Diffractive all-optical computing for quantitative phase imaging

• URL: http://arxiv.org/abs/2201.08964v1
• Date: Sat, 22 Jan 2022 05:28:44 GMT
• Title: Diffractive all-optical computing for quantitative phase imaging
• Authors: Deniz Mengu and Aydogan Ozcan
• Abstract summary: We demonstrate a diffractive QPI network that can synthesize the quantitative phase image of an object. A diffractive QPI network is a specialized all-optical processor designed to perform a quantitative phase-to-intensity transformation.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Quantitative phase imaging (QPI) is a label-free computational imaging technique that provides optical path length information of specimens. In modern implementations, the quantitative phase image of an object is reconstructed digitally through numerical methods running in a computer, often using iterative algorithms. Here, we demonstrate a diffractive QPI network that can synthesize the quantitative phase image of an object by converting the input phase information of a scene into intensity variations at the output plane. A diffractive QPI network is a specialized all-optical processor designed to perform a quantitative phase-to-intensity transformation through passive diffractive surfaces that are spatially engineered using deep learning and image data. Forming a compact, all-optical network that axially extends only ~200-300 times the illumination wavelength, this framework can replace traditional QPI systems and related digital computational burden with a set of passive transmissive layers. All-optical diffractive QPI networks can potentially enable power-efficient, high frame-rate and compact phase imaging systems that might be useful for various applications, including, e.g., on-chip microscopy and sensing.

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