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Multi-Contrast Imaging and Digital Refocusing on a Mobile Microscope with a Domed LED Array

Overview of attention for article published in PLOS ONE, May 2015
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Title
Multi-Contrast Imaging and Digital Refocusing on a Mobile Microscope with a Domed LED Array
Published in
PLOS ONE, May 2015
DOI 10.1371/journal.pone.0124938
Pubmed ID
Authors

Zachary F. Phillips, Michael V. D'Ambrosio, Lei Tian, Jared J. Rulison, Hurshal S. Patel, Nitin Sadras, Aditya V. Gande, Neil A. Switz, Daniel A. Fletcher, Laura Waller

Abstract

We demonstrate the design and application of an add-on device for improving the diagnostic and research capabilities of CellScope-a low-cost, smartphone-based point-of-care microscope. We replace the single LED illumination of the original CellScope with a programmable domed LED array. By leveraging recent advances in computational illumination, this new device enables simultaneous multi-contrast imaging with brightfield, darkfield, and phase imaging modes. Further, we scan through illumination angles to capture lightfield datasets, which can be used to recover 3D intensity and phase images without any hardware changes. This digital refocusing procedure can be used for either 3D imaging or software-only focus correction, reducing the need for precise mechanical focusing during field experiments. All acquisition and processing is performed on the mobile phone and controlled through a smartphone application, making the computational microscope compact and portable. Using multiple samples and different objective magnifications, we demonstrate that the performance of our device is comparable to that of a commercial microscope. This unique device platform extends the field imaging capabilities of CellScope, opening up new clinical and research possibilities.

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The data shown below were compiled from readership statistics for 133 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 2%
Denmark 1 <1%
Switzerland 1 <1%
Unknown 128 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 32 24%
Researcher 22 17%
Student > Bachelor 11 8%
Student > Master 9 7%
Professor 9 7%
Other 23 17%
Unknown 27 20%
Readers by discipline Count As %
Engineering 43 32%
Physics and Astronomy 27 20%
Computer Science 8 6%
Agricultural and Biological Sciences 6 5%
Psychology 5 4%
Other 14 11%
Unknown 30 23%