Publications by Laura Waller
2023
Nathan Tessema Ersaro; Cem Yalcin; Liz Murray; Leyla Kabuli; Laura Waller; Rikky Muller
Fast non-iterative algorithm for 3D point-cloud holography Journal Article
In: Opt. Express, vol. 31, no. 22, pp. 36468–36485, 2023.
@article{Ersaro:23,
title = {Fast non-iterative algorithm for 3D point-cloud holography},
author = {Nathan Tessema Ersaro and Cem Yalcin and Liz Murray and Leyla Kabuli and Laura Waller and Rikky Muller},
url = {https://opg.optica.org/oe/abstract.cfm?URI=oe-31-22-36468},
doi = {10.1364/OE.498302},
year = {2023},
date = {2023-10-01},
urldate = {2023-10-01},
journal = {Opt. Express},
volume = {31},
number = {22},
pages = {36468--36485},
publisher = {Optica Publishing Group},
abstract = {Recently developed iterative and deep learning-based approaches to computer-generated holography (CGH) have been shown to achieve high-quality photorealistic 3D images with spatial light modulators. However, such approaches remain overly cumbersome for patterning sparse collections of target points across a photoresponsive volume in applications including biological microscopy and material processing. Specifically, in addition to requiring heavy computation that cannot accommodate real-time operation in mobile or hardware-light settings, existing sampling-dependent 3D CGH methods preclude the ability to place target points with arbitrary precision, limiting accessible depths to a handful of planes. Accordingly, we present a non-iterative point cloud holography algorithm that employs fast deterministic calculations in order to efficiently allocate patches of SLM pixels to different target points in the 3D volume and spread the patterning of all points across multiple time frames. Compared to a matched-performance implementation of the iterative Gerchberg-Saxton algorithm, our algorithm’s relative computation speed advantage was found to increase with SLM pixel count, reaching >100,000x at 512 × 512 array format.},
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Recently developed iterative and deep learning-based approaches to computer-generated holography (CGH) have been shown to achieve high-quality photorealistic 3D images with spatial light modulators. However, such approaches remain overly cumbersome for patterning sparse collections of target points across a photoresponsive volume in applications including biological microscopy and material processing. Specifically, in addition to requiring heavy computation that cannot accommodate real-time operation in mobile or hardware-light settings, existing sampling-dependent 3D CGH methods preclude the ability to place target points with arbitrary precision, limiting accessible depths to a handful of planes. Accordingly, we present a non-iterative point cloud holography algorithm that employs fast deterministic calculations in order to efficiently allocate patches of SLM pixels to different target points in the 3D volume and spread the patterning of all points across multiple time frames. Compared to a matched-performance implementation of the iterative Gerchberg-Saxton algorithm, our algorithm’s relative computation speed advantage was found to increase with SLM pixel count, reaching >100,000x at 512 × 512 array format.
Gautam Gunjala; Antoine Wojdyla; Kenneth A. Goldberg; Zhi Qiao; Xianbo Shi; Lahsen Assoufid; Laura Waller
Data-driven modeling and control of an X-ray bimorph adaptive mirror Journal Article
In: Journal of Synchrotron Radiation, vol. 30, no. 1, 2023.
@article{Gunjala:tv5041,
title = {Data-driven modeling and control of an X-ray bimorph adaptive mirror},
author = {Gautam Gunjala and Antoine Wojdyla and Kenneth A. Goldberg and Zhi Qiao and Xianbo Shi and Lahsen Assoufid and Laura Waller},
url = {https://doi.org/10.1107/S1600577522011080},
doi = {10.1107/S1600577522011080},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
journal = {Journal of Synchrotron Radiation},
volume = {30},
number = {1},
abstract = {Adaptive X-ray mirrors are being adopted on high-coherent-flux synchrotron and X-ray free-electron laser beamlines where dynamic phase control and aberration compensation are necessary to preserve wavefront quality from source to sample, yet challenging to achieve. Additional difficulties arise from the inability to continuously probe the wavefront in this context, which demands methods of control that require little to no feedback. In this work, a data-driven approach to the control of adaptive X-ray optics with piezo-bimorph actuators is demonstrated. This approach approximates the non-linear system dynamics with a discrete-time model using random mirror shapes and interferometric measurements as training data. For mirrors of this type, prior states and voltage inputs affect the shape-change trajectory, and therefore must be included in the model. Without the need for assumed physical models of the mirror's behavior, the generality of the neural network structure accommodates drift, creep and hysteresis, and enables a control algorithm that achieves shape control and stability below 2nm RMS. Using a prototype mirror and it ex situ metrology, it is shown that the accuracy of our trained model enables open-loop shape control across a diverse set of states and that the control algorithm achieves shape error magnitudes that fall within diffraction-limited performance.},
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Adaptive X-ray mirrors are being adopted on high-coherent-flux synchrotron and X-ray free-electron laser beamlines where dynamic phase control and aberration compensation are necessary to preserve wavefront quality from source to sample, yet challenging to achieve. Additional difficulties arise from the inability to continuously probe the wavefront in this context, which demands methods of control that require little to no feedback. In this work, a data-driven approach to the control of adaptive X-ray optics with piezo-bimorph actuators is demonstrated. This approach approximates the non-linear system dynamics with a discrete-time model using random mirror shapes and interferometric measurements as training data. For mirrors of this type, prior states and voltage inputs affect the shape-change trajectory, and therefore must be included in the model. Without the need for assumed physical models of the mirror's behavior, the generality of the neural network structure accommodates drift, creep and hysteresis, and enables a control algorithm that achieves shape control and stability below 2nm RMS. Using a prototype mirror and it ex situ metrology, it is shown that the accuracy of our trained model enables open-loop shape control across a diverse set of states and that the control algorithm achieves shape error magnitudes that fall within diffraction-limited performance.
Eric Li; Stuart Sherwin; Gautam Gunjala; Laura Waller
Exceeding the limits of algorithmic self-calibrated aberration recovery in Fourier ptychography Journal Article
In: Opt. Continuum, vol. 2, no. 1, pp. 119–130, 2023.
@article{Li:23,
title = {Exceeding the limits of algorithmic self-calibrated aberration recovery in Fourier ptychography},
author = {Eric Li and Stuart Sherwin and Gautam Gunjala and Laura Waller},
url = {https://opg.optica.org/optcon/abstract.cfm?URI=optcon-2-1-119},
doi = {10.1364/OPTCON.475990},
year = {2023},
date = {2023-01-01},
journal = {Opt. Continuum},
volume = {2},
number = {1},
pages = {119--130},
publisher = {Optica Publishing Group},
abstract = {Fourier ptychographic microscopy is a computational imaging technique that provides quantitative phase information and high resolution over a large field-of-view. Although the technique presents numerous advantages over conventional microscopy, model mismatch due to unknown optical aberrations can significantly limit reconstruction quality. A practical way of correcting for aberrations without additional data capture is through algorithmic self-calibration, in which a pupil recovery step is embedded into the reconstruction algorithm. However, software-only aberration correction is limited in accuracy. Here, we evaluate the merits of implementing a simple, dedicated calibration procedure for applications requiring high accuracy. In simulations, we find that for a target sample reconstruction error, we can image without any aberration corrections only up to a maximum aberration magnitude of $łambda$/40. When we use algorithmic self-calibration, we can tolerate an aberration magnitude up to $łambda$/10 and with our proposed diffuser calibration technique, this working range is extended further to $łambda$/3. Hence, one can trade off complexity for accuracy by using a separate calibration process, which is particularly useful for larger aberrations.},
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Fourier ptychographic microscopy is a computational imaging technique that provides quantitative phase information and high resolution over a large field-of-view. Although the technique presents numerous advantages over conventional microscopy, model mismatch due to unknown optical aberrations can significantly limit reconstruction quality. A practical way of correcting for aberrations without additional data capture is through algorithmic self-calibration, in which a pupil recovery step is embedded into the reconstruction algorithm. However, software-only aberration correction is limited in accuracy. Here, we evaluate the merits of implementing a simple, dedicated calibration procedure for applications requiring high accuracy. In simulations, we find that for a target sample reconstruction error, we can image without any aberration corrections only up to a maximum aberration magnitude of $łambda$/40. When we use algorithmic self-calibration, we can tolerate an aberration magnitude up to $łambda$/10 and with our proposed diffuser calibration technique, this working range is extended further to $łambda$/3. Hence, one can trade off complexity for accuracy by using a separate calibration process, which is particularly useful for larger aberrations.
