arXiv subjects

Oumeng Zhang

Publications and source records attributed to Oumeng Zhang.

11 recordsLinked to original sources

arXiv2026

Plasmon-Enabled High-Precision Single Molecule Localization Microscopy over an Extended Field of View

We propose PIFLUX, a single-molecule localization scheme combining deep-subwavelength plasmonic illumination with widefield detection. Interference between counter-propagating gap plasmons and a normally incident optical field generates an illumination pattern whose position can be tuned through the plasmon phase while preserving its spatial period. A Cramér-Rao analysis shows PIFLUX reaches few-nanometer precision matching MINFLUX while doubling that of SIMFLUX over a micrometer field of view, and a maximum-likelihood estimator confirms this on a synthetic nuclear pore complex.

physics.optics↗

arXiv2026

Digital defocus aberration interference for automated optical microscopy

Automation in optical microscopy is critical for enabling high-throughput imaging across a wide range of biomedical applications. Among the essential components of automated systems, robust autofocusing plays a pivotal role in maintaining image quality for both single-plane and volumetric imaging. However, conventional autofocusing methods often struggle with implementation complexity, limited generalizability across sample types, incompatibility with thick specimens, and slow feedback. We observed that the digitally summed Fourier spectrum of two images acquired from two-angle illumination exhibits interference-like fringe modulation when the sample is defocused. These digital fringes correlate directly with defocus through a physics-based relation. Based on this principle, we developed an automatic, efficient, and generalizable defocus detection method termed digital defocus aberration interference (DAbI). Implemented with a simple two-LED setup, DAbI can quantify the defocus distance over a range of 443 times the depth-of-field (DoF) for thin samples and 296 times for thick specimens. It can additionally extend the natural DoF of the imaging system by 20 folds when integrated with complex-field imaging. We demonstrated the versatile applications of DAbI on brightfield, complex-field, refractive index, confocal, and widefield fluorescence imaging, establishing it as a promising solution for automated, high-throughput optical microscopy.

physics.optics↗

arXiv2025

Analytic Fourier ptychotomography for volumetric refractive index imaging

Three-dimensional (3D) refractive index (RI) tomography offers label-free, quantitative volumetric imaging but faces limitations due to optical aberrations, limited resolution, and the computational complexity inherent to existing approaches. To overcome these barriers, we propose Analytic Fourier Ptychotomography (AFP), a new computational microscopy technique that analytically reconstructs aberration-free, complex-valued 3D RI distributions without iterative optimization or axial scanning. AFP incorporates a new concept called the finite sample thickness (FST) prior, and analytically solves the inverse scattering problem through three sequential steps: complex-field reconstruction via the Kramers-Kronig relation, linear aberration correction using overlapping spectra, and analytic spectrum extension into the darkfield region. Unlike iterative reconstruction methods, AFP does not require parameter tuning or computationally intensive optimizations, which are often error-prone and non-generalizable. We experimentally demonstrate that AFP significantly enhances image quality and resolution under various aberration conditions across a range of applications. AFP corrected aberrations associated with 25 Zernike modes (with a maximal phase difference of 2.3$π$ and maximal Zernike coefficient value of 4), extended the synthetic numerical aperture from 0.41 to 0.99, and provided a two-fold resolution enhancement in all directions. AFP's simplicity and robustness make it an attractive imaging technology for quantitative 3D analysis in biological, microbial ecological, and medical studies.

physics.optics↗

arXiv2025

Five-dimensional single-shot fluorescence imaging using a polarized Fourier light-field microscope

Single-shot fluorescence imaging techniques have gained increasing interest in recent years due to their ability to rapidly capture complex biological data without the need for extensive scanning. In this letter, we introduce polarized Fourier light field microscopy (pFLFM), a novel fluorescence imaging technique that captures five-dimensional information (3D intensity and 2D polarization) in a single snapshot. This technique combines a polarization camera with an FLFM setup, significantly improving data acquisition efficiency. We experimentally validated the pFLFM system using a fluorescent Siemens star, demonstrating consistent resolution and an extended depth of field across various polarizations. Using the 5D imaging capabilities of pFLFM, we imaged plant roots and uncovered unique heterogeneities in cellulose fibril configurations across various root sections. These results not only highlight the potential of pFLFM in biological and environmental sciences, but also represent a significant advancement in the design of single-shot fluorescence imaging systems.

physics.optics↗

arXiv2025

Single-shot volumetric fluorescence imaging with neural fields

Single-shot volumetric fluorescence (SVF) imaging offers a significant advantage over traditional imaging methods that require scanning across multiple axial planes as it can capture biological processes with high temporal resolution. The key challenges in SVF imaging include requiring sparsity constraints, eliminating depth ambiguity in the reconstruction, and maintaining high resolution across a large field of view. In this paper, we introduce the QuadraPol point spread function (PSF) combined with neural fields, a novel approach for SVF imaging. This method utilizes a custom polarizer at the back focal plane and a polarization camera to detect fluorescence, effectively encoding the 3D scene within a compact PSF without depth ambiguity. Additionally, we propose a reconstruction algorithm based on the neural fields technique that provides improved reconstruction quality compared to classical deconvolution methods. QuadraPol PSF, combined with neural fields, significantly reduces the acquisition time of a conventional fluorescence microscope by approximately 20 times and captures a 100 mm$^3$ cubic volume in one shot. We validate the effectiveness of both our hardware and algorithm through all-in-focus imaging of bacterial colonies on sand surfaces and visualization of plant root morphology. Our approach offers a powerful tool for advancing biological research and ecological studies.

physics.optics↗

arXiv2024

Length-scale study in deep learning prediction for non-small cell lung cancer brain metastasis

