Publications
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.
Links | BibTeX | Tags: algorithms, computational imaging, experimental design, learning-based, LED array, memory efficient, memory-efficient, physics-based
@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 = {algorithms, computational imaging, experimental design, learning-based, LED array, memory efficient, memory-efficient, physics-based},
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.
Abstract | Links | BibTeX | Tags: 3D imaging, algorithms, diffuser, fluorescence imaging
@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}
}
Michael Kellman
Physics-based Learning for Large-scale Computational Imaging PhD Thesis
EECS Department, University of California, Berkeley, 2020.
Abstract | Links | BibTeX | Tags: algorithms, computational imaging, experimental design, learning-based, LED array, memory efficient, memory-efficient, physics-based
@phdthesis{Kellman:EECS-2020-167,
title = {Physics-based Learning for Large-scale Computational Imaging},
author = {Michael Kellman},
url = {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2020/EECS-2020-167.html},
year = {2020},
date = {2020-08-01},
number = {UCB/EECS-2020-167},
school = {EECS Department, University of California, Berkeley},
abstract = {In computational imaging systems (e.g. tomographic systems, computational optics, magnetic resonance imaging) the acquisition of data and reconstruction of images are co-designed to retrieve information which is not traditionally accessible. The performance of such systems is characterized by how information is encoded to (forward process) and decoded from (inverse problem) the measurements. Recently, critical aspects of these systems, such as their signal prior, have been optimized using deep neural networks formed from unrolling the iterations of a physics-based image reconstruction.
In this dissertation, I will detail my work, physics-based learned design, to optimize the performance of the entire computational imaging system by jointly learning aspects of its experimental design and computational reconstruction. As an application, I introduce how the LED-array microscope performs super-resolved quantitative phase imaging and demonstrate how physics-based learning can optimize a reduced set of measurements without sacrificing performance to enable the imaging of live fast moving biology.
In this dissertation's latter half, I will discuss how to overcome some of the computational challenges encountered in applying physics-based learning concepts to large-scale computational imaging systems. I will describe my work, memory-efficient learning, that makes physics-based learning for large-scale systems feasible on commercially-available graphics processing units. I demonstrate this method on two large-scale real-world systems: 3D multi-channel compressed sensing MRI and super-resolution optical microscopy.},
keywords = {algorithms, computational imaging, experimental design, learning-based, LED array, memory efficient, memory-efficient, physics-based},
pubstate = {published},
tppubtype = {phdthesis}
}
In this dissertation, I will detail my work, physics-based learned design, to optimize the performance of the entire computational imaging system by jointly learning aspects of its experimental design and computational reconstruction. As an application, I introduce how the LED-array microscope performs super-resolved quantitative phase imaging and demonstrate how physics-based learning can optimize a reduced set of measurements without sacrificing performance to enable the imaging of live fast moving biology.
In this dissertation's latter half, I will discuss how to overcome some of the computational challenges encountered in applying physics-based learning concepts to large-scale computational imaging systems. I will describe my work, memory-efficient learning, that makes physics-based learning for large-scale systems feasible on commercially-available graphics processing units. I demonstrate this method on two large-scale real-world systems: 3D multi-channel compressed sensing MRI and super-resolution optical microscopy.
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.
Links | BibTeX | Tags: algorithms, learning-based, LED array, measurement diversity, phase imaging, physics-based, self-calibration
@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 = {algorithms, learning-based, LED array, measurement diversity, phase imaging, physics-based, self-calibration},
pubstate = {published},
tppubtype = {article}
}
Stuart Sherwin; Isvar Cordova; Ryan Miyakawa; Laura Waller; Andrew Neureuther; Patrick Naulleau
Quantitative phase retrieval for EUV photomasks Proceedings Article
In: Felix, Nelson M; Lio, Anna (Ed.): Extreme Ultraviolet (EUV) Lithography XI, pp. 234 – 243, International Society for Optics and Photonics SPIE, 2020.
Links | BibTeX | Tags: algorithms, EUV, phase imaging
@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 = {algorithms, EUV, phase imaging},
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.
Links | BibTeX | Tags: 3D imaging, algorithms, multiple-scattering, phase imaging, TEM
@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 = {3D imaging, algorithms, multiple-scattering, phase imaging, TEM},
pubstate = {published},
tppubtype = {article}
}
Henry Pinkard; Zachary F Phillips; Arman Babakhani; Daniel A Fletcher; Laura Waller
Deep learning for single-shot autofocus microscopy Journal Article
In: Optica, vol. 6, no. 6, pp. 794–797, 2019.
