR significantly reduced image noise and improved image quality and diagnostic confidence.
EUROPEAN RADIOLOGY
(2023)
Article
Engineering, Biomedical
Genwei Ma, Xing Zhao, Yining Zhu, Huitao Zhang
Summary: This study proposes a novel lightweight block reconstruction network (LBRN) to address the issue of memory space in learning-based CT reconstruction. The network transforms the reconstruction operator into a deep neural network and consists of two main modules for filtering and back-projection. The first module decouples the relationship between the reconstructed image and the projection data, enabling the following block back-projection module to use a simplified block reconstruction strategy. The approach is trained end-to-end, working directly from raw projection data without relying on initial images.
PHYSICS IN MEDICINE AND BIOLOGY
(2022)
Article
Multidisciplinary Sciences
Shiwo Deng, Yining Zhu, Huitao Zhang, Qian Wang, Peiping Zhu, Kai Zhang, Peng Zhang
Summary: Material decomposition is an important application of computer tomography. A new method called PAMD-SART is developed for incorporating both phase and absorption information into the MD process, leading to superior noise suppression and accurate decomposition compared to traditional two-step methods. Numerical simulations and experiments show that PAMD-SART outperforms classical MD methods in terms of quantitative accuracy of material equivalent atomic number.
Article
Computer Science, Interdisciplinary Applications
Xi Tao, Yongbo Wang, Liyan Lin, Zixuan Hong, Jianhua Ma
Summary: The study trains DNN to reconstruct CT images from VVBP-Tensor, providing lossless information and preserving fine details. The learning strategy can be seen as a generalization of conventional methods and potentially inspire algorithm development. The VVBP-Tensor domain learning framework shows significant improvement over traditional image and projection-based learning frameworks.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2021)
Article
Optics
Zhen Guo, Jung Ki Song, George Barbastathis, Michael E. Glinsky, Courtenay T. Vaughan, Kurt W. Larson, Bradley K. Alpert, Zachary H. Levine
Summary: Researchers have developed a Physics-assisted Generative Adversarial Network (PGAN) algorithm for reconstruction in X-ray tomography. Compared to previous methods, PGAN combines known physics and learned prior to reduce photon requirement and achieve a given error rate by reducing projection angles.
Article
Radiology, Nuclear Medicine & Medical Imaging
Marta Ligero, Olivia Jordi-Ollero, Kinga Bernatowicz, Alonso Garcia-Ruiz, Eric Delgado-Munoz, David Leiva, Richard Mast, Cristina Suarez, Roser Sala-Llonch, Nahum Calvo, Manuel Escobar, Arturo Navarro-Martin, Guillermo Villacampa, Rodrigo Dienstmann, Raquel Perez-Lopez
Summary: The study aimed to identify CT-acquisition parameters affecting radiomics variability and develop a post-acquisition CT-image correction method to improve radiomics classification accuracy in phantom and clinical applications. Results showed that post-acquisition processing of CT images can reduce radiomics variability and improve classification accuracy.
EUROPEAN RADIOLOGY
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Hye Joo Park, Seo-Youn Choi, Ji Eun Lee, Sanghyeok Lim, Min Hee Lee, Boem Ha Yi, Jang Gyu Cha, Ji Hye Min, Bora Lee, Yunsub Jung
Summary: This study compared the image quality and radiation dose of a deep learning image reconstruction algorithm (DLIR) with iterative reconstruction (IR) and filtered back projection (FBP) at different tube voltages and tube currents. The results showed that DLIR significantly reduced noise and artifacts and improved overall image quality compared to FBP and hybrid IR. Despite the reduced image sharpness, low-dose CT with DLIR seemed to have a greater potential for dose optimization.
