Article
Optics
Fuda Jiang, Chonglei Zhang
Summary: For quantitative phase imaging (QPI) based on transport-of-intensity equation (TIE), the phase obtained by TIE is limited by the higher-order intensity derivatives caused by large defocus distance and the phase discrepancy caused by Teague assumption. To overcome these issues and achieve higher accuracy phase without increasing the number of defocus images, we propose a fast compensation algorithm that requires only a few iterations. The convergence of our algorithm is theoretically proved and its efficiency is verified by experiments. We believe that this method, with its characteristics of fast and higher accuracy, will contribute to the application of QPI.
OPTICS AND LASERS IN ENGINEERING
(2023)
Article
Construction & Building Technology
Sizhe Du, Yu Zhang, Jie Zhang, Nina Selyutina, Ivan Smirnov, Gang Ma, Xiang Zhang, Beibei Li, Yanchun Miao, Yuanzhen Liu, Wenjing Wang
Summary: High temperatures can significantly affect the internal pore structure of concrete and therefore degrade its mechanical properties. This study examined the impact of high temperatures on the microstructural characteristics and residual mechanical properties of recycled aggregate concrete mixed with glazed hollow beads (RATIC). The results showed that the addition of glazed hollow beads can slow down heat propagation in the concrete and improve its resistance to heat-induced damage. Additionally, a quantitative relationship was established between pore characteristic parameters and the residual compressive strength of RATIC.
CONSTRUCTION AND BUILDING MATERIALS
(2022)
Article
Energy & Fuels
Junwei Hou, Weichuang Wu, Lifu Li, Xin Tong, Renjun Hu, Weibin Wu, Weizhi Cai, Hailin Wang
Summary: A novel estimation method based on X-ray industrial computed tomography (ICT) is developed to accurately estimate the remaining capacity of Lithium-ion batteries for electric vehicles. Experimental results show that the maximum prediction error of this model is 5.2%, lower than that of the traditional method (24.1%), indicating great potential in reducing cost and improving efficiency.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Physics, Multidisciplinary
Tatiana Latychevskaia
Summary: In this study, a new method is proposed to reconstruct 3D sample distribution from a single 2D intensity measurement, exceeding the classical limit in z resolution. This method is practical for radiation-sensitive materials or experimental setups with constraints on the number of intensity measurements.
PHYSICAL REVIEW LETTERS
(2021)
Article
Construction & Building Technology
P. Kuusela, M. Pour-Ghaz, R. Pini, A. Voss, A. Seppanen
Summary: This study investigated chemical reactions and flow behaviors of fluids (krypton, CO2, water) in fractured cement-paste samples using X-ray computed tomography (CT) imaging. The CT images captured the formation of a carbonate phase during CO2 injection and water flow in the fractured media. Quantification of porosity reduction resulting from the carbonation reaction was performed to demonstrate the ability of CT to image reactive transport in cement-based materials.
CEMENT & CONCRETE COMPOSITES
(2021)
Article
Optics
Hong Cheng, Wentong Wu, Qiyang Zhang, Yifan Cheng
Summary: In this paper, we propose a binocular phase retrieval algorithm based on multiwavelength illumination. By combining the synthetic wavelengths and synthetic phases obtained from solving the single-phase results at different wavelengths, we calculate the surface height of the object and reconstruct the initial phase results at different wavelengths. A step-by-step noise reduction method is introduced to solve the amplification of traditional noise and surface profile noise in the phase synthesis step, achieving high-precision phase results at different wavelengths. The correctness and effectiveness of the algorithm are verified through intensity images collected by the proposed dual-microscope system.
OPTICAL ENGINEERING
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Sebastian Nowak, Christoph Kloth, Maike Theis, Milka Marinova, Ulrike I. Attenberger, Alois M. Sprinkart, Julian A. Luetkens
Summary: This study aimed to evaluate the prognostic value of CT-based markers of sarcopenia and myosteatosis in patients with advanced pancreatic cancer treated with HIFU. The markers were found to be associated with sex, age, body mass index (BMI), and ECOG score. Higher ECOG score and more severe sarcopenia were associated with shorter survival times. Multivariable analysis showed that higher ECOG score, more severe sarcopenia, less severe myosteatosis, and higher fatty muscle fraction were associated with increased patient risk for 1-year survival.
EUROPEAN RADIOLOGY
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Alexander Hertel, Hishan Tharmaseelan, Lukas T. Rotkopf, Dominik Noerenberg, Philipp Riffel, Konstantin Nikolaou, Jakob Weiss, Fabian Bamberg, Stefan O. Schoenberg, Matthias F. Froelich, Isabelle Ayx
Summary: This study aims to evaluate the stability of radiomics analysis using photon-counting detector CT (PCCT) on phantom scans. PCCT scans were performed on organic phantoms consisting of apples, kiwis, limes, and onions to extract radiomics parameters. Statistical analysis showed that most parameters have good stability, and identified important features for the application of radiomics analysis in clinical practice.