Links | BibTeX | Tags: algorithms, high-throughput, LED array
@article{pinkard2019deep,
title = {Deep learning for single-shot autofocus microscopy},
author = { Henry Pinkard and Zachary F Phillips and Arman Babakhani and Daniel A Fletcher and Laura Waller},
url = {https://www.osapublishing.org/optica/abstract.cfm?uri=optica-6-6-794},
year = {2019},
date = {2019-06-20},
journal = {Optica},
volume = {6},
number = {6},
pages = {794--797},
publisher = {Optical Society of America},
keywords = {algorithms, high-throughput, LED array},
pubstate = {published},
tppubtype = {article}
}
Zachary F Phillips
Quantitative Microscopy using Coded Illumination PhD Thesis
University of California, Berkeley, 2019.
Links | BibTeX | Tags: algorithms, DPC, LED array, motion deblur, self-calibration
@phdthesis{phillips2019quant,
title = {Quantitative Microscopy using Coded Illumination},
author = {Zachary F Phillips},
url = {https://escholarship.org/uc/item/70d9j190
https://search.proquest.com/openview/ac36264c1a5b90ee3c8e4085759b0cc4/1?pq-origsite=gscholar&cbl=18750&diss=y},
year = {2019},
date = {2019-05-01},
school = {University of California, Berkeley},
keywords = {algorithms, DPC, LED array, motion deblur, self-calibration},
pubstate = {published},
tppubtype = {phdthesis}
}
Zachary F Phillips; Sarah Dean; Benjamin Recht; Laura Waller
High-throughput Fluorescence Microscopy using Motion Deblurring Proceedings Article
In: Focus on Microscopy 2019.
Links | BibTeX | Tags: algorithms, fluorescence imaging, high-resolution, motion deblur
@inproceedings{phillipshigh,
title = {High-throughput Fluorescence Microscopy using Motion Deblurring},
author = { Zachary F Phillips and Sarah Dean and Benjamin Recht and Laura Waller},
url = {http://www.focusonmicroscopy.org/2019/PDF/1457_Phillips.pdf},
year = {2019},
date = {2019-04-14},
organization = {Focus on Microscopy},
keywords = {algorithms, fluorescence imaging, high-resolution, motion deblur},
pubstate = {published},
tppubtype = {inproceedings}
}
Emrah Bostan; Mahdi Soltanolkotabi; David Ren; Laura Waller
Accelerated Wirtinger flow for multiplexed Fourier ptychographic microscopy Proceedings Article
In: 2018 25th IEEE International Conference on Image Processing (ICIP), pp. 3823–3827, IEEE 2018.
Links | BibTeX | Tags: algorithms, FPM, multiplexed illumination
@inproceedings{bostan2018accelerated,
title = {Accelerated Wirtinger flow for multiplexed Fourier ptychographic microscopy},
author = { Emrah Bostan and Mahdi Soltanolkotabi and David Ren and Laura Waller},
url = {https://doi.org/10.1109/ICIP.2018.8451437},
doi = {10.1109/ICIP.2018.8451437},
year = {2018},
date = {2018-10-07},
booktitle = {2018 25th IEEE International Conference on Image Processing (ICIP)},
pages = {3823--3827},
organization = {IEEE},
keywords = {algorithms, FPM, multiplexed illumination},
pubstate = {published},
tppubtype = {inproceedings}
}
Colin Ophus; David Ren; Michael Chen; Catherine Groschner; Mary C Scott; Laura Waller
Linear and Nonlinear Reconstruction Algorithms for Atomic-Resolution Tomography Using Phase Contrast Electron Microscopy Journal Article
In: Microscopy and Microanalysis, vol. 24, no. S1, pp. 110–111, 2018.
Links | BibTeX | Tags: 3D imaging, algorithms, phase imaging, TEM
@article{ophus2018linear,
title = {Linear and Nonlinear Reconstruction Algorithms for Atomic-Resolution Tomography Using Phase Contrast Electron Microscopy},
author = { Colin Ophus and David Ren and Michael Chen and Catherine Groschner and Mary C Scott and Laura Waller},
url = {https://doi.org/10.1017/S1431927618001046},
doi = {10.1017/S1431927618001046},
year = {2018},
date = {2018-08-01},
journal = {Microscopy and Microanalysis},
volume = {24},
number = {S1},
pages = {110--111},
publisher = {Cambridge University Press},
keywords = {3D imaging, algorithms, phase imaging, TEM},
pubstate = {published},
tppubtype = {article}
}
Regina Eckert; Zachary F Phillips; Laura Waller
Efficient illumination angle self-calibration in Fourier ptychography Journal Article
In: Applied Optics, vol. 57, no. 19, pp. 5434–5442, 2018.