Joseph D. Malone; Neerja Aggarwal; Laura Waller; Audrey K. Bowden
DiffuserSpec: spectroscopy with Scotch tape Journal Article
In: Opt. Lett., vol. 48, no. 2, pp. 323–326, 2023.
@article{Malone:23,
title = {DiffuserSpec: spectroscopy with Scotch tape},
author = {Joseph D. Malone and Neerja Aggarwal and Laura Waller and Audrey K. Bowden},
url = {https://opg.optica.org/ol/abstract.cfm?URI=ol-48-2-323},
doi = {10.1364/OL.476472},
year = {2023},
date = {2023-01-01},
journal = {Opt. Lett.},
volume = {48},
number = {2},
pages = {323--326},
publisher = {Optica Publishing Group},
abstract = {Computational spectroscopy breaks the inherent one-to-one spatial-to-spectral pixel mapping of traditional spectrometers by multiplexing spectral data over a given sensor region. Most computational spectrometers require components that are complex to design, fabricate, or both. DiffuserSpec is a simple computational spectrometer that uses the inherent spectral dispersion of commercially available diffusers to generate speckle patterns that are unique to each wavelength. Using Scotch tape as a diffuser, we demonstrate narrowband and broadband spectral reconstructions with 2-nm spectral resolution over an 85-nm bandwidth in the near-infrared, limited only by the bandwidth of the calibration dataset. We also investigate the effect of spatial sub-sampling of the 2D speckle pattern on resolution performance.},
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Computational spectroscopy breaks the inherent one-to-one spatial-to-spectral pixel mapping of traditional spectrometers by multiplexing spectral data over a given sensor region. Most computational spectrometers require components that are complex to design, fabricate, or both. DiffuserSpec is a simple computational spectrometer that uses the inherent spectral dispersion of commercially available diffusers to generate speckle patterns that are unique to each wavelength. Using Scotch tape as a diffuser, we demonstrate narrowband and broadband spectral reconstructions with 2-nm spectral resolution over an 85-nm bandwidth in the near-infrared, limited only by the bandwidth of the calibration dataset. We also investigate the effect of spatial sub-sampling of the 2D speckle pattern on resolution performance.
2022
Yi Xue; David Ren; Laura Waller
Three-dimensional bi-functional refractive index and fluorescence microscopy (BRIEF) Journal Article
In: Biomed. Opt. Express, vol. 13, no. 11, pp. 5900–5908, 2022.
@article{Xue:22,
title = {Three-dimensional bi-functional refractive index and fluorescence microscopy (BRIEF)},
author = {Yi Xue and David Ren and Laura Waller},
url = {https://opg.optica.org/boe/abstract.cfm?URI=boe-13-11-5900},
doi = {10.1364/BOE.456621},
year = {2022},
date = {2022-11-01},
journal = {Biomed. Opt. Express},
volume = {13},
number = {11},
pages = {5900--5908},
publisher = {Optica Publishing Group},
abstract = {Fluorescence microscopy is a powerful tool for imaging biological samples with molecular specificity. In contrast, phase microscopy provides label-free measurement of the sample’s refractive index (RI), which is an intrinsic optical property that quantitatively relates to cell morphology, mass, and stiffness. Conventional imaging techniques measure either the labeled fluorescence (functional) information or the label-free RI (structural) information, though it may be valuable to have both. For example, biological tissues have heterogeneous RI distributions, causing sample-induced scattering that degrades the fluorescence image quality. When both fluorescence and 3D RI are measured, one can use the RI information to digitally correct multiple-scattering effects in the fluorescence image. Here, we develop a new computational multi-modal imaging method based on epi-mode microscopy that reconstructs both 3D fluorescence and 3D RI from a single dataset. We acquire dozens of fluorescence images, each ‘illuminated’ by a single fluorophore, then solve an inverse problem with a multiple-scattering forward model. We experimentally demonstrate our method for epi-mode 3D RI imaging and digital correction of multiple-scattering effects in fluorescence images.},
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Fluorescence microscopy is a powerful tool for imaging biological samples with molecular specificity. In contrast, phase microscopy provides label-free measurement of the sample’s refractive index (RI), which is an intrinsic optical property that quantitatively relates to cell morphology, mass, and stiffness. Conventional imaging techniques measure either the labeled fluorescence (functional) information or the label-free RI (structural) information, though it may be valuable to have both. For example, biological tissues have heterogeneous RI distributions, causing sample-induced scattering that degrades the fluorescence image quality. When both fluorescence and 3D RI are measured, one can use the RI information to digitally correct multiple-scattering effects in the fluorescence image. Here, we develop a new computational multi-modal imaging method based on epi-mode microscopy that reconstructs both 3D fluorescence and 3D RI from a single dataset. We acquire dozens of fluorescence images, each ‘illuminated’ by a single fluorophore, then solve an inverse problem with a multiple-scattering forward model. We experimentally demonstrate our method for epi-mode 3D RI imaging and digital correction of multiple-scattering effects in fluorescence images.
Henry Pinkard; Laura Waller
Microscopes are coming for your job Journal Article
In: Nature Methods, pp. 1–2, 2022.
@article{pinkard2022microscopes,
title = {Microscopes are coming for your job},
author = {Henry Pinkard and Laura Waller},
url = {https://www.nature.com/articles/s41592-022-01566-4},
year = {2022},
date = {2022-09-08},
urldate = {2022-01-01},
journal = {Nature Methods},
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Michael L. Whittaker; David Ren; Colin Ophus; Yugang Zhang; Laura Waller; Benjamin Gilbert; Jillian F. Banfield
Ion complexation waves emerge at the curved interfaces of layered minerals Journal Article
In: Nature Communications volume , vol. 13, iss. 1, 2022.
@article{Ion2022,
title = {Ion complexation waves emerge at the curved interfaces of layered minerals},
author = {Michael L. Whittaker and David Ren and Colin Ophus and Yugang Zhang and Laura Waller and Benjamin Gilbert and Jillian F. Banfield },
doi = {https://doi.org/10.1038/s41467-022-31004-0},
year = {2022},
date = {2022-06-13},
urldate = {2022-06-13},
journal = {Nature Communications volume },
volume = {13},
issue = {1},
abstract = {Visualizing hydrated interfaces is of widespread interest across the physical sciences and is a particularly acute need for layered minerals, whose properties are governed by the structure of the electric double layer (EDL) where mineral and solution meet. Here, we show that cryo electron microscopy and tomography enable direct imaging of the EDL at montmorillonite interfaces in monovalent electrolytes with ångstrom resolution over micron length scales. A learning-based multiple-scattering reconstruction method for cryo electron tomography reveals ions bound asymmetrically on opposite sides of curved, exfoliated layers. We observe conserved ion-density asymmetry across stacks of interacting layers in cryo electron microscopy that is associated with configurations of inner- and outer-sphere ion-water-mineral complexes that we term complexation waves. Coherent X-ray scattering confirms that complexation waves propagate at room-temperature via a competition between ion dehydration and charge interactions that are coupled across opposing sides of a layer, driving dynamic transitions between stacked and aggregated states via layer exfoliation.},
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Visualizing hydrated interfaces is of widespread interest across the physical sciences and is a particularly acute need for layered minerals, whose properties are governed by the structure of the electric double layer (EDL) where mineral and solution meet. Here, we show that cryo electron microscopy and tomography enable direct imaging of the EDL at montmorillonite interfaces in monovalent electrolytes with ångstrom resolution over micron length scales. A learning-based multiple-scattering reconstruction method for cryo electron tomography reveals ions bound asymmetrically on opposite sides of curved, exfoliated layers. We observe conserved ion-density asymmetry across stacks of interacting layers in cryo electron microscopy that is associated with configurations of inner- and outer-sphere ion-water-mineral complexes that we term complexation waves. Coherent X-ray scattering confirms that complexation waves propagate at room-temperature via a competition between ion dehydration and charge interactions that are coupled across opposing sides of a layer, driving dynamic transitions between stacked and aggregated states via layer exfoliation.
