Quasi-Dome: A Self-Calibrated High-NA LED Illuminator for Fourier Ptychography

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

doi:10.1364/isa.2017.iw4e.5

Cited by 26 publications

(31 citation statements)

References 7 publications

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“…Techniques such as multi-aperture Fourier ptychography [32,33] can further increase throughput, as is essential for fast biological processes. Reduced image-acquisition times are also facilitated by replacement of the planar LED array with a dome-shaped array [34], where all LEDs are oriented towards the sample offering improved illumination efficiency. Lastly a further factor of 6 increase in data acquisition speeds could be achieved by removing the high latency introduced during sequential read-out of our CMOS cameras.…”

Section: Discussionmentioning

confidence: 99%

Low-cost, sub-micron resolution, wide-field computational microscopy using opensource hardware

Aidukas

Eckert

Harvey

et al. 2018

Preprint

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Low-cost, sub-micron resolution, wide-field 1 computational microscopy using opensource 2 hardware 3 4 ABSTRACT 11 The revolution in low-cost consumer photography and computation provides fertile 12 opportunity for a disruptive reduction in the cost of biomedical imaging. Conventional 13 approaches to low-cost microscopy are fundamentally restricted, however, to modest field of 14 view (FOV) and/or resolution. We report a low-cost microscopy technique, implemented with 15a Raspberry Pi single-board computer and color camera combined with Fourier ptychography 16 (FP), to computationally construct 25-megapixel images with sub-micron resolution. New 17 image-construction techniques were developed to enable the use of the low-cost Bayer color 18 sensor, to compensate for the highly aberrated re-used camera lens and to compensate for 19 misalignments associated with the 3D-printed microscope structure. This high ratio of 20 performance to cost is of particular interest to high-throughput microscopy applications, 21 ranging from drug discovery and digital pathology to health screening in low-income countries. 22 3D models and assembly instructions of our microscope are made available for open source 23 use. 24 405 Instructions to build a Raspberry Pi 406 Fourier ptychographic computational 407 microscope 408This document provides instructions to build a low-cost computational microscope reported in 409 the manuscript: "Low-cost, sub-micron resolution, wide-field computational microscopy with 410Raspberry Pi hardware". The CAD files and data acquisition codes can be downloaded from 411

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Section: Discussionmentioning

confidence: 99%

Low-cost, sub-micron resolution, wide-field computational microscopy using opensource hardware

Aidukas

Eckert

Harvey

et al. 2018

Preprint

Self Cite

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“…Increased resolution/SBP Aperture synthesis [1,[21][22][23][24] Phase imaging Phase retrieval [25][26][27][28][29] Digital refocusing Phase retrieval [1,27,30] Aberration correction EPRY [24,[31][32][33] Long working distance low NA objective [34,35] Sub-λ imaging high-angle illumination [21][22][23]34,36,37] Multimodal imaging scanning illumination angle [24,34,38] High-speed LED & camera multiplexing [26,[39][40][41][42][43][44][45] Compact and portable Novel hardware [33,46,47] 3D imaging light field, 1st Born, multislice [48][49][50][51][52][53][54][55][56] computation using low numerical aperture (NA) op...…”

Section: Achieved By Referencesmentioning

confidence: 99%

Fourier ptychography: current applications and future promises

et al. 2020

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Traditional imaging systems exhibit a well-known trade-off between the resolution and the field of view of their captured images. Typical cameras and microscopes can either "zoom in" and image at high-resolution, or they can "zoom out" to see a larger area at lower resolution, but can rarely achieve both effects simultaneously. In this review, we present details about a relatively new procedure termed Fourier ptychography (FP), which addresses the above trade-off to produce gigapixel-scale images without requiring any moving parts. To accomplish this, FP captures multiple low-resolution, large field-of-view images and computationally combines them in the Fourier domain into a high-resolution, large field-of-view result. Here, we present details about the various implementations of FP and highlight its demonstrated advantages to date, such as aberration recovery, phase imaging, and 3D tomographic reconstruction, to name a few. After providing some basics about FP, we list important details for successful experimental implementation, discuss its relationship with other computational imaging techniques, and point to the latest advances in the field while highlighting persisting challenges.

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“…Finally, we analyze the choice of illumination on our defocus prediction network performance. Since our setup has a programmable illumina-tor [13], we can choose the source patterns at will. First, using one LED at a time, we tested how the angle of single-LED illumination affected performance ( Fig.…”

Section: Spatial Frequencymentioning

confidence: 99%

“…The central idea of our method is that a neural network can be trained to predict focus from a single image taken under coherent or nearly coherent illumination at arbitrary focus relative to the sample. Data were collected using a Zeiss Axio Observer microscope (20× 0.5 NA objective lens) with the illumination source replaced by a quasi-dome LED-array [13]. To train and validate our method, focal stacks were collected using Micro-Magellan [14] as software control of the microscope.…”

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confidence: 99%

Single-shot autofocus microscopy using deep learning

Pinkard

Phillips

Babakhani

et al. 2019

Preprint

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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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Quasi-Dome: A Self-Calibrated High-NA LED Illuminator for Fourier Ptychography

Cited by 26 publications

References 7 publications

Low-cost, sub-micron resolution, wide-field computational microscopy using opensource hardware

Low-cost, sub-micron resolution, wide-field computational microscopy using opensource hardware

Fourier ptychography: current applications and future promises

Single-shot autofocus microscopy using deep learning

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