EUROPEAN RADIOLOGY
(2022)
Article
Computer Science, Interdisciplinary Applications
Wenjun Xia, Zexin Lu, Yongqiang Huang, Yan Liu, Hu Chen, Jiliu Zhou, Yi Zhang
Summary: This paper introduces a parameter-dependent framework that trains a reconstruction network with data from multiple alternative geometries and dose levels simultaneously, reducing extra training costs for multiple geometries and dose levels.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Emil Y. Sidky, Xiaochuan Pan
Summary: The purpose of this challenge is to find a deep-learning technique that can achieve the minimum root mean square error for sparse-view CT image reconstruction under ideal conditions. The challenge involves a 2D breast CT simulation and a large training set to train the networks. About 60 groups participated in the challenge, achieving significant improvement in reconstruction accuracy.
Article
Radiology, Nuclear Medicine & Medical Imaging
Mayank Patwari, Ralf Gutjahr, Rainer Raupach, Andreas Maier
Summary: In this study, a novel CT denoising framework is introduced, which employs bilateral filtering in both the projection and volume domains to remove noise. Two deep CNNs are used for parameter tuning and training via a reward network. The framework demonstrates excellent denoising performance and outperforms other deep CNN models. It does not introduce blurring or deep learning artifacts.
Article
Radiology, Nuclear Medicine & Medical Imaging
Jingyu Zhong, Lingyun Wang, Hailin Shen, Jianying Li, Wei Lu, Xiaomeng Shi, Yue Xing, Yangfan Hu, Xiang Ge, Defang Ding, Fuhua Yan, Lianjun Du, Weiwu Yao, Huan Zhang
Summary: This study compares the image quality, diagnostic acceptability, and lesion conspicuity of abdominal dual-energy CT (DECT) using deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction-V (Asir-V) at 50% blending (AV-50). DLIR-H showed significantly better image quality, diagnostic acceptability, and lesion conspicuity than AV-50 and DLIR-M. This suggests that DLIR-H can be safely recommended for routine low-keV VMI reconstruction in daily contrast-enhanced abdominal DECT.
EUROPEAN RADIOLOGY
(2023)
Article
Physics, Applied
L. Brombal, F. Arfelli, F. Brun, F. Longo, N. Poles, L. Rigon
Summary: Accurate simulation tools are important for the design and optimization of x-ray phase-contrast imaging setups. This study presents a practical implementation of x-ray phase-contrast in Geant4 and validates the simulation results against theoretical predictions.
JOURNAL OF PHYSICS D-APPLIED PHYSICS
(2022)
Article
Electrochemistry
Francesca Rossi, Lucia Mancini, Ivonne Sgura, Marco Boniardi, Andrea Casaroli, Alexander Peter Kao, Benedetto Bozzini
Summary: This work addresses the methodological challenge of rationalizing symmetric-cell cycling data through experiment replication, mathematical modelling, and tomographic imaging from a materials-science perspective. It reveals an unexpected joint effect of tetrabutylammonium bromide and current density on passivation time and provides a rational explanation based on precipitate morphology using tomography.
Article
Instruments & Instrumentation
Alessia Nava, Patrick Mahoney, Luca Bondioli, Alfredo Coppa, Emanuela Cristiani, Luciano Fattore, Gina McFarlane, Diego Dreossi, Lucia Mancini
Summary: This study compares the results of physical and virtual thin sections of human deciduous incisors as well as the enamel secretion rates obtained from virtual and physical thin sections. The virtual sections showed good visibility of enamel microstructures, comparable to physical sections. The highest resolution virtual sections produced secretion rates that matched physical sections, while the lowest resolution sections produced higher rates.
JOURNAL OF SYNCHROTRON RADIATION
(2022)
Article
Audiology & Speech-Language Pathology
Fergio Sismono, Marc Leblans, Lucia Mancini, Alessio Veneziano, Franco Zanini, Joris Dirckx, Anja Bernaerts, Bert de Foer, Erwin Offeciers, Andrzej Zarowski
Summary: The study developed and validated a robust and efficient computerized algorithm for three-dimensional localization of cochlear implant electrode contacts using modern clinical cone-beam computed tomography (CBCT). The accuracy of the algorithm was validated in a temporal bone study by comparing it with synchrotron-radiation (SR) micro-computed tomography (mu CT). The algorithm showed accurate localization and had potential implications for optimizing cochlear implant surgery.