Kristina Monakhova; Stephan R. Richter; Laura Waller; Vladlen Koltun
Dancing Under the Stars: Video Denoising in Starlight Inproceedings
In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 16241-16251, 2022.
@inproceedings{Monakhova_2022_CVPR,
title = {Dancing Under the Stars: Video Denoising in Starlight},
author = {Kristina Monakhova and Stephan R. Richter and Laura Waller and Vladlen Koltun},
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Ruiming Cao; Michael Kellman; David Ren; Regina Eckert; Laura Waller
Self-calibrated 3D differential phase contrast microscopy with optimized illumination Journal Article
In: Biomed. Opt. Express, vol. 13, no. 3, pp. 1671–1684, 2022.
@article{Cao:22,
title = {Self-calibrated 3D differential phase contrast microscopy with optimized illumination},
author = {Ruiming Cao and Michael Kellman and David Ren and Regina Eckert and Laura Waller},
url = {http://opg.optica.org/boe/abstract.cfm?URI=boe-13-3-1671},
doi = {10.1364/BOE.450838},
year = {2022},
date = {2022-03-01},
urldate = {2022-03-01},
journal = {Biomed. Opt. Express},
volume = {13},
number = {3},
pages = {1671--1684},
publisher = {OSA},
abstract = {3D phase imaging recovers an object’s volumetric refractive index from intensity and/or holographic measurements. Partially coherent methods, such as illumination-based differential phase contrast (DPC), are particularly simple to implement in a commercial brightfield microscope. 3D DPC acquires images at multiple focus positions and with different illumination source patterns in order to reconstruct 3D refractive index. Here, we present a practical extension of the 3D DPC method that does not require a precise motion stage for scanning the focus and uses optimized illumination patterns for improved performance. The user scans the focus by hand, using the microscope’s focus knob, and the algorithm self-calibrates the axial position to solve for the 3D refractive index of the sample through a computational inverse problem. We further show that the illumination patterns can be optimized by an end-to-end learning procedure. Combining these two, we demonstrate improved 3D DPC with a commercial microscope whose only hardware modification is LED array illumination.},
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3D phase imaging recovers an object’s volumetric refractive index from intensity and/or holographic measurements. Partially coherent methods, such as illumination-based differential phase contrast (DPC), are particularly simple to implement in a commercial brightfield microscope. 3D DPC acquires images at multiple focus positions and with different illumination source patterns in order to reconstruct 3D refractive index. Here, we present a practical extension of the 3D DPC method that does not require a precise motion stage for scanning the focus and uses optimized illumination patterns for improved performance. The user scans the focus by hand, using the microscope’s focus knob, and the algorithm self-calibrates the axial position to solve for the 3D refractive index of the sample through a computational inverse problem. We further show that the illumination patterns can be optimized by an end-to-end learning procedure. Combining these two, we demonstrate improved 3D DPC with a commercial microscope whose only hardware modification is LED array illumination.
Yi Xue; Laura Waller; Hillel Adesnik; Nicolas Pégard
Three-dimensional multi-site random access photostimulation (3D-MAP) Journal Article
In: eLife, vol. 2022, no. 11, pp. e73266, 2022.
@article{Xue:2022,
title = {Three-dimensional multi-site random access photostimulation (3D-MAP)},
author = {Yi Xue and Laura Waller and Hillel Adesnik and Nicolas Pégard},
doi = {10.7554/eLife.73266},
year = {2022},
date = {2022-02-14},
journal = {eLife},
volume = { 2022},
number = {11},
pages = {e73266},
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Vivek Boominathan; Jacob T Robinson; Laura Waller; Ashok Veeraraghavan
Recent advances in lensless imaging Journal Article
In: Optica, vol. 9, no. 1, pp. 1–16, 2022.
@article{Boominathan:22,
title = {Recent advances in lensless imaging},
author = {Vivek Boominathan and Jacob T Robinson and Laura Waller and Ashok Veeraraghavan},
url = {http://www.osapublishing.org/optica/abstract.cfm?URI=optica-9-1-1},
doi = {10.1364/OPTICA.431361},
year = {2022},
date = {2022-01-01},
journal = {Optica},
volume = {9},
number = {1},
pages = {1--16},
publisher = {OSA},
abstract = {Lensless imaging provides opportunities to design imaging systems free from the constraints imposed by traditional camera architectures. Due to advances in imaging hardware, fabrication techniques, and new algorithms, researchers have recently developed lensless imaging systems that are extremely compact and lightweight or able to image higher-dimensional quantities. Here we review these recent advances and describe the design principles and their effects that one should consider when developing and using lensless imaging systems.},
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Lensless imaging provides opportunities to design imaging systems free from the constraints imposed by traditional camera architectures. Due to advances in imaging hardware, fabrication techniques, and new algorithms, researchers have recently developed lensless imaging systems that are extremely compact and lightweight or able to image higher-dimensional quantities. Here we review these recent advances and describe the design principles and their effects that one should consider when developing and using lensless imaging systems.
Kyrollos Yanny; Kristina Monakhova; Richard W Shuai; Laura Waller
Deep learning for fast spatially varying deconvolution Journal Article
In: Optica, vol. 9, no. 1, pp. 96–99, 2022.
@article{Yanny:22,
title = {Deep learning for fast spatially varying deconvolution},
author = {Kyrollos Yanny and Kristina Monakhova and Richard W Shuai and Laura Waller},
url = {http://www.osapublishing.org/optica/abstract.cfm?URI=optica-9-1-96},
doi = {10.1364/OPTICA.442438},
year = {2022},
date = {2022-01-01},
journal = {Optica},
volume = {9},
number = {1},
pages = {96--99},
publisher = {OSA},
abstract = {Deconvolution can be used to obtain sharp images or volumes from blurry or encoded measurements in imaging systems. Given knowledge of the system's point spread function (PSF) over the field of view, a reconstruction algorithm can be used to recover a clear image or volume. Most deconvolution algorithms assume shift-invariance; however, in realistic systems, the PSF varies laterally and axially across the field of view due to aberrations or design. Shift-varying models can be used, but are often slow and computationally intensive. In this work, we propose a deep-learning-based approach that leverages knowledge about the system's spatially varying PSFs for fast 2D and 3D reconstructions. Our approach, termed MultiWienerNet, uses multiple differentiable Wiener filters paired with a convolutional neural network to incorporate spatial variance. Trained using simulated data and tested on experimental data, our approach offers a 625textminus1600texttimes increase in speed compared to iterative methods with a spatially varying model, and outperforms existing deep-learning-based methods that assume shift invariance.},
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Deconvolution can be used to obtain sharp images or volumes from blurry or encoded measurements in imaging systems. Given knowledge of the system's point spread function (PSF) over the field of view, a reconstruction algorithm can be used to recover a clear image or volume. Most deconvolution algorithms assume shift-invariance; however, in realistic systems, the PSF varies laterally and axially across the field of view due to aberrations or design. Shift-varying models can be used, but are often slow and computationally intensive. In this work, we propose a deep-learning-based approach that leverages knowledge about the system's spatially varying PSFs for fast 2D and 3D reconstructions. Our approach, termed MultiWienerNet, uses multiple differentiable Wiener filters paired with a convolutional neural network to incorporate spatial variance. Trained using simulated data and tested on experimental data, our approach offers a 625textminus1600texttimes increase in speed compared to iterative methods with a spatially varying model, and outperforms existing deep-learning-based methods that assume shift invariance.
Sylvain Gigan; Ori Katz; Hilton Barbosa de Aguiar; Esben Andresen; Alexandre Aubry; Jacopo Bertolotti; Emmanuel Bossy; Dorian Bouchet; Josh Brake; Sophie Brasselet; Yaron Bromberg; Hui Cao; Thomas Chaigne; Zhongtao Cheng; Won-Shik Choi; Tomas Cizmar; Meng Cui; Vincent Curtis; Hugo Defienne; Matthias Hofer; Ryoichi Horisaki; Roarke Horstmeyer; Na Ji; Aaron LaViolette; Jerome Mertz; Christophe Moser; Allard P. Mosk; Nicolas Pégard; Rafael Piestun; Sébastien Popoff; Dave Phillips; D Psaltis; Babak Rahmani; Herve Rigneault; Stefan Rotter; Lei Tian; Ivo M Vellekoop; Laura Waller; Lihong V Wang; Timothy Weber; Sheng Xiao; Chris Xu; Alexey Yamilov; Changhuei Yang; Hasan Yılmaz
Roadmap on Wavefront Shaping and deep imaging in complex media Journal Article
In: Journal of Physics: Photonics, 2022.
