Single-frame 3D fluorescence microscopy with ultraminiature lensless FlatScope

Adams, Jesse K.; Boominathan, Vivek; Avants, Benjamin W.; Vercosa, Daniel G.; Ye, Fan; Baraniuk, Richard G.; Robinson, Jacob T.; Veeraraghavan, Ashok

doi:10.1126/sciadv.1701548

Cited by 165 publications

(121 citation statements)

References 37 publications

(42 reference statements)

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“…The 3D printed frame can be modified to incorporate mounting features to precisely attach miniaturized microscopes 54 and devices for wirelessly infusing pharmacological agents or performing optogenetic stimulations 55 . Recently, ultra-miniaturized lens-less fluorescence microscopes with thickness less than 1 mm have been developed 56 . Engineering See-Shells embedded with these miniaturized lens-less imaging systems offers the possibility of volumetrically mapping the activity of the whole cortex during freely moving animals.…”

Section: Discussionmentioning

confidence: 99%

Cortex-wide neural interfacing via transparent polymer skulls

Ghanbari

Carter

Rynes

et al. 2018

Preprint

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Neural computations occurring simultaneously in multiple cerebral cortical regions are critical for mediating cognition, perception and sensorimotor behaviors. Enormous progress has been made in understanding how neural activity in specific cortical regions contributes to behavior. However, there is a lack of tools that allow simultaneous monitoring and perturbing neural activity from multiple cortical regions. To fill this need, we have engineered "See-Shells" -digitally designed, morphologically realistic, transparent polymer skulls that allow long-term (>200 days) optical access to 45 mm 2 of the dorsal cerebral cortex in the mouse. We demonstrate the ability to perform mesoscopic imaging, as well as cellular and subcellular resolution two-photon imaging of neural structures up to 600 µm through the See-Shells. See-Shells implanted on transgenic mice expressing genetically encoded calcium (Ca 2+ ) indicators allow tracking of neural activities from multiple, non-contiguous regions spread across millimeters of the cortex. Further, neural probes can access the brain through perforated See-Shells, either for perturbing or recording neural activity from localized brain regions simultaneously with whole cortex imaging. As See-Shells can be constructed using readily available desktop fabrication tools and modified to fit a range of skull geometries, they provide a powerful tool for investigating brain structure and function.

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Section: Discussionmentioning

confidence: 99%

Cortex-wide neural interfacing via transparent polymer skulls

Ghanbari

Carter

Rynes

et al. 2018

Preprint

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“…The 3D lensless imaging problem has also recently been studied in [5], [11], [13], [14]. These methods can broadly be divided into two categories.…”

Section: Related Workmentioning

confidence: 99%

“…In the first category, the 3D scene is divided into a finite number of voxels. To recover the 3D light distribution, these methods solve an 1 normbased recovery problem under the assumption that the scene is very sparse [13], [14]. In the second category, the 3D scene is divided into an intensity map and multiple depth planes such that each pixel is assigned one intensity and depth.…”

Section: Related Workmentioning

confidence: 99%

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Image and Depth Estimation with Mask-Based Lensless Cameras

Zheng

Asif

2019

2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)

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Mask-based lensless cameras replace the lens of a conventional camera with a customized mask. These cameras can potentially be very thin and even flexible. Recently, it has been demonstrated that such mask-based cameras can recover light intensity and depth information of a scene. Existing depth recovery algorithms either assume that the scene consists of a small number of depth planes or solve a sparse recovery problem over a large 3D volume. Both these approaches fail to recover scene with large depth variations. In this paper, we propose a new approach for depth estimation based on alternating gradient descent algorithm that jointly estimates a continuous depth map and light distribution of the unknown scene from its lensless measurements. The computational complexity of the algorithm scales linearly with the spatial dimension of the imaging system. We present simulation results on image and depth reconstruction for a variety of 3D test scenes. A comparison between the proposed algorithm and other method shows that our algorithm is faster and more robust for natural scenes with a large range of depths.

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“…SVIM improves on conventional LFM by optimizing the illumination pathway, and thus is fully compatible with recent innovations in the detection pathway of LFM, via manipulation the phase content of the detected light field 44,45 or capturing the light field at the image plane 33 . LFM belongs to an emerging class of computational imaging techniques that utilize the power of physical modeling, signal processing, and computation to enable new performance space beyond conventional microscopy 34,37,[46][47][48] .…”

mentioning

confidence: 99%

Selective volume illumination microscopy offers synchronous volumetric imaging with high contrast

Truong

Holland²,

Madaan

et al. 2018

Preprint

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Light field microscopy provides an efficient means to collect 3D images in a single acquisition, as its plenoptic detection captures an extended image volume in one snapshot. The ability of light field microscopy to simultaneously capture image data from a volume of interest, such as a functioning brain or a beating heart, is compromised by inadequate contrast and effective resolution, due, in large part, to light scattering by the tissue. Surprisingly, a major contribution to the image degradation is the signal scattered into the volume of interest by the typical wide-field illumination that excites the sample region outside the volume of interest. Here, we minimize this degradation by employing selective volume illumination, using a modified light sheet approach to illuminate preferentially the volume of interest. This minimizes the unavoidable background generated when extraneous regions of the sample are illuminated, dramatically enhancing the contrast and effective resolution of the captured and reconstructed images. Light Field Selective Volume Illumination Microscopy (LF-SVIM, SVIM for short) dramatically improves the performance of light field microscopy, and offers an unprecedented combination of synchronous z-depth coverage, lateral and axial resolution, and imaging speed.

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Single-frame 3D fluorescence microscopy with ultraminiature lensless FlatScope

Abstract: FlatScope, a lensless microscope as thin as a credit card and small enough to sit on a fingertip, captures 3D fluorescence images.

Cited by 165 publications

References 37 publications

Cortex-wide neural interfacing via transparent polymer skulls

Cortex-wide neural interfacing via transparent polymer skulls

Image and Depth Estimation with Mask-Based Lensless Cameras

Selective volume illumination microscopy offers synchronous volumetric imaging with high contrast

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