Article
Geochemistry & Geophysics
Federico Casetta, Andrea L. Rizzo, Barbara Faccini, Theodoros Ntaflos, Rainer Abart, Gabriele Lanzafame, Luca Faccincani, Lucia Mancini, Pier Paolo Giacomoni, Massimo Coltorti
Summary: The study investigates the storage of CO2 in the Sub-Continental Lithospheric Mantle in northern Victoria Land, Antarctica, using petrology, fluid inclusions, and microstructural characterization. The results show that CO2 is mostly stored in mineral-hosted fluid inclusions and inter-granular fluids. The distribution of CO2 varies depending on the lithology, with higher concentrations in orthopyroxene and clinopyroxene-hosted fluid inclusions. This research provides insights into the geodynamic processes of the Earth.
Article
Multidisciplinary Sciences
Federico Lugli, Alessia Nava, Rita Sorrentino, Antonino Vazzana, Eugenio Bortolini, Gregorio Oxilia, Sara Silvestrini, Nicola Nannini, Luca Bondioli, Helen Fewlass, Sahra Talamo, Edouard Bard, Lucia Mancini, Wolfgang Mueller, Matteo Romandini, Stefano Benazzi
Summary: The study reveals that Pradis 1 is a deciduous molar of an 11-12 year old male child, with various analyses indicating his movements during the first year of life and suggesting a cyclical/seasonal mobility pattern among the Epigravettian human group. The faunal spectra also suggest the specialized use of Grotte di Pradis as a marmot hunting or butchering site.
SCIENTIFIC REPORTS
(2022)
Article
Multidisciplinary Sciences
Massimo Avian, Lucia Mancini, Marco Voltolini, Delphine Bonnet, Diego Dreossi, Vanessa Macaluso, Nicole Pillepich, Laura Prieto, Andreja Ramsak, Antonio Terlizzi, Gregorio Motta
Summary: The study investigated the gastrovascular system of Rhizostoma pulmo in detail using resin endocasts and 3D X-ray computed microtomography. The system was found to have a unique structure with separate inward and outward flows, and the differentiation of openings reflected the functional characteristics of a through-gut apparatus.
Article
Archaeology
Antonino Vazzana, Owen Alexander Higgins, Gregorio Oxilia, Federico Lugli, Sara Silvestrini, Alessia Nava, Luca Bondioli, Eugenio Bortolini, Giovanni Di Domenico, Federico Bernardini, Claudio Tuniz, Lucia Mancini, Matteo Bettuzzi, Maria Pia Morigi, Marcello Piperno, Carmine Collina, Matteo Romandini, Stefano Benazzi
Summary: The reconstruction of the original morphology of bones and teeth is crucial for physicochemical and biomolecular analyses. By using computed micro-tomography, reverse engineering, computer-aided design, and rapid prototyping techniques, customized missing parts can be fabricated to restore the original external morphology of sampled teeth. The proposed protocol allows for a remarkable correspondence between the reconstructed parts and the original specimens' contact surfaces.
JOURNAL OF ARCHAEOLOGICAL SCIENCE-REPORTS
(2022)
Article
Archaeology
Giacomo Vinci, Alessandro Fontana, Giorgia Musina, Lucia Mancini, Carmine Lubritto, Lucia Liccioli, Federico Bernardini
Summary: Depositional and erosional processes, subsidence and sea-level changes have significantly impacted the coastal landscape of northern Adriatic lagoons. The retrieval and analysis of six metal swords from Marano Lagoon, combined with the study of the coastal paleo-environment, revealed the historical importance of the area and the significant morphological changes that have occurred there. The data also indicate that Marano Lagoon served as a major hub in the northern Adriatic during the Late Middle Ages and Early Modern times, connecting inland Europe with the Mediterranean Sea. Furthermore, the research highlights the onset of coastal erosion and its possible causes.
