Publications

@article{yanny2020,

title = {Miniscope3D: optimized single-shot miniature 3D fluorescence microscopy},

author = {Kyrollos Yanny and Nick Antipa and William Liberti and Sam Dehaeck and Kristina Monakhova and Fanglin Linda Liu and Konlin Shen and Ren Ng and Laura Waller},

url = {https://www.nature.com/articles/s41377-020-00403-7},

doi = {https://doi.org/10.1038/s41377-020-00403-7},

year  = {2020},

date = {2020-10-02},

journal = {Light: Science & Applications},

volume = {9},

number = {171},

abstract = {Miniature fluorescence microscopes are a standard tool in systems biology. However, widefield miniature microscopes capture only 2D information, and modifications that enable 3D capabilities increase the size and weight and have poor resolution outside a narrow depth range. Here, we achieve the 3D capability by replacing the tube lens of a conventional 2D Miniscope with an optimized multifocal phase mask at the objective’s aperture stop. Placing the phase mask at the aperture stop significantly reduces the size of the device, and varying the focal lengths enables a uniform resolution across a wide depth range. The phase mask encodes the 3D fluorescence intensity into a single 2D measurement, and the 3D volume is recovered by solving a sparsity-constrained inverse problem. We provide methods for designing and fabricating the phase mask and an efficient forward model that accounts for the field-varying aberrations in miniature objectives. We demonstrate a prototype that is 17 mm tall and weighs 2.5 grams, achieving 2.76 μm lateral, and 15 μm axial resolution across most of the 900 × 700 × 390 μm3 volume at 40 volumes per second. The performance is validated experimentally on resolution targets, dynamic biological samples, and mouse brain tissue. Compared with existing miniature single-shot volume-capture implementations, our system is smaller and lighter and achieves a more than 2× better lateral and axial resolution throughout a 10× larger usable depth range. Our microscope design provides single-shot 3D imaging for applications where a compact platform matters, such as volumetric neural imaging in freely moving animals and 3D motion studies of dynamic samples in incubators and lab-on-a-chip devices.},

keywords = {3D imaging, algorithms, diffuser, fluorescence imaging},

pubstate = {published},

tppubtype = {article}

}

@article{Monakhova:20b,

title = {Spectral DiffuserCam: lensless snapshot hyperspectral imaging with a spectral filter array},

author = {Kristina Monakhova and Kyrollos Yanny and Neerja Aggarwal and Laura Waller},

url = {http://www.osapublishing.org/optica/abstract.cfm?URI=optica-7-10-1298},

doi = {10.1364/OPTICA.397214},

year  = {2020},

date = {2020-10-01},

journal = {Optica},

volume = {7},

number = {10},

pages = {1298--1307},

publisher = {OSA},

abstract = {Hyperspectral imaging is useful for applications ranging from medical diagnostics to agricultural crop monitoring; however, traditional scanning hyperspectral imagers are prohibitively slow and expensive for widespread adoption. Snapshot techniques exist but are often confined to bulky benchtop setups or have low spatio-spectral resolution. In this paper, we propose a novel, compact, and inexpensive computational camera for snapshot hyperspectral imaging. Our system consists of a tiled spectral filter array placed directly on the image sensor and a diffuser placed close to the sensor. Each point in the world maps to a unique pseudorandom pattern on the spectral filter array, which encodes multiplexed spatio-spectral information. By solving a sparsity-constrained inverse problem, we recover the hyperspectral volume with sub-super-pixel resolution. Our hyperspectral imaging framework is flexible and can be designed with contiguous or non-contiguous spectral filters that can be chosen for a given application. We provide theory for system design, demonstrate a prototype device, and present experimental results with high spatio-spectral resolution.},

keywords = {algorithm, compressed sensing, diffuser, Hyperspectral imaging; Imaging systems; Optical components; Optical design; Spectral imaging; Systems design, Image reconstruction, Image sensors, Inverse problems, Sensors},

pubstate = {published},

tppubtype = {article}

}

@article{kuo2020chip,

title = {On-chip fluorescence microscopy with a random microlens diffuser},

author = { Grace Kuo and Fanglin Linda Liu and Irene Grossrubatscher and Ren Ng and Laura Waller},

url = {https://doi.org/10.1364/OE.382055},

doi = {10.1364/OE.382055},

year  = {2020},

date = {2020-03-09},

journal = {Optics Express},

volume = {28},

number = {6},

pages = {8384--8399},

publisher = {Optical Society of America},

keywords = {3D imaging, diffuser, fluorescence imaging, lensless imaging, on-chip},