EUROPEAN RADIOLOGY
(2023)
Article
Multidisciplinary Sciences
Marina Eckermann, Bernhard Schmitzer, Franziska van der Meer, Jonas Franz, Ove Hansen, Christine Stadelmann, Tim Salditt
Summary: By studying the three-dimensional cytoarchitecture of the human hippocampus in healthy and AD individuals, focusing on the nuclear structure of dentate gyrus granule cells, we identified changes in volume and electron density in the nuclei, as well as other structural properties reflecting natural variability and effects associated with AD pathology.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2021)
Article
Optics
Iliya Gritsenko, Michael Kovalev, George Krasin, Matvey Konoplyov, Nikita Stsepuro
Summary: This paper proposes a new mathematical model that adapts the transport-of-intensity equation for wavefront sensing, analyzing the influence of longitudinal displacement and step between measurements, and comparing it to traditional methods and Fourier hologram-based methods. Numerical simulations show that this method allows for measuring the wavefront radius of curvature with a radius of 40 mm and an accuracy of approximately 200 μm.
Article
Chemistry, Physical
Julien Gonthier, Tilman Rilling, Ernesto Scoppola, Fabian Zemke, Aleksander Gurlo, Peter Fratzl, Wolfgang Wagermaier
Summary: This study used in operando X-ray micro-computed tomography (mu CT) to monitor the progression of the liquid, gaseous, and solid phases of silica gels during ambient pressure drying and spring-back. The findings challenge the common assumption about the penetration of gas during the spring-back effect and show that the emergence of the spring-back effect is correlated to an equal volume fraction of solid, liquid, and gas in the gels.
CHEMISTRY OF MATERIALS
(2023)
Article
Optics
Da-liang Wu, Jin Wu, Jin Liu, Xin Ma, Zhi-wei Kang
Summary: The study introduces the application of compressive sensing in X-ray pulsar signals, proposes a quantum-based compressive sensing method, and applies it to pulsar positioning and velocimetry. The quantum observation matrix explores the uncertainty of quantum and improves its diversity, providing a solution for accurate pulsar positioning and velocity measurement.
Article
Chemistry, Physical
Zeliang Su, Etienne Decenciere, Tuan-Tu Nguyen, Kaoutar El-Amiry, Vincent De Andrade, Alejandro A. Franco, Arnaud Demortiere
Summary: The segmentation of tomographic images of battery electrode is crucial for material characterization and electrochemical simulation. We propose a deep learning approach using a CNN for real-world battery material datasets, achieving high accuracy with limited labeled data. We also address the uncertainty in the segmentation quality by identifying human bias in the training data.
NPJ COMPUTATIONAL MATERIALS
(2022)
Article
Construction & Building Technology
Sheng Jiang, Luming Shen, Wengui Li
Summary: The study investigated the influence of aggregate shape on mortar dynamic failure behaviors using a Split Hopkinson bar device. It was found that the shape of aggregates significantly affected the cracking mechanisms in mortar, with more regular aggregates leading to higher dynamic compressive strength and strain rate sensitivity.
CONSTRUCTION AND BUILDING MATERIALS
(2021)
Article
Engineering, Civil
Adrian Rozanski, Anna Rozanska, Maciej Sobotka, Michal Pachnicz, Miroslawa Bukowska
Summary: Material properties depend on structure and can change significantly as structure evolves. Laboratory techniques can be used to evaluate material structure under different temperatures and analyze the impact on mechanical parameters.
ARCHIVES OF CIVIL AND MECHANICAL ENGINEERING
(2021)
Editorial Material
Optics
Yunzhe Li, Lei Tian
Summary: Diffractive Deep Neural Network allows for all-optical computational imaging to penetrate unknown random diffusers at the speed of light.
LIGHT-SCIENCE & APPLICATIONS
(2022)
Article
Optics
Waleed Tahir, Hao Wang, Lei Tian
Summary: The researchers propose an adaptive learning framework called dynamic synthesis network (DSN) to adapt to different scattering conditions by blending multiple experts using a gating network. They demonstrate the DSN in holographic 3D particle imaging for a variety of scattering conditions and show its robust performance in simulation and experiments.
LIGHT-SCIENCE & APPLICATIONS
(2022)
Editorial Material
Optics
Lei Tian
Summary: Deep learning allows for the optimization of imaging speed, field of view, and spatial resolution in autofluorescence-harmonic microscopy without tradeoffs.