Links | BibTeX | Tags: algorithms, FPM, LED array, phase imaging, self-calibration
@article{eckert2018efficient,
title = {Efficient illumination angle self-calibration in Fourier ptychography},
author = { Regina Eckert and Zachary F Phillips and Laura Waller},
url = {https://doi.org/10.1364/AO.57.005434},
year = {2018},
date = {2018-06-28},
journal = {Applied Optics},
volume = {57},
number = {19},
pages = {5434--5442},
publisher = {Optical Society of America},
keywords = {algorithms, FPM, LED array, phase imaging, self-calibration},
pubstate = {published},
tppubtype = {article}
}
Emrah Bostan; Ulugbek S Kamilov; Laura Waller
Learning-based image reconstruction via parallel proximal algorithm Journal Article
In: IEEE Signal Processing Letters, vol. 25, no. 7, pp. 989–993, 2018.
Links | BibTeX | Tags: algorithms, fluorescence imaging, learning-based, regularization
@article{bostan2018learning,
title = {Learning-based image reconstruction via parallel proximal algorithm},
author = { Emrah Bostan and Ulugbek S Kamilov and Laura Waller},
url = {https://doi.org/10.1109/LSP.2018.2833812},
doi = {10.1109/LSP.2018.2833812},
year = {2018},
date = {2018-05-07},
journal = {IEEE Signal Processing Letters},
volume = {25},
number = {7},
pages = {989--993},
publisher = {IEEE},
keywords = {algorithms, fluorescence imaging, learning-based, regularization},
pubstate = {published},
tppubtype = {article}
}
Hsiou-Yuan Liu; Dehong Liu; Hassan Mansour; Petros T Boufounos; Laura Waller; Ulugbek S Kamilov
SEAGLE: Sparsity-driven image reconstruction under multiple scattering Journal Article
In: IEEE Transactions on Computational Imaging, vol. 4, no. 1, pp. 73–86, 2017.
Links | BibTeX | Tags: algorithms, multiple-scattering, optical models
@article{liu2017seagle,
title = {SEAGLE: Sparsity-driven image reconstruction under multiple scattering},
author = { Hsiou-Yuan Liu and Dehong Liu and Hassan Mansour and Petros T Boufounos and Laura Waller and Ulugbek S Kamilov},
url = {https://doi.org/10.1109/TCI.2017.2764461},
doi = {10.1109/TCI.2017.2764461},
year = {2017},
date = {2017-10-19},
journal = {IEEE Transactions on Computational Imaging},
volume = {4},
number = {1},
pages = {73--86},
publisher = {IEEE},
keywords = {algorithms, multiple-scattering, optical models},
pubstate = {published},
tppubtype = {article}
}
Jingzhao Zhang; Nicolas C Pégard; Jingshan Zhong; Hillel Adesnik; Laura Waller
3D computer-generated holography by non-convex optimization Journal Article
In: Optica, vol. 4, no. 10, pp. 1306–1313, 2017.
Links | BibTeX | Tags: 3D imaging, algorithms, digital holography, fluorescence imaging, neural imaging
@article{zhang20173d,
title = {3D computer-generated holography by non-convex optimization},
author = { Jingzhao Zhang and Nicolas C Pégard and Jingshan Zhong and Hillel Adesnik and Laura Waller},
url = {https://doi.org/10.1364/OPTICA.4.001306},
doi = {10.1364/OPTICA.4.001306},
year = {2017},
date = {2017-10-19},
journal = {Optica},
volume = {4},
number = {10},
pages = {1306--1313},
publisher = {Optical Society of America},
keywords = {3D imaging, algorithms, digital holography, fluorescence imaging, neural imaging},
pubstate = {published},
tppubtype = {article}
}
Li-Hao Yeh; Nicole A Repina; Laura Waller
3D structured illumination microscopy with unknown patterns and a statistical prior Proceedings Article
In: 3D Image Acquisition and Display: Technology, Perception and Applications, pp. DW2F–3, Optical Society of America 2017.