@article{10.1088/2515-7647/ac76f9,
title = {Roadmap on Wavefront Shaping and deep imaging in complex media},
author = {Sylvain Gigan and Ori Katz and Hilton Barbosa de Aguiar and Esben Andresen and Alexandre Aubry and Jacopo Bertolotti and Emmanuel Bossy and Dorian Bouchet and Josh Brake and Sophie Brasselet and Yaron Bromberg and Hui Cao and Thomas Chaigne and Zhongtao Cheng and Won-Shik Choi and Tomas Cizmar and Meng Cui and Vincent Curtis and Hugo Defienne and Matthias Hofer and Ryoichi Horisaki and Roarke Horstmeyer and Na Ji and Aaron LaViolette and Jerome Mertz and Christophe Moser and Allard P. Mosk and Nicolas Pégard and Rafael Piestun and Sébastien Popoff and Dave Phillips and D Psaltis and Babak Rahmani and Herve Rigneault and Stefan Rotter and Lei Tian and Ivo M Vellekoop and Laura Waller and Lihong V Wang and Timothy Weber and Sheng Xiao and Chris Xu and Alexey Yamilov and Changhuei Yang and Hasan Yılmaz},
url = {http://iopscience.iop.org/article/10.1088/2515-7647/ac76f9},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
journal = {Journal of Physics: Photonics},
abstract = {The last decade has seen the development of a wide set of tools, such as wavefront shaping, computational or fundamental methods, that allow to understand and control light propagation in a complex medium, such as biological tissues or multimode fibers. A vibrant and diverse community is now working on this field, that has revolutionized the prospect of diffraction-limited imaging at depth in tissues. This roadmap highlights several key aspects of this fast developing field, and some of the challenges and opportunities ahead.},
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The last decade has seen the development of a wide set of tools, such as wavefront shaping, computational or fundamental methods, that allow to understand and control light propagation in a complex medium, such as biological tissues or multimode fibers. A vibrant and diverse community is now working on this field, that has revolutionized the prospect of diffraction-limited imaging at depth in tissues. This roadmap highlights several key aspects of this fast developing field, and some of the challenges and opportunities ahead.
Ruiming Cao; Fanglin Linda Liu; Li-Hao Yeh; Laura Waller
Dynamic Structured Illumination Microscopy with a Neural Space-time Model Inproceedings
In: 2022 IEEE International Conference on Computational Photography (ICCP), pp. 1-12, 2022.
@inproceedings{9887701,
title = {Dynamic Structured Illumination Microscopy with a Neural Space-time Model},
author = {Ruiming Cao and Fanglin Linda Liu and Li-Hao Yeh and Laura Waller},
doi = {10.1109/ICCP54855.2022.9887701},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
booktitle = {2022 IEEE International Conference on Computational Photography (ICCP)},
pages = {1-12},
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2021
Kristina Monakhova; Vi Tran; Grace Kuo; Laura Waller
Untrained networks for compressive lensless photography Journal Article
In: Opt. Express, vol. 29, no. 13, pp. 20913–20929, 2021.
@article{Monakhova:21,
title = {Untrained networks for compressive lensless photography},
author = {Kristina Monakhova and Vi Tran and Grace Kuo and Laura Waller},
url = {http://www.opticsexpress.org/abstract.cfm?URI=oe-29-13-20913},
doi = {10.1364/OE.424075},
year = {2021},
date = {2021-06-01},
journal = {Opt. Express},
volume = {29},
number = {13},
pages = {20913--20929},
publisher = {OSA},
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}
Emma Alexander; Leyla A Kabuli; Oliver S Cossairt; Laura Waller
Depth from Defocus as a Special Case of the Transport of Intensity Equation Inproceedings
In: 2021 IEEE International Conference on Computational Photography (ICCP), pp. 1-13, 2021.
@inproceedings{9466260,
title = {Depth from Defocus as a Special Case of the Transport of Intensity Equation},
author = {Emma Alexander and Leyla A Kabuli and Oliver S Cossairt and Laura Waller},
doi = {10.1109/ICCP51581.2021.9466260},
year = {2021},
date = {2021-01-01},
booktitle = {2021 IEEE International Conference on Computational Photography (ICCP)},
pages = {1-13},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Ruiming Cao; Michael Kellman; David Yonghuan Ren; Regina Eckert; Laura Waller
Algorithmic self-calibration for optimized 3D quantitative differential phase contrast microscopy Inproceedings
In: Quantitative Phase Imaging VII, pp. 116530R, International Society for Optics and Photonics 2021.
@inproceedings{cao2021algorithmic,
title = {Algorithmic self-calibration for optimized 3D quantitative differential phase contrast microscopy},
author = {Ruiming Cao and Michael Kellman and David Yonghuan Ren and Regina Eckert and Laura Waller},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11653/116530R/Algorithmic-self-calibration-for-optimized-3D-quantitative-differential-phase-contrast/10.1117/12.2577318.short?SSO=1},
year = {2021},
date = {2021-01-01},
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volume = {11653},
pages = {116530R},
organization = {International Society for Optics and Photonics},
keywords = {},
pubstate = {published},
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}
Jingshan Zhong; Emrah Bostan; Dihong Tian; Laura Waller
Simultaneous recovery of phase and defocus from coherent through-focus intensity images Inproceedings
In: Quantitative Phase Imaging VII, pp. 116530Z, International Society for Optics and Photonics 2021.
@inproceedings{zhong2021simultaneous,
title = {Simultaneous recovery of phase and defocus from coherent through-focus intensity images},
author = {Jingshan Zhong and Emrah Bostan and Dihong Tian and Laura Waller},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11653/116530Z/Simultaneous-recovery-of-phase-and-defocus-from-coherent-through-focus/10.1117/12.2575823.short},
year = {2021},
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organization = {International Society for Optics and Photonics},
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Yi Xue; Laura Waller
Computational Hybrid Imaging: Measure Fluorescence and Refractive Index Together Inproceedings
In: Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVIII, pp. 116490W, International Society for Optics and Photonics 2021.
@inproceedings{xue2021computational,
title = {Computational Hybrid Imaging: Measure Fluorescence and Refractive Index Together},
author = {Yi Xue and Laura Waller},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11649/116490W/Computational-Hybrid-Imaging-Measure-Fluorescence-and-Refractive-Index-Together/10.1117/12.2579940.short},
year = {2021},
date = {2021-01-01},
booktitle = {Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVIII},
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Stuart Sherwin; Isvar Cordova; Ryan Miyakawa; Markus Benk; Laura Waller; Andrew Neureuther; Patrick Naulleau
Picometer sensitivity metrology for EUV absorber phase Journal Article
In: Journal of Micro/Nanopatterning, Materials, and Metrology, vol. 20, no. 3, pp. 1 – 19, 2021.
@article{10.1117/1.JMM.20.3.031011,
title = {Picometer sensitivity metrology for EUV absorber phase},
author = {Stuart Sherwin and Isvar Cordova and Ryan Miyakawa and Markus Benk and Laura Waller and Andrew Neureuther and Patrick Naulleau},
url = {https://doi.org/10.1117/1.JMM.20.3.031011},
doi = {10.1117/1.JMM.20.3.031011},
year = {2021},
date = {2021-01-01},
journal = {Journal of Micro/Nanopatterning, Materials, and Metrology},
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Stuart Sherwin; Isvar A Cordova; Ryan H Miyakawa; Markus P Benk; Laura Waller; Andrew R Neureuther; Patrick Naulleau
Picometer sensitivity metrology for EUV absorber phase Journal Article
In: Journal of Micro/Nanopatterning, Materials, and Metrology, vol. 20, no. 3, pp. 1 – 19, 2021.
