First born model for reflection-mode Fourier ptychographic microscopy

We validate a first Born approximation based model for Reflection-mode Fourier ptychography under the semi-infinite boundary condition. Our model enables optical thickness and absorption recovery with enhanced resolution from thin samples.Published versio

High-throughput, volumetric quantitative phase imaging with multiplexed intensity diffraction tomography.

Intensity diffraction tomography (IDT) provides quantitative, volumetric refractive index reconstructions of unlabeled biological samples from intensity-only measurements. IDT is scanless and easily implemented in standard optical microscopes using an LED array but suffers from large data requirements and slow acquisition speeds. Here, we develop multiplexed IDT (mIDT), a coded illumination framework providing high volume-rate IDT for evaluating dynamic biological samples. mIDT combines illuminations from an LED grid using physical model-based design choices to improve acquisition rates and reduce dataset size with minimal loss to resolution and reconstruction quality. We analyze the optimal design scheme with our mIDT framework in simulation using the reconstruction error compared to conventional IDT and theoretical acquisition speed. With the optimally determined mIDT scheme, we achieve hardware-limited 4Hz acquisition rates enabling 3D refractive index distribution recovery on live Caenorhabditis elegans worms and embryos as well as epithelial buccal cells. Our mIDT architecture provides a 60 × speed improvement over conventional IDT and is robust across different illumination hardware designs, making it an easily adoptable imaging tool for volumetrically quantifying biological samples in their natural state.https://www.osapublishing.org/boe/abstract.cfm?uri=boe-10-12-6432Published versio

Inverse scattering for reflection intensity phase microscopy

Reflection phase imaging provides label-free, high-resolution characterization of biological samples, typically using interferometric-based techniques. Here, we investigate reflection phase microscopy from intensity-only measurements under diverse illumination. We evaluate the forward and inverse scattering model based on the first Born approximation for imaging scattering objects above a glass slide. Under this design, the measured field combines linear forward-scattering and height-dependent nonlinear back-scattering from the object that complicates object phase recovery. Using only the forward-scattering, we derive a linear inverse scattering model and evaluate this model's validity range in simulation and experiment using a standard reflection microscope modified with a programmable light source. Our method provides enhanced contrast of thin, weakly scattering samples that complement transmission techniques. This model provides a promising development for creating simplified intensity-based reflection quantitative phase imaging systems easily adoptable for biological research.https://arxiv.org/abs/1912.07709Accepted manuscrip

SIMBA: scalable inversion in optical tomography using deep denoising priors

Two features desired in a three-dimensional (3D) optical tomographic image reconstruction algorithm are the ability to reduce imaging artifacts and to do fast processing of large data volumes. Traditional iterative inversion algorithms are impractical in this context due to their heavy computational and memory requirements. We propose and experimentally validate a novel scalable iterative mini-batch algorithm (SIMBA) for fast and high-quality optical tomographic imaging. SIMBA enables highquality imaging by combining two complementary information sources: the physics of the imaging system characterized by its forward model and the imaging prior characterized by a denoising deep neural net. SIMBA easily scales to very large 3D tomographic datasets by processing only a small subset of measurements at each iteration. We establish the theoretical fixedpoint convergence of SIMBA under nonexpansive denoisers for convex data-fidelity terms. We validate SIMBA on both simulated and experimentally collected intensity diffraction tomography (IDT) datasets. Our results show that SIMBA can significantly reduce the computational burden of 3D image formation without sacrificing the imaging quality.https://arxiv.org/abs/1911.13241First author draf

Model and learning-based strategies for intensity diffraction tomography

Intensity Diffraction Tomography (IDT) is a recently developed quantitative phase imaging tool with significant potential for biological imaging applications. This modality captures intensity images from a scattering sample under diverse illumination and reconstructs the object's volumetric permittivity contrast using linear inverse scattering models. IDT requires no through-focus sample scans or exogenous contrast agents for 3D object recovery and can be easily implemented with a standard microscope equipped with an off-the-shelf LED array. These factors make IDT ideal for biological research applications where easily implementable setups providing native sample morphological information are highly desirable. Given this modality's recent development, IDT suffers from a number of limitations preventing its widespread adoption: 1) large measurement datasets with long acquisition times limiting its temporal resolution, 2) model-based constraints preventing the evaluation of multiple-scattering samples, and 3) low axial resolution preventing the recovery of fine axial structures such as organelles and other subcellular structures. These factors limit IDT to primarily thin, static objects, and its unknown accuracy and sensitivity metrics cast doubt on the technology's quantitative recovery of morphological features. This thesis addresses the limitations of IDT through advancements provided from model and learning-based strategies. The model-based advancements guide new computational illumination strategies for high volume-rate imaging as well as investigate new imaging geometries, while the learning-based enhancements to IDT present an efficient method for recovering multiple-scattering biological specimens. These advancements place IDT in the optimal position of being an easily implementable, computationally efficient phase imaging modality recovering high-resolution volumes of complex, living biological samples in their native state. We first discuss two illumination strategies for high-speed IDT. The first strategy develops a multiplexed illumination framework based on IDT's linear model enabling hardware-limited 4Hz volume-rate imaging of living biological samples. This implementation is hardware-agnostic, allowing for fast IDT to be added to any existing setup containing programmable illumination hardware. While sacrificing some reconstruction quality, this multiplexed approach recovers high-resolution features in live cell cultures, worms, and embryos highlighting IDT's potential across numerous ranges of biological imaging. Following this illumination scheme, we discuss a hardware-based solution for live sample imaging using ring-geometry LED arrays. Inspired from the linear model, this hardware modification optimally captures the object's information in each LED illumination allowing for high-quality object volumes to be reconstructed from as few as eight intensity images. This small image requirement allows IDT to achieve camera-limited 10Hz volume rate imaging of live biological samples without motion artifacts. We show the capabilities of this annular illumination IDT setup on live worm samples. This low-cost solution for IDT's speed shows huge implications for enabling any biological imaging lab to easily study the form and function of biological samples of interest in their native state. Next, we present a learning-based approach to expand IDT to recovering multiple-scattering samples. IDT's linear model provides efficient computation of an object's 3D volume but fails to recover quantitative information in the presence of highly scattering samples. We introduce a lightweight neural network architecture, trained only on simulated natural image-based objects, that corrects the linear model estimates and improves the recovery of both weakly and strongly scattering samples. This implementation maintains the computational efficiency of IDT while expanding its reconstruction capabilities allowing for more generic imaging of biological samples. Finally, we discuss an investigation of the IDT modality for reflection mode imaging. IDT traditionally captures only low axial resolution information because it cannot capture the backscattered fields from the object that contain rich information regarding the fine details of the object's axial structures. Here, we investigated whether a reflection-mode IDT implementation was possible for recovering high axial resolution structures from this backscattered light. We develop the model, imaging setup, and rigorously evaluate the reflection case in simulation and experiment to show the possibility for reflection IDT. While this imaging geometry ultimately requires a nonlinear model for 3D imaging, we show the technique provides enhanced sensitivity to the object's structures in a complementary fashion to transmission-based IDT