Links | BibTeX | Tags: 3D imaging, algorithms, self-calibration, structured illumination
@inproceedings{yeh20173d,
title = {3D structured illumination microscopy with unknown patterns and a statistical prior},
author = { Li-Hao Yeh and Nicole A Repina and Laura Waller},
url = {https://doi.org/10.1364/3D.2017.DW2F.3},
doi = {10.1364/3D.2017.DW2F.3},
year = {2017},
date = {2017-06-26},
booktitle = {3D Image Acquisition and Display: Technology, Perception and Applications},
pages = {DW2F--3},
organization = {Optical Society of America},
keywords = {3D imaging, algorithms, self-calibration, structured illumination},
pubstate = {published},
tppubtype = {inproceedings}
}
David Ren; Emrah Bostan; Li-Hao Yeh; Laura Waller
Total-variation regularized Fourier ptychographic microscopy with multiplexed coded illumination Proceedings Article
In: Mathematics in Imaging, pp. MM3C–5, Optical Society of America 2017.
Links | BibTeX | Tags: algorithms, FPM, LED array, multiplexed illumination
@inproceedings{ren2017total,
title = {Total-variation regularized Fourier ptychographic microscopy with multiplexed coded illumination},
author = { David Ren and Emrah Bostan and Li-Hao Yeh and Laura Waller},
url = {https://doi.org/10.1364/MATH.2017.MM3C.5},
doi = {10.1364/MATH.2017.MM3C.5},
year = {2017},
date = {2017-06-26},
booktitle = {Mathematics in Imaging},
pages = {MM3C--5},
organization = {Optical Society of America},
keywords = {algorithms, FPM, LED array, multiplexed illumination},
pubstate = {published},
tppubtype = {inproceedings}
}
Lei Tian; Li-hao Yeh; Regina Eckert; Laura Waller
Computational microscopy: illumination coding and nonlinear optimization enables gigapixel 3D phase imaging Proceedings Article
In: 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 6225–6229, IEEE 2017.
Links | BibTeX | Tags: 3D imaging, algorithms, FPM, high-throughput, LED array, phase imaging
@inproceedings{tian2017computational,
title = {Computational microscopy: illumination coding and nonlinear optimization enables gigapixel 3D phase imaging},
author = { Lei Tian and Li-hao Yeh and Regina Eckert and Laura Waller},
url = {https://doi.org/10.1109/ICASSP.2017.7953353},
year = {2017},
date = {2017-06-19},
booktitle = {2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
pages = {6225--6229},
organization = {IEEE},
keywords = {3D imaging, algorithms, FPM, high-throughput, LED array, phase imaging},
pubstate = {published},
tppubtype = {inproceedings}
}
Li-Hao Yeh; Lei Tian; Laura Waller
Structured illumination microscopy with unknown patterns and a statistical prior Journal Article
In: Biomedical optics express, vol. 8, no. 2, pp. 695–711, 2017.
Links | BibTeX | Tags: algorithms, self-calibration, structured illumination
@article{yeh2017structured,
title = {Structured illumination microscopy with unknown patterns and a statistical prior},
author = { Li-Hao Yeh and Lei Tian and Laura Waller},
url = {https://doi.org/10.1364/BOE.8.000695},
doi = {10.1364/BOE.8.000695},
year = {2017},
date = {2017-02-01},
journal = {Biomedical optics express},
volume = {8},
number = {2},
pages = {695--711},
publisher = {Optical Society of America},
keywords = {algorithms, self-calibration, structured illumination},
pubstate = {published},
tppubtype = {article}
}
Nicolas C Pégard; Hsiou-Yuan Liu; Nick Antipa; Maximillian Gerlock; Hillel Adesnik; Laura Waller
Recording 3-D Neural Activity Online
Optics & Photonics News 2016, visited: 17.04.2020.
Links | BibTeX | Tags: 3D imaging, algorithms, fluorescence imaging, neural imaging
@online{pegardrecording,
title = {Recording 3-D Neural Activity},
author = { Nicolas C Pégard and Hsiou-Yuan Liu and Nick Antipa and Maximillian Gerlock and Hillel Adesnik and Laura Waller},
url = {https://www.osa-opn.org/home/articles/volume_27/december_2016/extras/recording_3-d_neural_activity/},
year = {2016},
date = {2016-12-01},
urldate = {2020-04-17},
organization = {Optics & Photonics News},
keywords = {3D imaging, algorithms, fluorescence imaging, neural imaging},
pubstate = {published},
tppubtype = {online}
}
Jingzhao Zhang; Jingshan Zhong; Laura Waller
Nonlinear optimization for partially coherent phase recovery with Abbe’s method Proceedings Article
In: Digital Holography and Three-Dimensional Imaging, pp. JT3A–27, Optical Society of America 2016.