@article{10.1117/1.JMM.20.3.031011b,
title = {Picometer sensitivity metrology for EUV absorber phase},
author = {Stuart Sherwin and Isvar A Cordova and Ryan H Miyakawa and Markus P Benk and Laura Waller and Andrew R Neureuther and Patrick Naulleau},
url = {https://doi.org/10.1117/1.JMM.20.3.031011},
doi = {10.1117/1.JMM.20.3.031011},
year = {2021},
date = {2021-01-01},
journal = {Journal of Micro/Nanopatterning, Materials, and Metrology},
volume = {20},
number = {3},
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2020
Michael Kellman; Kevin Zhang; Eric Markley; Jon Tamir; Emrah Bostan; Michael Lustig; Laura Waller
Memory-efficient Learning for Large-Scale Computational Imaging Journal Article
In: IEEE Transactions on Computational Imaging, vol. 6, pp. 1403-1414, 2020.
@article{kellman2020memory,
title = {Memory-efficient Learning for Large-Scale Computational Imaging},
author = { Michael Kellman and Kevin Zhang and Eric Markley and Jon Tamir and Emrah Bostan and Michael Lustig and Laura Waller},
url = {https://ieeexplore.ieee.org/document/9204455},
doi = {10.1109/TCI.2020.3025735},
year = {2020},
date = {2020-10-14},
journal = {IEEE Transactions on Computational Imaging},
volume = {6},
pages = {1403-1414},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Kyrollos Yanny; Nick Antipa; William Liberti; Sam Dehaeck; Kristina Monakhova; Fanglin Linda Liu; Konlin Shen; Ren Ng; Laura Waller
Miniscope3D: optimized single-shot miniature 3D fluorescence microscopy Journal Article
In: Light: Science & Applications, vol. 9, no. 171, 2020.
@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 = {},
pubstate = {published},
tppubtype = {article}
}
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.
Kristina Monakhova; Kyrollos Yanny; Neerja Aggarwal; Laura Waller
Spectral DiffuserCam: lensless snapshot hyperspectral imaging with a spectral filter array Journal Article
In: Optica, vol. 7, no. 10, pp. 1298–1307, 2020.
@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 = {},
pubstate = {published},
tppubtype = {article}
}
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.
Bahram Javidi; Artur Carnicer; Jun Arai; Toshiaki Fujii; Hong Hua; Hongen Liao; Manuel Martínez-Corral; Filiberto Pla; Adrian Stern; Laura Waller; Qiong-Hua Wang; Gordon Wetzstein; Masahiro Yamaguchi; Hirotsugu Yamamoto
Roadmap on 3D integral imaging: sensing, processing, and display Journal Article
In: Opt. Express, vol. 28, no. 22, pp. 32266–32293, 2020.
@article{Javidi:20,
title = {Roadmap on 3D integral imaging: sensing, processing, and display},
author = {Bahram Javidi and Artur Carnicer and Jun Arai and Toshiaki Fujii and Hong Hua and Hongen Liao and Manuel Martínez-Corral and Filiberto Pla and Adrian Stern and Laura Waller and Qiong-Hua Wang and Gordon Wetzstein and Masahiro Yamaguchi and Hirotsugu Yamamoto},
url = {http://www.opticsexpress.org/abstract.cfm?URI=oe-28-22-32266},
doi = {10.1364/OE.402193},
year = {2020},
date = {2020-10-01},
journal = {Opt. Express},
volume = {28},
number = {22},
pages = {32266--32293},
publisher = {OSA},
abstract = {This Roadmap article on three-dimensional integral imaging provides an overview of some of the research activities in the field of integral imaging. The article discusses various aspects of the field including sensing of 3D scenes, processing of captured information, and 3D display and visualization of information. The paper consists of a series of 15 sections from the experts presenting various aspects of the field on sensing, processing, displays, augmented reality, microscopy, object recognition, and other applications. Each section represents the vision of its author to describe the progress, potential, vision, and challenging issues in this field.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This Roadmap article on three-dimensional integral imaging provides an overview of some of the research activities in the field of integral imaging. The article discusses various aspects of the field including sensing of 3D scenes, processing of captured information, and 3D display and visualization of information. The paper consists of a series of 15 sections from the experts presenting various aspects of the field on sensing, processing, displays, augmented reality, microscopy, object recognition, and other applications. Each section represents the vision of its author to describe the progress, potential, vision, and challenging issues in this field.
Fanglin Linda Liu; Grace Kuo; Nick Antipa; Kyrollos Yanny; Laura Waller
Fourier DiffuserScope: single-shot 3D Fourier light field microscopy with a diffuser Journal Article
In: Opt. Express, vol. 28, no. 20, pp. 28969–28986, 2020.
@article{LindaLiu:20,
title = {Fourier DiffuserScope: single-shot 3D Fourier light field microscopy with a diffuser},
author = {Fanglin Linda Liu and Grace Kuo and Nick Antipa and Kyrollos Yanny and Laura Waller},
url = {http://www.opticsexpress.org/abstract.cfm?URI=oe-28-20-28969},
doi = {10.1364/OE.400876},
year = {2020},
date = {2020-09-01},
journal = {Opt. Express},
volume = {28},
number = {20},
pages = {28969--28986},
publisher = {OSA},
abstract = {Light field microscopy (LFM) uses a microlens array (MLA) near the sensor plane of a microscope to achieve single-shot 3D imaging of a sample without any moving parts. Unfortunately, the 3D capability of LFM comes with a significant loss of lateral resolution at the focal plane. Placing the MLA near the pupil plane of the microscope, instead of the image plane, can mitigate the artifacts and provide an efficient forward model, at the expense of field-of-view (FOV). Here, we demonstrate improved resolution across a large volume with Fourier DiffuserScope, which uses a diffuser in the pupil plane to encode 3D information, then computationally reconstructs the volume by solving a sparsity-constrained inverse problem. Our diffuser consists of randomly placed microlenses with varying focal lengths; the random positions provide a larger FOV compared to a conventional MLA, and the diverse focal lengths improve the axial depth range. To predict system performance based on diffuser parameters, we, for the first time, establish a theoretical framework and design guidelines, which are verified by numerical simulations, and then build an experimental system that achieves < 3 µm lateral and 4 µm axial resolution over a 1000 × 1000 × 280 µm3 volume. Our diffuser design outperforms the MLA used in LFM, providing more uniform resolution over a larger volume, both laterally and axially.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Light field microscopy (LFM) uses a microlens array (MLA) near the sensor plane of a microscope to achieve single-shot 3D imaging of a sample without any moving parts. Unfortunately, the 3D capability of LFM comes with a significant loss of lateral resolution at the focal plane. Placing the MLA near the pupil plane of the microscope, instead of the image plane, can mitigate the artifacts and provide an efficient forward model, at the expense of field-of-view (FOV). Here, we demonstrate improved resolution across a large volume with Fourier DiffuserScope, which uses a diffuser in the pupil plane to encode 3D information, then computationally reconstructs the volume by solving a sparsity-constrained inverse problem. Our diffuser consists of randomly placed microlenses with varying focal lengths; the random positions provide a larger FOV compared to a conventional MLA, and the diverse focal lengths improve the axial depth range. To predict system performance based on diffuser parameters, we, for the first time, establish a theoretical framework and design guidelines, which are verified by numerical simulations, and then build an experimental system that achieves < 3 µm lateral and 4 µm axial resolution over a 1000 × 1000 × 280 µm3 volume. Our diffuser design outperforms the MLA used in LFM, providing more uniform resolution over a larger volume, both laterally and axially.
Gautam Gunjala; Antoine Wojdyla; Stuart Sherwin; Aamod Shanker; Markus P. Benk; Kenneth A. Goldberg; Patrick P. Naulleau; Laura Waller
Extreme ultraviolet microscope characterization using photomask surface roughness Journal Article
In: Scientific Reports, vol. 10, no. 1, pp. 11673, 2020.