Article
Electrochemistry
Benedetto Bozzini, Sonia Bagheri, Marco Boniardi, Lucia Mancini, Emanuele Marini, Ivonne Sgura, Claudio Mele
Summary: Zinc-air fuel cells have gained attention in flow-battery technologies due to their better energy storage flexibility and environmental compatibility. However, there are still operational aspects that need to be studied, especially regarding anode passivation and air cathode degradation. This work proposes a simple and robust method to monitor cell response to changes in operating conditions using polarization curves and a macro-electrokinetic equation, providing a clear correlation between overvoltage components and cell state.
ELECTROCHIMICA ACTA
(2022)
Article
Geochemistry & Geophysics
Gabriele Lanzafame, Pier Paolo Giacomoni, Federico Casetta, Lucia Mancini, Gianluca Iezzi, Massimo Coltorti, Carmelo Ferlito
Summary: Understanding lava flow dynamics during major effusive events is crucial in volcanic areas with a high risk of lava invasion. This study investigates the 1669 eruption of Mount Etna volcano and reconstructs the degassing, crystallization, and rheological history of the magma and lavas. The results indicate that a combination of factors, including lava tunneling, delayed crystal nucleation and growth, and the presence of deformed bubbles, maintained the high fluidity of the melt suspension, allowing the flow to reach considerable distances from the vent. Accurate real-time petrological characterization is essential for reliable viscosity modeling and predicting lava flow direction.
JOURNAL OF PETROLOGY
(2022)
Article
Materials Science, Multidisciplinary
N. Ranc, A. Messager, A. Junet, T. Palin-Luc, J. Y. Buffiere, N. Saintier, M. Elmay, L. Mancini, A. King, Y. Nadot
Summary: This paper aims to study the initiation and propagation of internal cracks in very high cycle fatigue fractures. By using infrared thermography to measure the surface temperature field during an ultrasonic fatigue test, a relationship between the internal crack growth and temperature field evolution on the specimen surface can be established.
MECHANICS OF MATERIALS
(2022)
Article
Electrochemistry
Benedetto Bozzini, Marco Boniardi, Tommaso Caielli, Andrea Casaroli, Elisa Emanuele, Lucia Mancini, Nicola Sodini, Jacopo Strada
Summary: Secondary Zn-based batteries are a promising alternative to Li batteries for stationary storage, but their commercialization is hindered by issues such as anode shape-change and passivation. This study investigates the use of mildly acidic electrolytes to limit the unstable growth of Zn, with a focus on the impact of specific quaternary ammonium salts as electrolyte additives. The results show that TBAB is the most effective additive for low-current density operation, while additive-free electrolyte performs better at high current densities, consistent with previous findings for alkaline electrolytes.
Article
Geochemistry & Geophysics
F. Colle, M. Masotta, S. Costa, S. Mollo, P. Landi, A. Pontesilli, S. Peres, L. Mancini
Summary: This study investigates the textural and compositional evolution of clinopyroxene crystals using undercooling experiments. The results show that plagioclase is the dominant mineral phase at low undercooling, while clinopyroxene and spinel co-saturate the melt at higher undercooling. The morphological and geochemical changes in clinopyroxene are controlled by melt supersaturation and relaxation phenomena.
Article
Construction & Building Technology
Simona Raneri, Lucia Mancini, Gabriele Lanzafame, Alexander Peter Kao, Konstantinos Giannoukos, Ravi Chandra Malladi, M. Shiva Kumar, Vincenzo Palleschi, Thirumalini Selvaraj
Summary: The characterisation of lime mortars is crucial for the conservation and repair of ancient buildings. The pore structure, influenced by manufacturing processes, recipes, and technical expedients, plays a significant role in the strength and durability of mortars. Fermenting organic matter in water and adding it to lime mixture has shown promising potential for improving workability and mechanical performance. The use of high-resolution synchrotron radiation computed microtomography (SR-mu-CT) proves to be an effective tool for studying the contribution of organically fermented water in lime mortars and understanding the impact on pore structure and mechanical properties.
JOURNAL OF BUILDING ENGINEERING
(2023)