Links | BibTeX | Tags: algorithms, nonlinear optimization, partial coherence, phase imaging
@inproceedings{zhang2016nonlinear,
title = {Nonlinear optimization for partially coherent phase recovery with Abbe’s method},
author = { Jingzhao Zhang and Jingshan Zhong and Laura Waller},
url = {https://doi.org/10.1364/3D.2016.JT3A.27},
doi = {10.1364/3D.2016.JT3A.27},
year = {2016},
date = {2016-07-25},
booktitle = {Digital Holography and Three-Dimensional Imaging},
pages = {JT3A--27},
organization = {Optical Society of America},
keywords = {algorithms, nonlinear optimization, partial coherence, phase imaging},
pubstate = {published},
tppubtype = {inproceedings}
}
Jingshan Zhong; Lei Tian; Paroma Varma; Laura Waller
Nonlinear optimization algorithm for partially coherent phase retrieval and source recovery Journal Article
In: IEEE Transactions on Computational Imaging, vol. 2, no. 3, pp. 310–322, 2016.
Links | BibTeX | Tags: algorithms, LED array, nonlinear optimization, partial coherence, phase from defocus, phase imaging
@article{zhong2016nonlinear,
title = {Nonlinear optimization algorithm for partially coherent phase retrieval and source recovery},
author = { Jingshan Zhong and Lei Tian and Paroma Varma and Laura Waller},
url = {https://doi.org/10.1109/TCI.2016.2571669},
doi = {10.1109/TCI.2016.2571669},
year = {2016},
date = {2016-05-23},
journal = {IEEE Transactions on Computational Imaging},
volume = {2},
number = {3},
pages = {310--322},
publisher = {IEEE},
keywords = {algorithms, LED array, nonlinear optimization, partial coherence, phase from defocus, phase imaging},
pubstate = {published},
tppubtype = {article}
}
Gili Dardikman; Mor Habaza; Laura Waller; Natan T Shaked
Video-rate processing in tomographic phase microscopy of biological cells using CUDA Journal Article
In: Optics express, vol. 24, no. 11, pp. 11839–11854, 2016.
Links | BibTeX | Tags: 3D imaging, algorithms
@article{dardikman2016video,
title = {Video-rate processing in tomographic phase microscopy of biological cells using CUDA},
author = { Gili Dardikman and Mor Habaza and Laura Waller and Natan T Shaked},
url = {https://doi.org/10.1364/OE.24.011839},
doi = {10.1364/OE.24.011839},
year = {2016},
date = {2016-05-23},
journal = {Optics express},
volume = {24},
number = {11},
pages = {11839--11854},
publisher = {Optical Society of America},
keywords = {3D imaging, algorithms},
pubstate = {published},
tppubtype = {article}
}
Li-Hao Yeh; Jonathan Dong; Jingshan Zhong; Lei Tian; Michael Chen; Gongguo Tang; Mahdi Soltanolkotabi; Laura Waller
Experimental robustness of Fourier ptychography phase retrieval algorithms Journal Article
In: Optics express, vol. 23, no. 26, pp. 33214–33240, 2015.
Links | BibTeX | Tags: algorithms, FPM, high-resolution, high-throughput, LED array, phase imaging
@article{yeh2015experimental,
title = {Experimental robustness of Fourier ptychography phase retrieval algorithms},
author = { Li-Hao Yeh and Jonathan Dong and Jingshan Zhong and Lei Tian and Michael Chen and Gongguo Tang and Mahdi Soltanolkotabi and Laura Waller},
url = {https://doi.org/10.1364/OE.23.033214},
doi = {10.1364/OE.23.033214},
year = {2015},
date = {2015-12-16},
journal = {Optics express},
volume = {23},
number = {26},
pages = {33214--33240},
publisher = {Optical Society of America},
keywords = {algorithms, FPM, high-resolution, high-throughput, LED array, phase imaging},
pubstate = {published},
tppubtype = {article}
}
Rene A Claus; Patrick P Naulleau; Andrew R Neureuther; Laura Waller
Quantitative phase retrieval with arbitrary pupil and illumination Journal Article
In: Optics express, vol. 23, no. 20, pp. 26672–26682, 2015.
Links | BibTeX | Tags: algorithms, EUV, phase imaging
@article{claus2015quantitative,
title = {Quantitative phase retrieval with arbitrary pupil and illumination},
author = { Rene A Claus and Patrick P Naulleau and Andrew R Neureuther and Laura Waller},
url = {https://doi.org/10.1364/OE.23.026672},
doi = {10.1364/OE.23.026672},
year = {2015},
date = {2015-10-02},
journal = {Optics express},
volume = {23},
number = {20},
pages = {26672--26682},
publisher = {Optical Society of America},
keywords = {algorithms, EUV, phase imaging},
pubstate = {published},
tppubtype = {article}
}