Large-scale compressive microscopy via diffractive multiplexing across a sensor array
Kevin C. Zhou, Chaoying Gu, Muneki Ikeda, Tina M. Hayward, Nicholas Antipa, Rajesh Menon, Roarke Horstmeyer, Saul Kato, and Laura Waller

TL;DR
This paper introduces a large-scale compressive microscopy system using a sensor array and diffractive optical elements, enabling high-resolution, wide-field, high-speed imaging through computational reconstruction.
Contribution
It presents a novel snapshot gigapixel-scale microscope combining sensor arrays and PSF engineering with compressive sensing, achieving unprecedented throughput and resolution.
Findings
Achieves ~3 μm resolution over >5.2 cm² FOVs at 120 fps
Total spatiotemporal throughput of 25.2 billion pixels/sec
Demonstrates structural and functional imaging of C. elegans
Abstract
Microscopes face a trade-off between spatial resolution, field-of-view, and frame rate -- improving one of these properties typically requires sacrificing the others, due to the limited spatiotemporal throughput of the sensor. To overcome this, we propose a new microscope that achieves snapshot gigapixel-scale imaging with a sensor array and a diffractive optical element (DOE). We improve the spatiotemporal throughput in two ways. First, we capture data with an array of 48 sensors resulting in 48x more pixels than a single sensor. Second, we use point spread function (PSF) engineering and compressive sensing algorithms to fill in the missing information from the gaps surrounding the individual sensors in the array, further increasing the spatiotemporal throughput of the system by an additional >5.4x. The array of sensors is modeled as a single large-format "super-sensor," with erasures…
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