Efficient illumination angle self-calibration in Fourier ptychography

Eckert, Regina; Phillips, Zachary F.; Waller, Laura

doi:10.1364/ao.57.005434

Cited by 99 publications

(67 citation statements)

References 44 publications

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“…The Fourier transforms demonstrate that the spatial-frequency information is mostly contained within two circular regions in Fourier space, symmetrically positioned around the origin. This is expected for intensity-based imaging of weakly-scattering objects with off-axis illumination [35,43] (see Supplementary Information for details).…”

Section: B Data Acquisitionmentioning

confidence: 79%

“…In the main text, we note that the Fourier amplitude of an intensity measurement of a single scattering sample under angular illumination contains two distinct circles in Fourier space [43]. These two circles are symmetrically positioned in Fourier space around the origin.…”

Section: Supplementary Informationmentioning

confidence: 90%

“…Thus, we instead use postacquisition algorithmic angle-calibration as our means for precise angle measurement. We leverage previous developments in self-calibration to precisely estimate the incident illumination angles from the raw measurements [43]. Fig.…”

Section: Calibration Of Angular Illuminationsmentioning

confidence: 99%

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High-resolution 3D refractive index microscopy of multiple-scattering samples from intensity images

Chowdhury

Chen

Eckert

et al. 2019

Optica

Self Cite

152

103

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Optical diffraction tomography (ODT) reconstructs a sample's volumetric refractive index (RI) to create high-contrast, quantitative 3D visualizations of biological samples. However, standard implementations of ODT use interferometric systems, and so are sensitive to phase instabilities, complex mechanical design, and coherent noise. Furthermore, their reconstruction framework is typically limited to weaklyscattering samples, and thus excludes a whole class of multiple-scattering samples. Here, we implement a new 3D RI microscopy technique that utilizes a computational multi-slice beam propagation method to invert the optical scattering process and reconstruct high-resolution (NA>1.0) 3D RI distributions of multiple-scattering samples. The method acquires intensity-only measurements from different illumination angles, and then solves a non-linear optimization problem to recover the sample's 3D RI distribution. We experimentally demonstrate reconstruction of samples with varying amounts of multiple scattering: a 3T3 fibroblast cell, a cluster of C. elegans embryos, and a whole C. elegans worm, with lateral and axial resolutions of ≤250 nm and ≤900 nm, respectively. for text or data mining, so long as such uses are for non-commercial purposes and appropriate attribution is maintained. All other rights are reserved. Fluorescent imaging has enabled stunning visualizations of biological processes at a variety of size scales and resolutions, for studies of gene expression, protein interactions, intracellular dynamics, etc [1][2][3][4]. However, the fluorescent techniques require exogenous biological labels, and so do not directly give endogenous information about a sample's biological structure.Optical diffraction tomography (ODT) also targets 3D biological imaging. In contrast to fluorescent methods, ODT avoids the use of exogenous biological labels, and instead utilizes the intrinsic optical variation within a sample to reconstruct its 3D refractive-index (RI) distribution [5][6][7][8][9][10][11]. Hence, ODT avoids some of fluorescent imaging's main drawbacks, such as photobleaching, slow acquisition speed, low signal-to-noise (SNR) ratio, and complex samplepreparation protocol. Furthermore, RI imaging enables examination of the structural, mechanical, and biochemical properties of a sample, which are important for studies in morphology, mass, shear stiffness, and spectroscopy [9,[12][13][14][15].Standard implementations of ODT use either a rotating sample or a scanning laser beam to capture the angle-specific scattering arising from the sample [5,7,[16][17][18]. Under the assumption of weak scattering (i.e., 1st Born or Rytov approximations), 2D electric-field measurements directly yield information about the sample's 3D scattering potential [19][20][21]. Standard ODT reconstruction algorithms utilize the Fourier diffraction theorem to project the information contained in each electric-field measurement onto spherical shells (i.e., Ewald surfaces) in the 3D Fourier space of the sample's scattering potential [22,23]. ...

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Section: B Data Acquisitionmentioning

confidence: 79%

Section: Supplementary Informationmentioning

confidence: 90%

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High-resolution 3D refractive index microscopy of multiple-scattering samples from intensity images

Chowdhury

Chen

Eckert

et al. 2019

Optica

Self Cite

152

103

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“…Recently, motion-free IDT techniques have been demonstrated by our group allowing 3D RI information recovery using oblique illumination-only intensity measurements without any mechanical scanning. While lasers coupled with DMDs, galvanometers, and other programmable sources have been used for scan-free oblique illumination [15,28,36], we equip a standard brightfield microscope with a ring LED array. The LED array provides a low-cost illumination source easily adoptable for biological research that avoids the speckle artifacts present with coherent lasers.…”

Section: Introductionmentioning

confidence: 99%

High-speed in vitro intensity diffraction tomography

Li¹,

Matlock²,

Li³

et al. 2019

Advanced Optical Imaging Technologies II

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We demonstrate a label-free, scan-free intensity diffraction tomography technique utilizing annular illumination (aIDT) to rapidly characterize large-volume 3D refractive index distributions in vitro. By optimally matching the illumination geometry to the microscope pupil, our technique reduces the data requirement by 60× to achieve highspeed 10 Hz volume rates. Using 8 intensity images, we recover ∼ 350 × 100 × 20µm 3 volumes with near diffraction-limited lateral resolution of 487 nm and axial resolution of 3.4 µm. Our technique's large volume rate and high resolution enables 3D 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 macro-scale 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 our aIDT system to highlight the accuracy and sensitivity of our technique. aIDT shows promise as a powerful high-speed, label-free computational microscopy technique applications where natural imaging is required to evaluate environmental effects on a sample in real-time. We provide example datasets and an open source implementation of aIDT at https://github.com/bu-cisl/IDT-using-Annular-Illumination.

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“…In our case, the gradient of the output neuron (i.e the defocus prediction) was computed with respect to the the Fourier transform magnitude. Averaging the magnitude of the gradient image over many examples clearly shows that the network recognizes specific parts of the the overlapping two-circle structure [5] that is typical for an image formed by coherent off-axis illumination (Fig. 3c).…”

Section: Spatial Frequencymentioning

confidence: 93%

Single-shot autofocus microscopy using deep learning

Pinkard

Phillips

Babakhani

et al. 2019

Preprint

Self Cite

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Maintaining an in-focus image over long time scales is an essential and non-trivial task for a variety of microscopic imaging applications. Here, we present an autofocusing method that is inexpensive, fast, and robust. It requires only the addition of one or a few off-axis LEDs to a conventional transmitted light microscope. Defocus distance can be estimated and corrected based on a single image under this LED illumination using a neural network that is small enough to be trained on a desktop CPU in a few hours. In this work, we detail the procedure for generating data and training such a network, explore practical limits, and describe relevant design principles governing the illumination source and network architecture.

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Efficient illumination angle self-calibration in Fourier ptychography

Cited by 99 publications

References 44 publications

High-resolution 3D refractive index microscopy of multiple-scattering samples from intensity images

High-resolution 3D refractive index microscopy of multiple-scattering samples from intensity images

High-speed in vitro intensity diffraction tomography

Single-shot autofocus microscopy using deep learning

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