@article{gunjala2020extreme,
title = {Extreme ultraviolet microscope characterization using photomask surface roughness },
author = {Gautam Gunjala and Antoine Wojdyla and Stuart Sherwin and Aamod Shanker and Markus P. Benk and Kenneth A. Goldberg and Patrick P. Naulleau and Laura Waller },
url = {https://doi.org/10.1038/s41598-020-68588-w},
doi = {10.1038/s41598-020-68588-w},
year = {2020},
date = {2020-07-15},
journal = {Scientific Reports},
volume = {10},
number = {1},
pages = {11673},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Emrah Bostan; Reinhard Heckel; Michael Chen; Michael Kellman; Laura Waller
Deep Phase Decoder: Self-calibrating phase microscopy with an untrained deep neural network Journal Article
In: Optica, vol. 7, no. 6, pp. 559-562, 2020.
@article{bostan2020deep,
title = {Deep Phase Decoder: Self-calibrating phase microscopy with an untrained deep neural network},
author = { Emrah Bostan and Reinhard Heckel and Michael Chen and Michael Kellman and Laura Waller},
url = {https://doi.org/10.1364/OPTICA.389314
https://arxiv.org/abs/2001.09803},
doi = {10.1364/OPTICA.389314},
year = {2020},
date = {2020-05-21},
journal = {Optica},
volume = {7},
number = {6},
pages = {559-562},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Michael Chen; David Ren; Hsiou-Yuan Liu; Shwetadwip Chowdhury; Laura Waller
Multi-layer Born multiple-scattering model for 3D phase microscopy Journal Article
In: Optica, vol. 7, no. 5, pp. 394–403, 2020.
@article{Chen:20,
title = {Multi-layer Born multiple-scattering model for 3D phase microscopy},
author = {Michael Chen and David Ren and Hsiou-Yuan Liu and Shwetadwip Chowdhury and Laura Waller},
url = {http://www.osapublishing.org/optica/abstract.cfm?URI=optica-7-5-394},
doi = {10.1364/OPTICA.383030},
year = {2020},
date = {2020-05-01},
journal = {Optica},
volume = {7},
number = {5},
pages = {394--403},
publisher = {OSA},
abstract = {We propose an accurate and computationally efficient 3D scattering model, multi-layer Born (MLB), and use it to recover the 3D refractive index (RI) of thick biological samples. For inverse problems recovering the complex field of thick samples, weak scattering models (e.g., first Born) may fail or underestimate the RI, especially with a large index contrast. Multi-slice (MS) beam propagation methods model multiple scattering to provide more realistic reconstructions; however, MS does not properly account for highly oblique scattering, nor does it model backward scattering. Our proposed MLB model uses a first Born model at each of many slices, accurately capturing the oblique scattering effects and estimating the backward scattering process. When used in conjunction with an inverse solver, the model provides more accurate RI reconstructions for high-resolution phase tomography. Importantly, MLB retains a reasonable computation time that is critical for practical implementation with iterative inverse algorithms.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We propose an accurate and computationally efficient 3D scattering model, multi-layer Born (MLB), and use it to recover the 3D refractive index (RI) of thick biological samples. For inverse problems recovering the complex field of thick samples, weak scattering models (e.g., first Born) may fail or underestimate the RI, especially with a large index contrast. Multi-slice (MS) beam propagation methods model multiple scattering to provide more realistic reconstructions; however, MS does not properly account for highly oblique scattering, nor does it model backward scattering. Our proposed MLB model uses a first Born model at each of many slices, accurately capturing the oblique scattering effects and estimating the backward scattering process. When used in conjunction with an inverse solver, the model provides more accurate RI reconstructions for high-resolution phase tomography. Importantly, MLB retains a reasonable computation time that is critical for practical implementation with iterative inverse algorithms.
Stuart Sherwin; Isvar Cordova; Ryan Miyakawa; Laura Waller; Andrew Neureuther; Patrick Naulleau
Quantitative phase retrieval for EUV photomasks Inproceedings
In: Felix, Nelson M; Lio, Anna (Ed.): Extreme Ultraviolet (EUV) Lithography XI, pp. 234 – 243, International Society for Optics and Photonics SPIE, 2020.
@inproceedings{10.1117/12.2552967,
title = {Quantitative phase retrieval for EUV photomasks},
author = {Stuart Sherwin and Isvar Cordova and Ryan Miyakawa and Laura Waller and Andrew Neureuther and Patrick Naulleau},
editor = {Nelson M Felix and Anna Lio},
url = {https://doi.org/10.1117/12.2552967},
doi = {10.1117/12.2552967},
year = {2020},
date = {2020-03-23},
booktitle = {Extreme Ultraviolet (EUV) Lithography XI},
volume = {11323},
pages = {234 -- 243},
publisher = {SPIE},
organization = {International Society for Optics and Photonics},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Grace Kuo; Fanglin Linda Liu; Irene Grossrubatscher; Ren Ng; Laura Waller
On-chip fluorescence microscopy with a random microlens diffuser Journal Article
In: Optics Express, vol. 28, no. 6, pp. 8384–8399, 2020.
@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 = {},
pubstate = {published},
tppubtype = {article}
}
Regina Eckert; Michael Kellman; Laura Waller
Physics-based learning for measurement diversity in 3D refractive index microscopy Inproceedings
In: Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVII, pp. 112450X, International Society for Optics and Photonics 2020.
@inproceedings{eckert2020physics,
title = {Physics-based learning for measurement diversity in 3D refractive index microscopy},
author = { Regina Eckert and Michael Kellman and Laura Waller},
url = {https://doi.org/10.1117/12.2543402},
year = {2020},
date = {2020-03-09},
booktitle = {Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVII},
volume = {11245},
pages = {112450X},
organization = {International Society for Optics and Photonics},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Nathan Tessema Ersumo; Cem Yalcin; Nick Antipa; Nicolas C Pégard; Laura Waller; Daniel Lopez; Rikky Muller
Design framework for high-speed 3D scanning tools and development of an axial focusing micromirror-based array Inproceedings
In: MOEMS and Miniaturized Systems XIX, pp. 1129303, International Society for Optics and Photonics 2020.
@inproceedings{ersumo2020design,
title = {Design framework for high-speed 3D scanning tools and development of an axial focusing micromirror-based array},
author = { Nathan Tessema Ersumo and Cem Yalcin and Nick Antipa and Nicolas C Pégard and Laura Waller and Daniel Lopez and Rikky Muller},
url = {https://doi.org/10.1117/12.2550994},
doi = {10.1117/12.2550994},
year = {2020},
date = {2020-02-28},
booktitle = {MOEMS and Miniaturized Systems XIX},
volume = {11293},
pages = {1129303},
organization = {International Society for Optics and Photonics},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Michael Kellman; Emrah Bostan; Michael Lustig; Laura Waller
Data-driven experimental design for computational imaging Inproceedings
In: Quantitative Phase Imaging VI, pp. 1124916, International Society for Optics and Photonics 2020.
@inproceedings{kellman2020data,
title = {Data-driven experimental design for computational imaging},
author = { Michael Kellman and Emrah Bostan and Michael Lustig and Laura Waller},
year = {2020},
date = {2020-02-03},
booktitle = {Quantitative Phase Imaging VI},
volume = {11249},
pages = {1124916},
organization = {International Society for Optics and Photonics},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Kevin Zhang; Michael Kellman; Emrah Bostan; Laura Waller
3D fluorescence deconvolution with deep priors Inproceedings
In: Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVII, pp. 112450N, International Society for Optics and Photonics 2020.
@inproceedings{zhang20203d,
title = {3D fluorescence deconvolution with deep priors},
author = { Kevin Zhang and Michael Kellman and Emrah Bostan and Laura Waller},
year = {2020},
date = {2020-02-03},
booktitle = {Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVII},
volume = {11245},
pages = {112450N},
organization = {International Society for Optics and Photonics},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
David Ren; Colin Ophus; Michael Chen; Laura Waller
A multiple scattering algorithm for three dimensional phase contrast atomic electron tomography Journal Article
In: Ultramicroscopy, vol. 208, pp. 112860, 2020.
@article{ren2020multiple,
title = {A multiple scattering algorithm for three dimensional phase contrast atomic electron tomography},
author = { David Ren and Colin Ophus and Michael Chen and Laura Waller},
url = {https://www.sciencedirect.com/science/article/pii/S030439911930052X},
year = {2020},
date = {2020-01-01},
journal = {Ultramicroscopy},
volume = {208},
pages = {112860},
publisher = {North-Holland},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Ruiming Cao; Michael Kellman; David Ren; Laura Waller
3D Differential Phase Contrast Microscopy with Axial Motion Deblurring Inproceedings
In: Imaging and Applied Optics Congress, pp. CF4C.2, Optical Society of America, 2020.
