Article
Physics, Multidisciplinary
Cheng Zhang, Jiaxuan Zhou, Feng Wu, Sui Wei
Summary: A compressive holography approach with autofocusing from a single-shot subsampled hologram is proposed in this paper. The approach combines a subsampling mechanism to establish a subsampled compressive holographic imaging model and an eigenvalues-based autofocusing algorithm to achieve autofocus reconstruction under subsampling condition in compressive holography. Furthermore, a multi-scale search algorithm is proposed to improve the accuracy of autofocus. Numerical experiments demonstrate the feasibility of the proposed approach in terms of precisely autofocusing and twin-image-free reconstruction from single-shot subsampled holograms.
Article
Optics
Tushar Sarkar, Vipin Tiwari, Sourav Chandra, Nandan S. Bisht, Rakesh Kumar Singh
Summary: This paper presents a holography technique based on higher-order Stokes correlation and demonstrates its application through experiments. The proposed technique is capable of reconstructing complex-valued objects from random light fields and overcomes twin image issues in higher-order correlation holography.
Article
Physics, Multidisciplinary
Cameron W. Johnson, Amy E. Turner, F. Javier Garcia de Abajo, Benjamin J. McMorran
Summary: A novel scanning electron Mach-Zehnder interferometer constructed in a conventional transmission electron microscope is used to perform inelastic interferometric imaging with free electrons. This technique is sensitive to the phase of localized optical modes and provides a new platform for controlling the transverse momentum of free electrons and studying coherent electron-matter.
PHYSICAL REVIEW LETTERS
(2022)
Article
Computer Science, Artificial Intelligence
Zhengquan Piao, Junbo Wang, Linbo Tang, Baojun Zhao, Wenzheng Wang
Summary: In this paper, a new anchor-free object detection method is proposed. Two-stage networks are used to predict regression results, reducing the scope of prediction space, and two novel modules are designed to extract effective features for accurate localization. Experimental results demonstrate that the proposed method outperforms previous related and advanced methods in object localization performance.
PATTERN RECOGNITION
(2022)
Article
Physics, Applied
Zhenpeng Luo, Da Sun, Ping Su, Jianshe Ma, Liangcai Cao
Summary: An algorithm for staggered tomography based on compressive holography (ST-CH) was proposed to improve the positioning accuracy of three-dimensional objects. Experimental observations on the movements and behaviors of Caenorhabditis elegans were conducted, leading to the successful observation of a kinematic fiber using segmented positioning along the object's skeleton.
JOURNAL OF PHYSICS D-APPLIED PHYSICS
(2021)
Article
Optics
Chaochen Ma, Qing Ren, Jian Zhao
Summary: A convolutional neural network based subpixel displacement measurement method is proposed in this paper, achieving coarse-to-fine subpixel displacement estimation by comparing images of an object with speckle patterns. Experimental results demonstrate the method's high efficiency, robustness, and simple structure in subpixel displacement measurement.
Article
Engineering, Mechanical
Hao Geng, Zhiyuan Gao, Guorun Fang, Yangmin Xie
Summary: This article introduces an effective solution for dense scanning, focusing on autonomous target recognition and accurate 3D localization in the process of geometrical modeling. By employing system calibration and fast outlier exclusion techniques, precise and clean data can be obtained, enabling the extraction of target objects and accurate estimation of their positions and orientations.
Article
Engineering, Electrical & Electronic
Shuaiheng Huai, Xinzhe Liu, Yi Jiang, Yanpeng Dai, Xiaoye Wang, Qing Hu
Summary: This article proposes a multifeature-based outdoor fingerprint localization technique for enhancing the accuracy of cellular network localization. Experimental results show that the proposed technique achieves high localization accuracy in complex urban outdoor environments.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Optics
Naru Yoneda, Osamu Matoba
Summary: Computational optical scanning holography (COSH) is a single-pixel incoherent digital holographic technique that requires a phase-shifting method to remove unnecessary components, resulting in a larger number of measurements. To reduce the number of measurements, a spatially divided phase-shifting method has been proposed, but it has a lower spatial resolution. In this paper, a spatially divided two-step phase-shifting method is proposed to improve spatial resolution, and its feasibility and the improvement in image quality are validated through numerical evaluation and microscopy experiments.
Article
Chemistry, Multidisciplinary
Dominik Bachmann, Rolf Broennimann, Luis Nicklaus Caceres, Sofie L. Gnannt, Erwin Hack, Elena Mavrona, Daniel Sacre, Peter Zolliker
Summary: THz-Time domain spectroscopic imaging is achieved by combining robotic scanning, continuous signal acquisition, and holographic reconstruction to enhance imaging resolution. The method is applied to a metallic Siemens star for resolution quantification and to wood samples for showcasing the technique on a non-metallic object with an unknown structure.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Interdisciplinary Applications
Maciej Czepita, Anna Fabijanska
Summary: An automated pipeline was proposed for analyzing blood flow through retinal vessels to replace time-consuming manual methods. Using convolutional neural networks and full width at half maximum analysis, blood flow was successfully detected in 18 retinal blood vessels. The average difference between manual and automatic measurements was 4.96%, with an average relative error of 8% for single vessel measurements.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2021)
Article
Engineering, Electrical & Electronic
Qing He, Zhiwen Ji, Peng Yu, Dongyue Chen
Summary: Camera calibration is essential in 3-D computer vision, and the precision of calibration relies on the accurate localization of control points in calibration patterns. However, the sub-pixel localization methods for the commonly used control points, i.e., corners of squares and centers of circles, differ significantly. This study proposes a unified approach to sub-pixel localization for both types of control points, derived from theoretical analysis and consisting of a closed-form solution and practical implementation algorithms. The proposed approach has been tested using synthetic datasets and real calibration experiments, demonstrating good results. Compared to existing techniques, this approach provides a unified and high-precision sub-pixel localization method for commonly used calibration patterns.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Environmental Sciences
Jesus Palomar-Vazquez, Josep E. Pardo-Pascual, Jaime Almonacid-Caballer, Carlos Cabezas-Rabadan
Summary: SAET is an open-source tool that automatically detects shoreline position changes using optical imagery from Sentinel-2 and Landsat 8 and 9 satellites. It is developed to characterize shoreline response to various events and phenomena, and offers different settings for different coastal environments. The tool is efficient, flexible, and provides high subpixel accuracy.
Article
Computer Science, Artificial Intelligence
Mohammed Y. Abbass, Ki-Chul Kwon, Nam Kim, Safey A. Abdelwahab, Fathi E. Abd El-Samie, Ashraf A. M. Khalaf
Summary: This paper proposes an efficient object tracking algorithm that adaptively represents the object appearance using CNN-based features and a sparse measurement matrix. It achieves real-time tracking with substantially better performance in terms of robustness, accuracy, and efficiency compared to state-of-the-art techniques on challenging video datasets.
ARTIFICIAL INTELLIGENCE REVIEW
(2021)
Article
Computer Science, Artificial Intelligence
Alexey Zakharov, Maxim Pisov, Alim Bukharaev, Alexey Petraikin, Sergey Morozov, Victor Gombolevskiy, Mikhail Belyaev
Summary: Vertebral body compression fractures are early signs of osteoporosis, but they are often missed by radiologists in clinical settings. This study proposes a new algorithm that can localize the vertebral column, detect individual vertebrae, and quantify fractures in 3D CT images. The algorithm achieves excellent performance in processing speed, accuracy, and fracture identification.
MEDICAL IMAGE ANALYSIS
(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)