Imaging without lenses: achievements and remaining challenges of wide-field on-chip microscopy

Greenbaum, Alon; Luo, Weili; Su, Ting‐Wei; Gӧrӧcs, Zoltán; Li, Xue; Isikman, Serhan O.; Coşkun, Ahmet F.; Mudanyali, Onur; Ozcan, Aydogan

doi:10.1038/nmeth.2114

Cited by 494 publications

(351 citation statements)

References 60 publications

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“…[30][31][32][33][34][35][36][37][38][39][40] To date, a number of optical techniques have been proposed for point-of-care diagnostics such as in vitro optical devices, [41][42][43][44][45][46][47][48][49][50][51][52][53] including portable optical imaging systems, optical microscopes integrated to cell phones or in vivo optical devices, [54][55][56][57][58][59][60][61][62][63] involving confocal microscopy, microendoscopy and optical coherence tomography techniques. Among these approaches, lens-free computational on-chip imaging 64 has been an emerging technique that can eliminate the need for bulky and costly optical components while also preserving (or even enhancing in certain cases) the image resolution, field of view and sensitivity. In this on-chip microscopy platform, computational holographic reconstruction and phase recovery methods are used to partially eliminate diffraction effects, providing higher resolution microscopic images across very large imaging areas, e.g., .20-30 mm 2 using off-the-shelf CMOS (Complementary Metal-Oxide-Semiconductor) imager chips.…”

Section: Introductionmentioning

confidence: 99%

Handheld high-throughput plasmonic biosensor using computational on-chip imaging

et al. 2014

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We demonstrate a handheld on-chip biosensing technology that employs plasmonic microarrays coupled with a lens-free computational imaging system towards multiplexed and high-throughput screening of biomolecular interactions for point-of-care applications and resource-limited settings. This lightweight and field-portable biosensing device, weighing 60 g and 7.5 cm tall, utilizes a compact optoelectronic sensor array to record the diffraction patterns of plasmonic nanostructures under uniform illumination by a single-light emitting diode tuned to the plasmonic mode of the nanoapertures. Employing a sensitive plasmonic array design that is combined with lens-free computational imaging, we demonstrate label-free and quantitative detection of biomolecules with a protein layer thickness down to 3 nm. Integrating large-scale plasmonic microarrays, our on-chip imaging platform enables simultaneous detection of protein mono-and bilayers on the same platform over a wide range of biomolecule concentrations. In this handheld device, we also employ an iterative phase retrieval-based image reconstruction method, which offers the ability to digitally image a highly multiplexed array of sensors on the same plasmonic chip, making this approach especially suitable for high-throughput diagnostic applications in field settings.

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Section: Introductionmentioning

confidence: 99%

Handheld high-throughput plasmonic biosensor using computational on-chip imaging

et al. 2014

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“…2,3 In microscopy, these systems were also realized in a more compact way, by developing lens-free devices to record holographic patterns. [4][5][6][7] Although the features of wide-field digital holography have confirmed this technique as a relevant tool for imaging, only recently this method has been implemented in optical scanning microscopy. 8 In the latter, named synthetic optical holography (SOH), a point detector is employed, replacing CCD cameras, in order to encode the phase across the whole image.…”

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confidence: 99%

Synthetic holography based on scanning microcavity

Donato

Farina

2015

AIP Advances

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Synthetic optical holography (SOH) is an imaging technique, introduced in scanning microscopy to record amplitude and phase of a scattered field from a sample. In this paper, it is described a novel implementation of SOH through a lens-free low-coherence system, based on a scanning optical microcavity. This technique combines the low-coherence properties of the source with the mutual interference of scattered waves and the resonant behavior of a micro-cavity, in order to realize a high sensitive imaging system. Micro-cavity is compact and realized by approaching a cleaved optical fiber to the sample. The scanning system works in an open-loop configuration without the need for a reference wave, usually required in interferometric systems. Measurements were performed over calibration samples and a lateral resolution of about 1 μm is achieved by means of an optical fiber with a Numerical Aperture (NA) equal to 0.1 and a Mode Field Diameter (MDF) of 5.6 μm.

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“…We also evaluate the performance of a robust estimation performed jointly over several consecutive frames (super-resolution). In these examples, the image formation model m θ is non-linear with respect to the parameters θ, as given by equation (1). As a result, the minimization problem (2) and each IRLS iteration in (4) is solved using a few iterations of Levenberg-Marquardt algorithm.…”

Section: Application To Lensless Microscopy Videosmentioning

confidence: 99%

“…It is already used in several fields where the accurate estimation of 3D location and size over time is crucial, such as in the study of fluid flows or biomedical imaging [1].…”

Section: Introductionmentioning

confidence: 99%

Robust object characterization from lensless microscopy videos

Flasseur

Dénis

Fournier

et al. 2017

2017 25th European Signal Processing Conference (EUSIPCO)

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Abstract-Lensless microscopy, also known as in-line digital holography, is a 3D quantitative imaging method used in various fields including microfluidics and biomedical imaging. To estimate the size and 3D location of microscopic objects in holograms, maximum likelihood methods have been shown to outperform traditional approaches based on 3D image reconstruction followed by 3D image analysis. However, the presence of objects other than the object of interest may bias maximum likelihood estimates. Using experimental videos of holograms, we show that replacing the maximum likelihood with a robust estimation procedure reduces this bias. We propose a criterion based on the intersection of confidence intervals in order to automatically set the level that distinguishes between inliers and outliers. We show that this criterion achieves a bias / variance trade-off. We also show that joint analysis of a sequence of holograms using the robust procedure is shown to further improve estimation accuracy.

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Imaging without lenses: achievements and remaining challenges of wide-field on-chip microscopy

Cited by 494 publications

References 60 publications

Handheld high-throughput plasmonic biosensor using computational on-chip imaging

Handheld high-throughput plasmonic biosensor using computational on-chip imaging

Synthetic holography based on scanning microcavity

Robust object characterization from lensless microscopy videos

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