@inproceedings{Cao:20,
title = {3D Differential Phase Contrast Microscopy with Axial Motion Deblurring},
author = {Ruiming Cao and Michael Kellman and David Ren and Laura Waller},
url = {http://www.osapublishing.org/abstract.cfm?URI=COSI-2020-CF4C.2},
year = {2020},
date = {2020-01-01},
booktitle = {Imaging and Applied Optics Congress},
journal = {Imaging and Applied Optics Congress},
pages = {CF4C.2},
publisher = {Optical Society of America},
abstract = {We demonstrate 3D phase imaging using asymmetric illumination patterns and defocused intensity measurements taken with continuous axial motion. The sample's 3D refractive index is reconstructed with a motion-corrected transfer function.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We demonstrate 3D phase imaging using asymmetric illumination patterns and defocused intensity measurements taken with continuous axial motion. The sample's 3D refractive index is reconstructed with a motion-corrected transfer function.
Grace Kuo; Kristina Monakhova; Kyrollos Yanny; Ren Ng; Laura Waller
Spatially-varying microscope calibration from unstructured sparse inputs Inproceedings
In: Imaging and Applied Optics Congress, pp. CF4C.4, Optical Society of America, 2020.
@inproceedings{Kuo:20,
title = {Spatially-varying microscope calibration from unstructured sparse inputs},
author = {Grace Kuo and Kristina Monakhova and Kyrollos Yanny and Ren Ng and Laura Waller},
url = {http://www.osapublishing.org/abstract.cfm?URI=COSI-2020-CF4C.4},
year = {2020},
date = {2020-01-01},
booktitle = {Imaging and Applied Optics Congress},
journal = {Imaging and Applied Optics Congress},
pages = {CF4C.4},
publisher = {Optical Society of America},
abstract = {We propose a method based on blind deconvolution to calibrate the spatially-varying point spread functions of a coded-aperture microscope system. From easy-to- acquire measurements of unstructured fluorescent beads, we recover a spatially-varying forward model that outperforms prior approaches.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We propose a method based on blind deconvolution to calibrate the spatially-varying point spread functions of a coded-aperture microscope system. From easy-to- acquire measurements of unstructured fluorescent beads, we recover a spatially-varying forward model that outperforms prior approaches.
Ruiming Cao; Michael Kellman; David Ren; Laura Waller
3D Differential Phase Contrast Microscopy with Axial Motion Deblurring Inproceedings
In: Imaging and Applied Optics Congress, pp. CF4C.2, Optical Society of America, 2020.
@inproceedings{Cao:20b,
title = {3D Differential Phase Contrast Microscopy with Axial Motion Deblurring},
author = {Ruiming Cao and Michael Kellman and David Ren and Laura Waller},
url = {http://www.osapublishing.org/abstract.cfm?URI=COSI-2020-CF4C.2},
year = {2020},
date = {2020-01-01},
booktitle = {Imaging and Applied Optics Congress},
journal = {Imaging and Applied Optics Congress},
pages = {CF4C.2},
publisher = {Optical Society of America},
abstract = {We demonstrate 3D phase imaging using asymmetric illumination patterns and defocused intensity measurements taken with continuous axial motion. The sample's 3D refractive index is reconstructed with a motion-corrected transfer function.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We demonstrate 3D phase imaging using asymmetric illumination patterns and defocused intensity measurements taken with continuous axial motion. The sample's 3D refractive index is reconstructed with a motion-corrected transfer function.
Ellin Zhao; Nicolas Deshler; Kristina Monakhova; Laura Waller
Multi-sensor lensless imaging: synthetic large-format sensing with a disjoint sensor array Inproceedings
In: Imaging and Applied Optics Congress, pp. CF2C.6, Optical Society of America, 2020.
@inproceedings{Zhao:20,
title = {Multi-sensor lensless imaging: synthetic large-format sensing with a disjoint sensor array},
author = {Ellin Zhao and Nicolas Deshler and Kristina Monakhova and Laura Waller},
url = {http://www.osapublishing.org/abstract.cfm?URI=COSI-2020-CF2C.6},
year = {2020},
date = {2020-01-01},
booktitle = {Imaging and Applied Optics Congress},
journal = {Imaging and Applied Optics Congress},
pages = {CF2C.6},
publisher = {Optical Society of America},
abstract = {We demonstrate a lensless diffuser-based camera array for large field-of-view imaging. Images are captured from multiple disjoint sensors and the synthetic large format sensing area is recovered by solving a compressive sensing inverse problem.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We demonstrate a lensless diffuser-based camera array for large field-of-view imaging. Images are captured from multiple disjoint sensors and the synthetic large format sensing area is recovered by solving a compressive sensing inverse problem.
Kristina Monakhova; Kyrollos Yanny; Laura Waller
Snapshot hyperspectral imaging using a random phase mask and spectral filter array Inproceedings
In: Imaging and Applied Optics Congress, pp. JF2F.4, Optical Society of America, 2020.
@inproceedings{Monakhova:20,
title = {Snapshot hyperspectral imaging using a random phase mask and spectral filter array},
author = {Kristina Monakhova and Kyrollos Yanny and Laura Waller},
url = {http://www.osapublishing.org/abstract.cfm?URI=COSI-2020-JF2F.4},
year = {2020},
date = {2020-01-01},
booktitle = {Imaging and Applied Optics Congress},
journal = {Imaging and Applied Optics Congress},
pages = {JF2F.4},
publisher = {Optical Society of America},
abstract = {We introduce a snapshot hyperspectral imager that uses a random phase mask, repeated spectral filter array, and compressive recovery to achieve high spatial and spectral resolution in a small form factor.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We introduce a snapshot hyperspectral imager that uses a random phase mask, repeated spectral filter array, and compressive recovery to achieve high spatial and spectral resolution in a small form factor.
Kyrollos Yanny; Nick Antipa; William Liberti; Sam Dehaeck; Kristina Monakhova; Fanglin Linda Liu; Konlin Shen; Ren Ng; Laura Waller
Compressed Sensing 3D Fluorescence Microscopy Using Optimized Phase Mask Inproceedings
In: Imaging and Applied Optics Congress, pp. CW4B.5, Optical Society of America, 2020.
@inproceedings{Yanny:20,
title = {Compressed Sensing 3D Fluorescence Microscopy Using Optimized Phase Mask},
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 = {http://www.osapublishing.org/abstract.cfm?URI=COSI-2020-CW4B.5},
year = {2020},
date = {2020-01-01},
booktitle = {Imaging and Applied Optics Congress},
journal = {Imaging and Applied Optics Congress},
pages = {CW4B.5},
publisher = {Optical Society of America},
abstract = {We demonstrate a single-shot miniature 3D computational microscope with an optimized phase encoder. Our method uses sparsity-based reconstruction to achieve a 2.76-m lateral and 15،nm axial resolution across most of the 900 x 700 x 390،nm3 volume.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We demonstrate a single-shot miniature 3D computational microscope with an optimized phase encoder. Our method uses sparsity-based reconstruction to achieve a 2.76-m lateral and 15،nm axial resolution across most of the 900 x 700 x 390،nm3 volume.
Grace Kuo; Laura Waller; Ren Ng; Andrew Maimone
High Resolution éTendue Expansion for Holographic Displays Journal Article
In: ACM Trans. Graph., vol. 39, no. 4, 2020, ISSN: 0730-0301.