LIGHT-SCIENCE & APPLICATIONS
(2022)
Article
Neurosciences
Ahmed S. Abdelfattah, Sapna Ahuja, Taner Akkin, Srinivasa Rao Allu, Joshua Brake, David A. Boas, Erin M. Buckley, Robert E. Campbell, Anderson Chen, Xiaojun Cheng, Tomas Cizmar, Irene Costantini, Massimo De Vittorio, Anna Devor, Patrick R. Doran, Mirna El Khatib, Valentina Emiliani, Natalie Fomin-Thunemann, Yeshaiahu Fainman, Tomas Fernandez-Alfonso, Christopher G. L. Ferri, Ariel Gilad, Xue Han, Andrew Harris, Elizabeth M. C. Hillman, Ute Hochgeschwender, Matthew G. Holt, Na Ji, Kivilcim Kilic, Evelyn M. R. Lake, Lei Li, Tianqi Li, Philipp Machler, Evan W. Miller, Rickson C. Mesquita, K. M. Naga Srinivas Nadella, U. Valentin Nagerl, Yusuke Nasu, Axel Nimmerjahn, Petra Ondrackova, Francesco S. Pavone, Citlali Perez Campos, Darcy S. Peterka, Filippo Pisano, Ferruccio Pisanello, Francesca Puppo, Bernardo L. Sabatini, Sanaz Sadegh, Sava Sakadzic, Shy Shoham, Sanaya N. Shroff, R. Angus Silver, Ruth R. Sims, Spencer L. Smith, Vivek J. Srinivasan, Martin Thunemann, Lei Tian, Lin Tian, Thomas Troxler, Antoine Valera, Alipasha Vaziri, Sergei A. Vinogradov, Flavia Vitale, Lihong Wang, Hana Uhlirova, Chris Xu, Changhuei Yang, Mu-Han Yang, Gary Yellen, Ofer Yizhar, Yongxin Zhao
Summary: This article reviews a diverse toolkit of novel methods for exploring brain function that have emerged from the BRAIN Initiative and related large-scale efforts, with a focus on neurophotonic tools applicable to animal studies. It provides an outlook for future directions in the field.
Article
Optics
Jiabei Zhu, Hao Wang, Lei Tian
Summary: In this study, a novel IDT reconstruction algorithm based on the SSNP model is proposed for recovering the 3D refractive index distribution of multiple-scattering biological samples. The algorithm accurately computes multiple scattering from high-angle illumination and is applied to both sequential and multiplexed IDT techniques. Experimental results demonstrate the effectiveness and computational efficiency of the algorithm.
Article
Optics
Jianing Liu, Hao Wang, Leonard C. Kogos, Yuyu Li, Yunzhe Li, Lei Tian, Roberto Paiella
Summary: Photonics offers a promising approach for image processing through spatial filtering, providing faster speeds and lower power consumption compared to electronic digital solutions. A new method based on pixel arrays of plasmonic directional image sensors is presented, allowing selective detection of light along a small set of geometrically adjustable directions. The resulting imaging systems serve as optical spatial filters without external filtering elements, enabling extreme size miniaturization and the ability to perform multiple filtering operations simultaneously. Rigorous theoretical models and experimental demonstrations showcase the image processing capabilities of these devices, with potential applications in biomedicine and computer vision.
Article
Optics
Yujia Xue, Qianwan Yang, Guorong Hu, Kehan Guo, Lei Tian
Summary: A computational miniature mesoscope (CM2) was developed to enable single-shot, 3D high-resolution imaging across a wide field of view on a miniaturized platform. By improving hardware and computation, including a hybrid emission filter and a 3D-printed collimator for LED illuminator, along with the development of a 3D linear shift-variant model and a deep learning model, accurate and efficient 3D reconstruction was achieved. The CM2Net model demonstrated superior axial resolution and speed compared to previous algorithms, making it a promising tool for large-scale 3D fluorescence imaging applications.
Article
Optics
Sylvain Gigan, Ori Katz, Hilton B. de Aguiar, Esben Ravn Andresen, Alexandre Aubry, Jacopo Bertolotti, Emmanuel Bossy, Dorian Bouchet, Joshua Brake, Sophie Brasselet, Yaron Bromberg, Hui Cao, Thomas Chaigne, Zhongtao Cheng, Wonshik Choi, Tomas Cizmar, Meng Cui, Vincent R. Curtis, Hugo Defienne, Matthias Hofer, Ryoichi Horisaki, Roarke Horstmeyer, Na Ji, Aaron K. LaViolette, Jerome Mertz, Christophe Moser, Allard P. Mosk, Nicolas C. Pegard, Rafael Piestun, Sebastien Popoff, David B. Phillips, Demetri Psaltis, Babak Rahmani, Herve Rigneault, Stefan Rotter, Lei Tian, Ivo M. Vellekoop, Laura Waller, Lihong Wang, Timothy Weber, Sheng Xiao, Chris Xu, Alexey Yamilov, Changhuei Yang, Hasan Yilmaz
Summary: In the last decade, various tools such as wavefront shaping and computational methods have been developed to understand and control the propagation of light in complex mediums. This field has revolutionized the possibility of diffraction-limited imaging at depth in tissues, and a vibrant community is actively working on it.
