Article
Optics
Xiaofeng Wu, Ziling Wu, Sibi Chakravarthy Shanmugavel, Hang Z. Yu, Yunhui Zhu
Summary: In this study, we propose a physics-informed neural network (PINN) to address the issues in non-interferometric quantitative phase imaging. By integrating the forward and inverse physics models into the neural network, high-quality phase images can be efficiently obtained from noise-corrupted data. The effectiveness of the proposed approach is demonstrated through experiments, showing the ability to achieve high image quality with a reduced size of labeled data.
Article
Multidisciplinary Sciences
Alexander Goncharsky, Anton Goncharsky, Svyatoslav Durlevich, Dmitry Melnik
Summary: A method is proposed for computing and synthesizing microrelief to produce nano-optical elements that can form 3D images with full parallax. The accuracy of microrelief formation is 10 nm, and the optical elements developed can be replicated using standard equipment. The new optical security feature is visually controllable, protected against counterfeiting, and designed for protecting various documents.
SCIENTIFIC REPORTS
(2022)
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
Mathematics
Tao Liu, Di Ouyang, Lianjun Guo, Ruofeng Qiu, Yunfei Qi, Wu Xie, Qiang Ma, Chao Liu
Summary: This paper proposes a rapid and accurate numerical solution for the inverse problem of the nonlinear diffusion equation in multiphase porous media flow. The combination of the multigrid method with constraint data is utilized and investigated. The results demonstrate the effectiveness of this combination strategy in reducing noise, avoiding local minima, and accelerating convergence.
Article
Optics
Shane Carney, Ting Chean Khoo, Alireza Sheikhsofla, Samaneh Ghazanfarpour, Anna Sharikova, Supriya D. Mahajan, Alexander Khmaladze, Jonathan C. Petruccelli
Summary: Quantitative phase imaging (QPI) allows label-free assessment of live cells, and digital holographic microscopy (DHM) is an accurate and reliable technique for QPI. However, the assembly and operation of DHM can be challenging for many labs. The transport of intensity equation (TIE) imaging is a QPI method that is compatible with conventional microscopy and has lower cost and coherence requirements compared to DHM. Here, a microscope capable of performing simultaneous DHM and TIE phase reconstructions is presented to validate TIE as an accurate method for both static sample arrays and live cells.
OPTICS AND LASERS IN ENGINEERING
(2023)
Article
Physics, Multidisciplinary
Mark J. Ablowitz, Joel B. Been, Lincoln D. Carr
Summary: This article presents a new class of integrable fractional nonlinear evolution equations that describe dispersive transport in fractional media. These equations can be constructed from nonlinear integrable equations using a widely generalizable mathematical process and have been applied to fractional extensions of the Korteweg-deVries and nonlinear Schrodinger equations.
PHYSICAL REVIEW LETTERS
(2022)
Article
Optics
Linpeng Lu, Yao Fan, Jiasong Sun, Jialing Zhang, Xuejuan Wu, Qian Chen, Chao Zuo
Summary: The TIE approach has limitations in application, while alternative QPI methods are only suitable for weakly scattering samples, posing a challenge for nonweak phase objects with large phase excursions. The proposed mixed-transfer-function approach effectively addresses the dilemma between measurement accuracy and imaging resolution.
Article
Mathematics, Applied
Dinh Nguyen Duy Hai
Summary: This paper discusses an ill-posed inverse problem related to practical applications. With two regularization strategies, the paper obtains error estimates for the exact solution and provides numerical examples.
JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS
(2024)
Article
Materials Science, Multidisciplinary
S. Candussio, L. E. Golub, S. Bernreuter, T. Joetten, T. Rockinger, K. Watanabe, T. Taniguchi, J. Eroms, D. Weiss, S. D. Ganichev
Summary: This study reports the observation of terahertz-radiation-induced edge photogalvanic currents in graphene, which exhibit nonlinearity in intensity and are controlled by various factors. The nonlinearity is attributed to the interplay of direct interband optical transitions and Drude-like absorption mechanisms. Both photocurrents saturate at high intensities but demonstrate different intensity dependencies, while the total photocurrent shows a complex sign-alternating intensity dependence. The experimental data and theory developed show good agreement regarding the functional behavior of the saturation intensities and amplitudes of the photogalvanic currents under different conditions.
Article
Computer Science, Artificial Intelligence
Hossein S. Aghamiry, Ali Gholami, Stephane Operto
Summary: Full-waveform inversion is a nonlinear optimization problem seeking to estimate medium parameters by fitting waveforms. To address this, processing complex velocities in the frequency domain and using relaxation methods in optimization have been proposed. Additionally, TV regularization schemes can help mitigate ill-posedness and improve reliability in the estimation of phase velocity and attenuation factor.
SIAM JOURNAL ON IMAGING SCIENCES
(2021)
Article
Optics
KeMing Gao, Meng Chang, Kunjun Jiang, Yaxu Wang, Zhihai Xu, Huajun Feng, Qi Li, Zengxin Hu, YueTing Chen
Summary: A new method is proposed to address the degradation of under-display imaging, utilizing a synthetic dataset and a two-stage neural network to tackle the issue, with superior performance demonstrated on real-world test sets in different dynamic range scenes.
Article
Geosciences, Multidisciplinary
Shufang Fan, Wei Tang, Yanfei Wang, M. Zuhair Nashed
Summary: X-ray computed tomography is a non-destructive method commonly used to study the properties of shale, such as size, shape, 3D structures, and connectivity of pores. This study proposes a new method that solves the ill-posed problem caused by phase shift using phase retrieval in the space domain with a regularization technique. The results show that the new method has advantages over traditional frequency domain methods, with more stability and fewer artifacts under noise perturbations.
FRONTIERS IN EARTH SCIENCE
(2023)
Review
Materials Science, Multidisciplinary
Shuai Li, C. M. Wang, Z. Z. Du, Fang Qin, Hai-Zhou Lu, X. C. Xie
Summary: The perspective introduces the emergent 3D quantum Hall effects and nonlinear Hall effect, discussing their significance in advancing the understanding of Hall physics and exploring future research directions.
NPJ QUANTUM MATERIALS
(2021)
Article
Optics
Gaston A. Ayubi, M. Fernandez Lakatos, Nicolas Casaballe, Erna Frins
Summary: A new quantitative approach for phase retrieval is presented, which is derived from analyzing the light intensity propagation through a phase object and a sinusoidal intensity mask. Unlike the Transport of Intensity Equation (TIE), this new algorithm is simpler as it does not involve the Laplacian of the phase, and it can be easily implemented in practical applications.
OPTICS AND LASERS IN ENGINEERING
(2023)
Article
Engineering, Electrical & Electronic
Chen Fan, Hong Zhao, Zixin Zhao, Junxiang Li, Yijun Du, Gaopeng Zhang
Summary: We propose a high-accurate quantitative phase imaging (QPI) method by combining transport of intensity equation (TIE) and wavelet transform (WT). TIE provides a simple and fast approach for QPI, but its accuracy is limited due to nonlinear error and noise caused by defocus distance. By introducing WT and fusing effective information extracted from phases at different defocus distances, we can obtain a more accurate phase. We also solve the problems of phase discrepancy and phase singularity in TIE using an iterative WT-TIE algorithm, extending the applicability of our method.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
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)