High-speed in vitro intensity diffraction tomography

We demonstrate a label-free, scan-free intensity diffraction tomography technique utilizing annular illumination (aIDT) to rapidly characterize large-volume three-dimensional (3-D) refractive index distributions in vitro. By optimally matching the illumination geometry to the microscope pupil, our technique reduces the data requirement by 60 times to achieve high-speed 10-Hz volume rates. Using eight intensity images, we recover volumes of ∼350 μm  ×  100 μm  ×  20  μm, with near diffraction-limited lateral resolution of   ∼  487  nm and axial resolution of   ∼  3.4  μm. The attained large volume rate and high-resolution enable 3-D quantitative phase imaging of complex living biological samples across multiple length scales. We demonstrate aIDT’s capabilities on unicellular diatom microalgae, epithelial buccal cell clusters with native bacteria, and live Caenorhabditis elegans specimens. Within these samples, we recover macroscale cellular structures, subcellular organelles, and dynamic micro-organism tissues with minimal motion artifacts. Quantifying such features has significant utility in oncology, immunology, and cellular pathophysiology, where these morphological features are evaluated for changes in the presence of disease, parasites, and new drug treatments. Finally, we simulate the aIDT system to highlight the accuracy and sensitivity of the proposed technique. aIDT shows promise as a powerful high-speed, label-free computational microscopy approach for applications where natural imaging is required to evaluate environmental effects on a sample in real time.https://arxiv.org/abs/1904.06004Accepted manuscrip

High-resolution Imaging of nanoparticles in wide-field interferometric scattering microscopy

Single particle interferometric scattering microscopy has demonstrated great capability in label-free imaging of sub-wavelength dielectric nanoparticles (r<25 nm); however, it suffers from diffraction-limited resolution. Here, we demonstrate ~2-fold improvement in lateral resolution upon asymmetric illumination.Published versio

Resolution-enhanced intensity diffraction tomography in high numerical aperture label-free microscopy

We propose label-free and motion-free resolution-enhanced intensity diffraction tomography (reIDT) recovering the 3D complex refractive index distribution of an object. By combining an annular illumination strategy with a high numerical aperture (NA) condenser, we achieve near-diffraction-limited lateral resolution of 346 nm and axial resolution of 1.2  μm over 130 μm×130 μm×8 μm volume. Our annular pattern matches the system’s maximum NA to reduce the data requirement to 48 intensity frames. The reIDT system is directly built on a standard commercial microscope with a simple LED array source and condenser lens adds-on, and promises broad applications for natural biological imaging with minimal hardware modifications. To test the capabilities of our technique, we present the 3D complex refractive index reconstructions on an absorptive USAF resolution target and Henrietta Lacks (HeLa) and HT29 human cancer cells. Our work provides an important step in intensity-based diffraction tomography toward high-resolution imaging applications.https://www.osapublishing.org/prj/fulltext.cfm?uri=prj-8-12-1818&id=442609Published versio

Bond-Selective Intensity Diffraction Tomography

Recovering molecular information remains a grand challenge in the widely used holographic and computational imaging technologies. To address this challenge, we developed a computational mid-infrared photothermal microscope, termed Bond-selective Intensity Diffraction Tomography (BS-IDT). Based on a low-cost brightfield microscope with an add-on pulsed light source, BS-IDT recovers both infrared spectra and bond-selective 3D refractive index maps from intensity-only measurements. High-fidelity infrared fingerprint spectra extraction is validated. Volumetric chemical imaging of biological cells is demonstrated at a speed of ~20 seconds per volume, with a lateral and axial resolution of ~350 nm and ~1.1 micron, respectively. BS-IDT's application potential is investigated by chemically quantifying lipids stored in cancer cells and volumetric chemical imaging on Caenorhabditis elegans with a large field of view (~100 micron X 100 micron)