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Automated Disease Identification using computational 3D Optical Sensing and Imaging Systems

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Abstract

In this invited paper, we present an overview of our reported work on 3D sensing and imaging applied to automated cell identification. The sensing and imaging methods include digital holographic imaging, interferometric systems, and integral imaging. We show that 3D sensing and imaging approaches combined with appropriate pattern recognition algorithms provide an impressive approach for automated cell identification with compact field portable systems.

© 2016 Optical Society of America

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