JOURNAL OF PHYSICS-PHOTONICS
(2022)
Article
Optics
Alex Matlock, Jiabei Zhu, Lei Tian
Summary: Recovering the 3D phase features of complex biological samples has traditionally involved sacrificing computational efficiency and processing time for physical model accuracy and reconstruction quality. However, this study introduces an approximant-guided deep learning framework that overcomes this challenge in a high-speed intensity diffraction tomography system. By training the network on natural image datasets using a physics model simulator-based learning strategy, complex 3D biological samples can be robustly reconstructed. This framework utilizes a lightweight 2D network structure with a multi-channel input to encode axial information, achieving highly efficient training and prediction.
Article
Multidisciplinary Sciences
Jian Zhao, Alex Matlock, Hongbo Zhu, Ziqi Song, Jiabei Zhu, Biao Wang, Fukai Chen, Yuewei Zhan, Zhicong Chen, Yihong Xu, Xingchen Lin, Lei Tian, Ji-Xin Cheng
Summary: This paper introduces Bond-selective Intensity Diffraction Tomography (BS-IDT), a computational mid-infrared photothermal microscopy technique based on a standard bright-field microscope and an add-on pulsed light source. It recovers both mid-infrared spectra and bond-selective 3D refractive index maps based on intensity-only measurements.
NATURE COMMUNICATIONS
(2022)
Article
Biochemical Research Methods
Jelena Platisa, Xin Ye, Allison M. Ahrens, Chang Liu, Ichun Anderson Chen, Ian G. Davison, Lei Tian, Vincent A. Pieribone, Jerry L. Chen
Summary: Monitoring spiking activity in large neuronal populations is crucial for understanding neural circuit function. Voltage imaging provides a new approach for this, but it faces challenges such as reduced fluorescence detection and limited imaging duration. This study developed improved voltage indicators, a high-speed two-photon microscope, and denoising software, enabling simultaneous high-speed deep-tissue imaging of more than 100 labeled neurons over 1 hour. This scalable approach offers a way to image voltage activity across increasing neuronal populations.
Article
Optics
Hao Wang, Jiabei Zhu, Jangwoon Sung, Guorong Hu, Joseph Greene, Yunzhe LI, Seungbeom Park, Wookrae Kim, Myungjun Lee, Yusin Yang, Lei Tian
Summary: Topography measurement is crucial for surface characterization and inspection applications. This study presents a novel topography technique called Fourier ptychographic topography (FPT), which combines a computational microscope and a phase retrieval algorithm to achieve wide-field-of-view and high-resolution topography reconstruction with nanoscale accuracy. FPT has important implications for surface characterization, semiconductor metrology, and inspection applications.
Article
Optics
Jian Zhao, Lulu Jiang, Alex Matlock, Yihong Xu, Jiabei Zhu, Hongbo Zhu, Lei Tian, Benjamin Wolozin, Ji-Xin Cheng
Summary: Researchers developed a computational chemical microscope, FBS-IDT, which can extract molecular structure information of amyloid proteins in their native cellular environment. This technology enables label-free volumetric chemical imaging and 3D visualization of amyloid protein aggregates, as well as depth-resolved mid-infrared fingerprint spectroscopy for protein secondary structure analysis. It provides a new approach to study the relationship between neurodegenerative diseases and amyloid proteins.
LIGHT-SCIENCE & APPLICATIONS
(2023)
Article
Nanoscience & Nanotechnology
Jianing Liu, Hao Wang, Yuyu Li, Lei Tian, Roberto Paiella
Summary: This paper introduces a new type of image sensor that can directly visualize phase objects without additional optical elements. It is particularly significant for applications involving space-constrained and portable setups, and is applicable to surface profiling and biomedical microscopy.
Article
Computer Science, Artificial Intelligence
Renhao Liu, Yu Sun, Jiabei Zhu, Lei Tian, Ulugbek S. Kamilov
Summary: Intensity Diffraction Tomography (IDT) is a technique that uses optical microscopy to image the three-dimensional refractive index distribution of a sample from two-dimensional intensity-only measurements. Neural fields is a new deep learning approach that can learn continuous representations of physical fields. DeCAF is a neural-fields-based IDT method that can learn a high-quality continuous representation of a refractive index volume from intensity-only and limited-angle measurements, without ground-truth RI maps. DeCAF can generate high-contrast and artifact-free RI maps and outperforms existing methods in terms of mean squared error reduction.
NATURE MACHINE INTELLIGENCE
(2022)