L
Laura Waller
Researcher at University of California, Berkeley
Publications - 277
Citations - 8163
Laura Waller is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Phase retrieval & Microscope. The author has an hindex of 39, co-authored 252 publications receiving 5831 citations. Previous affiliations of Laura Waller include University of Colorado Boulder & University of California, San Francisco.
Papers
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Multiplexed coded illumination for Fourier Ptychography with an LED array microscope.
TL;DR: A multiplexed illumination strategy in which multiple randomly selected LEDs are turned on for each image so that the total number of images can be significantly reduced, without sacrificing image quality.
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3D intensity and phase imaging from light field measurements in an LED array microscope
Lei Tian,Laura Waller +1 more
TL;DR: In this article, the Fourier ptychography was used to estimate the 3D complex transmittance function of the sample at multiple depths, without any weak or single-scattering approximations.
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DiffuserCam: lensless single-exposure 3D imaging
TL;DR: In this article, a diffuser placed in front of an image sensor is used for single-shot 3D imaging, which exploits sparsity in the sample to solve for more 3D voxels than pixels on the 2D sensor.
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Transport of Intensity phase-amplitude imaging with higher order intensity derivatives
TL;DR: A method for improving the accuracy of phase retrieval based on the Transport of Intensity equation is demonstrated by using intensity measurements at multiple planes to estimate and remove the artifacts due to higher order axial derivatives.
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Experimental robustness of Fourier ptychography phase retrieval algorithms
Li-Hao Yeh,Jonathan Dong,Jingshan Zhong,Lei Tian,Michael Chen,Gongguo Tang,Mahdi Soltanolkotabi,Laura Waller +7 more
TL;DR: In this article, the authors compare and classify multiple Fourier ptychography inverse algorithms in terms of experimental robustness and find that the main sources of error are noise, aberrations and mis-calibration (i.e. model mis-match).