pubstate = {published},

tppubtype = {article}

}

@article{monakhova2019learned,

title = {Learned reconstructions for practical mask-based lensless imaging},

author = { Kristina Monakhova and Joshua Yurtsever and Grace Kuo and Nick Antipa and Kyrollos Yanny and Laura Waller},

url = {https://doi.org/10.1364/OE.27.028075},

doi = {10.1364/OE.27.028075},

year  = {2019},

date = {2019-09-30},

journal = {Optics express},

volume = {27},

number = {20},

pages = {28075--28090},

publisher = {Optical Society of America},

keywords = {diffuser, learning-based, lensless imaging, physics-based},

pubstate = {published},

tppubtype = {article}

}

@article{monakhova2019unrolled,

title = {Unrolled, model-based networks for lensless imaging},

author = { Kristina Monakhova and Joshua Yurtsever and Grace Kuo and Nick Antipa and Kyrollos Yanny and Laura Waller},

url = {https://pdfs.semanticscholar.org/6a49/3ac2a0c8a3be888ece00b52bc1ec013df2bd.pdf},

year  = {2019},

date = {2019-09-14},

keywords = {diffuser, learning-based, lensless imaging, physics-based},

pubstate = {published},

tppubtype = {article}

}

@article{yeh2019computational,

title = {Computational structured illumination for high-content fluorescence and phase microscopy},

author = { Li-Hao Yeh and Shwetadwip Chowdhury and Laura Waller},

url = {https://www.osapublishing.org/boe/abstract.cfm?uri=boe-10-4-1978

https://doi.org/10.1364/BOE.10.001978},

doi = {10.1364/BOE.10.001978},

year  = {2019},

date = {2019-04-01},

journal = {Biomedical optics express},

volume = {10},

number = {4},

pages = {1978--1998},

publisher = {Optical Society of America},

abstract = {High-content biological microscopy targets high-resolution imaging across large fields-of-view (FOVs). Recent works have demonstrated that computational imaging can provide efficient solutions for high-content microscopy. Here, we use speckle structured illumination microscopy (SIM) as a robust and cost-effective solution for high-content fluorescence microscopy with simultaneous high-content quantitative phase (QP). This multi-modal compatibility is essential for studies requiring cross-correlative biological analysis. Our method uses laterally-translated Scotch tape to generate high-resolution speckle illumination patterns across a large FOV. Custom optimization algorithms then jointly reconstruct the sample’s super-resolution fluorescent (incoherent) and QP (coherent) distributions, while digitally correcting for system imperfections such as unknown speckle illumination patterns, system aberrations and pattern translations. Beyond previous linear SIM works, we achieve resolution gains of 4× the objective’s diffraction-limited native resolution, resulting in 700 nm fluorescence and 1.2 μm QP resolution, across a FOV of 2×2.7 mm 2, giving a space-bandwidth product (SBP) of 60 megapixels.},

keywords = {diffuser, fluorescence imaging, high-throughput, phase imaging, structured illumination, super-resolution},

pubstate = {published},

tppubtype = {article}

}

@article{antipa2018diffusercam,

title = {DiffuserCam: Lensless single-exposure 3D imaging},

author = { Nick Antipa and Grace Kuo and Reinhard Heckel and Ben Mildenhall and Emrah Bostan and Ren Ng and Laura Waller},

url = {https://doi.org/10.1364/OPTICA.5.000001},

doi = {10.1364/OPTICA.5.000001},

year  = {2018},

date = {2018-01-20},

journal = {Optica},

volume = {5},

number = {1},

pages = {1--9},

publisher = {Optical Society of America},

keywords = {compressed sensing, diffuser, lensless imaging},

pubstate = {published},

tppubtype = {article}

}

@article{almoro2012enhanced,

title = {Enhanced deterministic phase retrieval using a partially developed speckle field},

author = { Percival F Almoro and Laura Waller and Mostafa Agour and Claas Falldorf and Giancarlo Pedrini and Wolfgang Osten and Steen G Hanson},

url = {https://doi.org/10.1364/OL.37.002088},

doi = {10.1364/OL.37.002088},

year  = {2012},

date = {2012-05-30},

journal = {Optics letters},

volume = {37},

number = {11},

pages = {2088--2090},

publisher = {Optical Society of America},

keywords = {diffuser, phase imaging, TIE},

pubstate = {published},

tppubtype = {article}

}