Correction
Optics
Lei Tian, Laura Waller
Summary: This errata corrects typographical errors in the derived transfer functions in [Opt. Express 23, 11394 (2015)].
Article
Optics
Jixin Jiang, Fanxing Li, Fan Yang, Wei Yan, Jialin Du
Summary: Common quantitative differential phase contrast microscopy imaging usually suffers from low capture efficiency and poor phase reconstruction due to multistep circular or annular illuminations and color multiplexed illuminations. In this study, a new single-shot imaging method using R/B-G annular LED multiplexed illumination is presented for better phase reconstruction. Simulation results show that this method achieves better axial phase reconstruction accuracy and weaker lateral anisotropy compared to other color multiplexed illuminations. Experimental results on different samples demonstrate the feasibility and utility of this method in real-time quantitative phase imaging, especially for living biological tissues.
OPTICS AND LASER TECHNOLOGY
(2023)
Review
Physics, Applied
Sunil Vyas, An-Cin Li, Yu-Hsiang Lin, J. Andrew Yeh, Yuan Luo
Summary: This review focuses on quantitative differential phase contrast microscopy (qDPC), a non-interferometric technique for quantitative phase imaging. The principles, imaging systems, and applications of qDPC are discussed, and the latest results using deep learning for isotropic phase contrast enhancements are presented.
JOURNAL OF PHYSICS D-APPLIED PHYSICS
(2022)
Article
Computer Science, Interdisciplinary Applications
Shuhe Zhang, Tao Peng, Zeyu Ke, Han Yang, Tos T. J. M. Berendschot, Jinhua Zhou
Summary: In this study, the Retinex-qDPC method is proposed to improve the quality of phase recovery in the presence of mismatched background. By utilizing the edge features of images, the Retinex-qDPC models achieve high background-robustness qDPC reconstruction. The L1-Retinex-qDPC outperforms other state-of-the-art qDPC algorithms.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2023)
Article
Optics
Stewart Koppell, Mark Kasevich
Summary: The importance of dedicated phase contrast optics for imaging non-absorbing samples is discussed in the article. The efficiency of various phase imaging schemes is evaluated using Fisher information, and an information transfer function is calculated. The study shows that generalized Zernike phase contrast with prior knowledge and random sensing measurements are effective methods.
Article
Biochemical Research Methods
Ying-Ju Chen, Yu-Zi Lin, Sunil Vyas, Tai-Horng Young, Yuan Luo
Summary: This study proposes a dual-color linear-gradient pupil approach with two intensity measurements, achieving high-contrast and isotropic qDPC images. By performing time-lapse imaging of rat astrocytes, the morphological and dynamic changes of cells were observed.
JOURNAL OF BIOMEDICAL OPTICS
(2022)
Article
Nanoscience & Nanotechnology
Ying Zhu, Peter J. Reece
Summary: This study introduces a phase-based imaging approach using differential interference contrast (DIC) as a means of label-free optical sensing with plasmonic nanohole arrays. By developing a colorimetric-based imaging readout and evaluating the refractive-index sensing capability using a layer-by-layer polyelectrolyte deposition model, the researchers cross-validate the DIC imaging approach and show good agreement among different measurements, opening up potential applications for rapid and multiplexed sensing using the phase response of nanoplasmonic structures.
ACS APPLIED NANO MATERIALS
(2021)
Article
Computer Science, Interdisciplinary Applications
An-Cin Li, Sunil Vyas, Yu-Hsiang Lin, Yi-You Huang, Hsuan-Ming Huang, Yuan Luo
Summary: The proposed DL-based method utilizes U-net architecture to generate isotropic qDPC microscopy images from the least number of measurements. Training the model with a patch-wise approach improves phase uniformity and retrieves missing spatial frequencies in 1-axis reconstructed images. Results show higher PSNR and SSIM values compared to other methods, indicating the advantage of using the U-net model for isotropic qDPC microscopy in high-resolution quantitative studies for cell biology.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2021)
Article
Optics
Tao Peng, Zeyu Ke, Shuhe Zhang, Jun He, Peng Wang, Fengsong Wang, Zhensheng Zhong, Shu Fang, Hui Shi, Rongsheng Lu, Jinhua Zhou
Summary: Quantitative differential phase contrast (qDPC) microscopy is a high spatial resolution technique for phase imaging of unlabeled cell samples, but it is easily affected by experimental noise. In this study, L0-norm regularization was introduced into qDPC phase reconstruction for sparse samples (L0-qDPC) and compared with L2-norm and total variation regularization. The results showed that L0-qDPC method provides stable qDPC phase imaging without parameter adjustment, due to the strong constraint and good robustness of L0-norm based on sparse prior.
OPTICS AND LASERS IN ENGINEERING
(2023)
Article
Optics
Young-Sung Park, Jieun Hong, Jaeho Choi
Summary: Non-interferometric X-ray quantitative phase imaging (XQPI) provides high-resolution and reliable phase-contrast images. We implemented volumetric XQPI images by concurrently scanning the orthogonal plane on the optical axis of the Foucault differential filter and extracting data using the transport-intensity equation. Our XQPI method successfully reconstructed a volumetric image of the laminate microstructure of fish gills, demonstrating its capability for 3D rendering without rotational motion for laterally extended objects using incoherent X-rays and a pinhole array.
CHINESE OPTICS LETTERS
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Xin Zhang, Ting Su, Jiecheng Yang, Jiongtao Zhu, Dongmei Xia, Hairong Zheng, Dong Liang, Yongshuai Ge
Summary: In this study, the quantitative material decomposition performance of dual-energy CT (DECT) and differential phase contrast CT (DPCT) were evaluated and compared via numerical observer studies. The results showed that DECT and DPCT exhibited different quantitative imaging performance under different spatial resolutions and radiation dose levels.
Article
Optics
Yao Fan, Jiaji Li, Linpeng Lu, Jiasong Sun, Yan Hu, Jialin Zhang, Zhuoshi Li, Qian Shen, Bowen Wang, Runnan Zhang, Qian Chen, Chao Zuo
Summary: Computational microscopy, a subfield of computational imaging, combines optical manipulation and image algorithmic reconstruction to recover multi-dimensional microscopic images or information of micro-objects. Recent advancements in LED technology, low-cost consumer image sensors, digital computers, and smartphones have enabled the rapid development of computational microscopy, offering high-resolution imaging capabilities for various applications in biomedicine and industry.
Article
Chemistry, Multidisciplinary
Kisoo Kim, Yeon Hwang, Jongbok Park
Summary: This paper presents a multi-mode compact microscope (MCM) that offers high-contrast and high-resolution imaging. The MCM supports various imaging modes, including reflection, transmission, and higher magnification. It utilizes LED illuminations and micro-lens array (MLA) technology to enhance image quality and resolution. This compact portable microscope provides a new platform for on-site defect inspection or disease detection.
APPLIED SCIENCES-BASEL
(2022)
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
Cell Biology
Osamu Yasuhiko, Kozo Takeuchi, Hidenao Yamada, Yukio Ueda
Summary: A single-shot quantitative phase imaging (QPI) method was proposed by combining DIC microscopy and QPI in this study. The system successfully imaged nucleoli and lipid droplets in cell biology research, and combining it with fluorescence microscopy may provide more comprehensive information for research. Time-lapse imaging was also conducted to visualize the dynamics of intracellular granules in monocyte-/macrophage-like cells, demonstrating the potential of this approach for standard biomedical laboratories.
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)