@article{10.1145/3386569.3392414,
title = {High Resolution éTendue Expansion for Holographic Displays},
author = {Grace Kuo and Laura Waller and Ren Ng and Andrew Maimone},
url = {https://doi.org/10.1145/3386569.3392414},
doi = {10.1145/3386569.3392414},
issn = {0730-0301},
year = {2020},
date = {2020-01-01},
journal = {ACM Trans. Graph.},
volume = {39},
number = {4},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
abstract = {Holographic displays can create high quality 3D images while maintaining a small form factor suitable for head-mounted virtual and augmented reality systems. However, holographic displays have limited étendue based on the number of pixels in their spatial light modulators, creating a tradeoff between the eyebox size and the field-of-view. Scattering-based étendue expansion, in which coherent light is focused into an image after being scattered by a static mask, is a promising avenue to break this tradeoff. However, to date, this approach has been limited to very sparse content consisting of, for example, only tens of spots.In this work, we introduce new algorithms to scattering-based étendue expansion that support dense, photorealistic imagery at the native resolution of the spatial light modulator, offering up to a 20 dB improvement in peak signal to noise ratio over baseline methods. We propose spatial and frequency constraints to optimize performance for human perception, and performance is characterized both through simulation and a preliminary benchtop prototype. We further demonstrate the ability to generate content at multiple depths, and we provide a path for the miniaturization of our benchtop prototype into a sunglasses-like form factor.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Holographic displays can create high quality 3D images while maintaining a small form factor suitable for head-mounted virtual and augmented reality systems. However, holographic displays have limited étendue based on the number of pixels in their spatial light modulators, creating a tradeoff between the eyebox size and the field-of-view. Scattering-based étendue expansion, in which coherent light is focused into an image after being scattered by a static mask, is a promising avenue to break this tradeoff. However, to date, this approach has been limited to very sparse content consisting of, for example, only tens of spots.In this work, we introduce new algorithms to scattering-based étendue expansion that support dense, photorealistic imagery at the native resolution of the spatial light modulator, offering up to a 20 dB improvement in peak signal to noise ratio over baseline methods. We propose spatial and frequency constraints to optimize performance for human perception, and performance is characterized both through simulation and a preliminary benchtop prototype. We further demonstrate the ability to generate content at multiple depths, and we provide a path for the miniaturization of our benchtop prototype into a sunglasses-like form factor.
2019
Zachary F Phillips; Sarah Dean; Benjamin Recht; Laura Waller
High-throughput fluorescence microscopy using multi-frame motion deblurring Journal Article
In: Biomedical Optics Express, vol. 11, no. 1, pp. 281–300, 2019.
@article{phillips2020high,
title = {High-throughput fluorescence microscopy using multi-frame motion deblurring},
author = { Zachary F Phillips and Sarah Dean and Benjamin Recht and Laura Waller},
url = {https://doi.org/10.1364/BOE.11.000281},
doi = {10.1364/BOE.11.000281},
year = {2019},
date = {2019-12-16},
journal = {Biomedical Optics Express},
volume = {11},
number = {1},
pages = {281--300},
publisher = {Optical Society of America},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Stuart Sherwin; Isvar Cordova; Laura Waller; Andrew R Neureuther; Patrick P Naulleau
Measuring the Phase of EUV Photomasks Inproceedings
In: International Conference on Extreme Ultraviolet Lithography 2019, pp. 111471F, International Society for Optics and Photonics 2019.
@inproceedings{sherwin2019measuring,
title = {Measuring the Phase of EUV Photomasks},
author = { Stuart Sherwin and Isvar Cordova and Laura Waller and Andrew R Neureuther and Patrick P Naulleau},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11147/111471F/Measuring-the-Phase-of-EUV-Photomasks/10.1117/12.2538107.full},
year = {2019},
date = {2019-11-11},
booktitle = {International Conference on Extreme Ultraviolet Lithography 2019},
volume = {11147},
pages = {111471F},
organization = {International Society for Optics and Photonics},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Matthew Wells; Jesus Deloya Garcia; Shwetadwip Chowdhury; Michael Kellman; Laura Waller; Rachel Pepper
Characterizing the feeding current of sessile microorganisms using digital holography Inproceedings
In: APS Division of Fluid Dynamics , 2019.
@inproceedings{wells2019characterizing,
title = {Characterizing the feeding current of sessile microorganisms using digital holography},
author = { Matthew Wells and Jesus Deloya Garcia and Shwetadwip Chowdhury and Michael Kellman and Laura Waller and Rachel Pepper},
url = {https://ui.adsabs.harvard.edu/abs/2019APS..DFDN05082W/abstract},
year = {2019},
date = {2019-11-01},
booktitle = {APS Division of Fluid Dynamics },
journal = {APS},
volume = {Fall 2019},
number = {NP05--082},
abstract = {Microscopic sessile suspension feeders (MSSFs) are single-celled organisms that live attached to surfaces in freshwater and marine environments. MSSFs generate a feeding current to consume bacteria and debris. They play a vital role in aquatic ecosystems of moving carbon up the food chain. Therefore, characterizing MSSF feeding flow is important for understanding their role in the environment. MSSF feeding flows have only been viewed in 2D and often with samples pressed between two coverslips that distort the flow. However, calculations predict the feeding current forms recirculating eddies when the MSSF body is oriented perpendicular to the surface of attachment. These eddies reduce feeding rate, and as the MSSF tends toward a parallel orientation it is predicted that the eddies disappear. Here we test those predictions by measuring 3D flow around individual Vorticella. Vorticellaare a common and representative MSSF. We use digital holography to record 3D videos of Vorticella in water seeded with 5-10 μm spherical flow tracers. We then use Particle Tracking Velocimetry to find fluid velocity from particle trajectories. },
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Microscopic sessile suspension feeders (MSSFs) are single-celled organisms that live attached to surfaces in freshwater and marine environments. MSSFs generate a feeding current to consume bacteria and debris. They play a vital role in aquatic ecosystems of moving carbon up the food chain. Therefore, characterizing MSSF feeding flow is important for understanding their role in the environment. MSSF feeding flows have only been viewed in 2D and often with samples pressed between two coverslips that distort the flow. However, calculations predict the feeding current forms recirculating eddies when the MSSF body is oriented perpendicular to the surface of attachment. These eddies reduce feeding rate, and as the MSSF tends toward a parallel orientation it is predicted that the eddies disappear. Here we test those predictions by measuring 3D flow around individual Vorticella. Vorticellaare a common and representative MSSF. We use digital holography to record 3D videos of Vorticella in water seeded with 5-10 μm spherical flow tracers. We then use Particle Tracking Velocimetry to find fluid velocity from particle trajectories.
Kristina Monakhova; Joshua Yurtsever; Grace Kuo; Nick Antipa; Kyrollos Yanny; Laura Waller
Learned reconstructions for practical mask-based lensless imaging Journal Article
In: Optics express, vol. 27, no. 20, pp. 28075–28090, 2019.
@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 = {},
pubstate = {published},
tppubtype = {article}
}
Shwetadwip Chowdhury; Michael Chen; Regina Eckert; David Ren; Fan Wu; Nicole A Repina; Laura Waller
High-resolution 3D refractive index microscopy of multiple-scattering samples from intensity images Journal Article
In: Optica, vol. 6, no. 9, pp. 1211–1219, 2019.
@article{chowdhury2019high,
title = {High-resolution 3D refractive index microscopy of multiple-scattering samples from intensity images},
author = { Shwetadwip Chowdhury and Michael Chen and Regina Eckert and David Ren and Fan Wu and Nicole A Repina and Laura Waller},
url = {https://doi.org/10.1364/OPTICA.6.001211},
doi = {10.1364/OPTICA.6.001211},
year = {2019},
date = {2019-09-16},
journal = {Optica},
volume = {6},
number = {9},
pages = {1211--1219},
publisher = {Optical Society of America},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Kristina Monakhova; Joshua Yurtsever; Grace Kuo; Nick Antipa; Kyrollos Yanny; Laura Waller
Unrolled, model-based networks for lensless imaging Journal Article
In: 2019.
@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 = {},
pubstate = {published},
tppubtype = {article}
}
Michael Kellman; Emrah Bostan; Nicole A Repina; Laura Waller
Physics-based learned design: Optimized coded-illumination for quantitative phase imaging Journal Article
In: IEEE Transactions on Computational Imaging, vol. 5, no. 3, pp. 344–353, 2019.
@article{kellman2019physics,
title = {Physics-based learned design: Optimized coded-illumination for quantitative phase imaging},
author = { Michael Kellman and Emrah Bostan and Nicole A Repina and Laura Waller},
url = {https://ieeexplore.ieee.org/document/8667888},
year = {2019},
date = {2019-09-01},
journal = {IEEE Transactions on Computational Imaging},
volume = {5},
number = {3},
pages = {344--353},
publisher = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {article}
}