Deep learning assisted digital pathology has the potential to impact clinical practice in significant ways. In recent studies, deep neural network (DNN) enabled analysis outperforms human pathologists. Increasing sizes and complexity of the DNN architecture generally improves performance at the cost of DNN's explainability. For pathology, this lack of DNN explainability is particularly problematic as it hinders the broader clinical interpretation of the pathology features that may provide physiological disease insights. To better assess the features that DNN uses in developing predictive algorithms to interpret digital microscopic images, we sought to understand the role of resolution and tissue scale and here describe a novel method for studying the predictive feature length-scale that underpins a DNN's predictive power. We applied the method to study a DNN's predictive capability in the case example of brain metastasis prediction from early-stage non-small-cell lung cancer biopsy slides. The study highlights the DNN attention in the brain metastasis prediction targeting both cellular scale (resolution) and tissue scale features on H&E-stained histological whole slide images. At the cellular scale, we see that DNN's predictive power is progressively increased at higher resolution (i.e., lower resolvable feature length) and is largely lost when the resolvable feature length is longer than 5 microns. In addition, DNN uses more macro-scale features (maximal feature length) associated with tissue organization/architecture and is optimized when assessing visual fields larger than 41 microns. This study for the first time demonstrates the length-scale requirements necessary for optimal DNN learning on digital whole slide images.

eess.IV↗

arXiv2021

Single-molecule orientation localization microscopy I: fundamental limits

Precisely measuring the three-dimensional position and orientation of individual fluorophores is challenging due to the substantial photon shot noise in single-molecule experiments. Facing this limited photon budget, numerous techniques have been developed to encode 2D and 3D position and 2D and 3D orientation information into fluorescence images. In this work, we adapt classical and quantum estimation theory and propose a mathematical framework to derive the best possible precision for measuring the position and orientation of dipole-like emitters for any fixed imaging system. We find that it is impossible to design an instrument that achieves the maximum sensitivity limit for measuring all possible rotational motions. Further, our vectorial dipole imaging model shows that the best quantum-limited localization precision is ~4-8% worse than that suggested by a scalar monopole model. Overall, we conclude that no single instrument can be optimized for maximum precision across all possible 2D and 3D localization and orientation measurement tasks.

physics.optics↗

arXiv2021

Single-molecule orientation localization microscopy II: a performance comparison

Various techniques have been developed to measure the 2D and 3D positions and 2D and 3D orientations of fluorescent molecules with improved precision over standard epifluorescence microscopes. Due to the challenging signal-to-background ratio in typical single-molecule experiments, it is essential to choose an imaging system optimized for the specific target sample. In this work, we compare the performance of multiple state-of-the-art and commonly used methods for orientation localization microscopy against the fundamental limits of measurement precision. Our analysis reveals optimal imaging methods for various experiment conditions and sample geometries. Interestingly, simple modifications to the standard fluorescence microscope exhibit superior performance in many imaging scenarios.

physics.optics↗

arXiv2020

Quantum limits for precisely estimating the orientation and wobble of dipole emitters

Precisely measuring molecular orientation is key to understanding how molecules organize and interact in soft matter, but the maximum theoretical limit of measurement precision has yet to be quantified. We use quantum estimation theory and Fisher information (QFI) to derive a fundamental bound on the precision of estimating the orientations of rotationally fixed molecules. While direct imaging of the microscope pupil achieves the quantum bound, it is not compatible with widefield imaging, so we propose an interferometric imaging system that also achieves QFI-limited measurement precision. Extending our analysis to rotationally diffusing molecules, we derive conditions that enable a subset of second-order dipole orientation moments to be measured with quantum-limited precision. Interestingly, we find that no existing techniques can measure all second moments simultaneously with QFI-limited precision; there exists a fundamental trade-off between precisely measuring the mean orientation of a molecule versus its wobble. This theoretical analysis provides crucial insight for optimizing the design of orientation-sensitive imaging systems.

physics.optics↗

arXiv2019

Fundamental Limits on Measuring the Rotational Constraint of Single Molecules using Fluorescence Microscopy

Optical fluorescence imaging is capable of measuring both the spatial and rotational dynamics of single molecules. However, unavoidable measurement noise will result in inaccurate estimates of rotational dynamics, causing a molecule to appear to be more rotationally constrained than it actually is. We report a mathematical framework to compute the fundamental limit of accuracy in measuring the rotational mobility of dipole-like emitters. By applying our framework to both in-plane and three-dimensional methods, we provide a means to choose the optimal orientation-measurement technique based on experimental conditions.

physics.optics↗

arXiv2019

Dense Super-Resolution Imaging of Molecular Orientation via Joint Sparse Basis Deconvolution and Spatial Pooling

In single-molecule super-resolution microscopy, engineered point-spread functions (PSFs) are designed to efficiently encode new molecular properties, such as 3D orientation, into complex spatial features captured by a camera. To fully benefit from their optimality, algorithms must estimate multi-dimensional parameters such as molecular position and orientation in the presence of PSF overlap and model-experiment mismatches. Here, we present a novel joint sparse deconvolution algorithm based on the decomposition of fluorescence images into six basis images that characterize molecular orientation. The proposed algorithm exploits a group-sparsity structure across these basis images and applies a pooling strategy on corresponding spatial features for robust simultaneous estimates of the number, brightness, 2D position, and 3D orientation of fluorescent molecules. We demonstrate this method by imaging DNA transiently labeled with the intercalating dye YOYO-1. Imaging the position and orientation of each molecule reveals orientational order and disorder within DNA with nanoscale spatial precision.

eess.IV↗