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  1. We present a computational 3D profilometric microscope employing an array of 54 cameras and 3-axis scanning to produce multi-TB datasets per sample. Using stereo and sharpness cues, our self-supervised reconstruction algorithm generates 6-gigapixel reconstructions with micron-scale resolution across >110 cm2
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  2. This paper experimentally examines different configurations of a multi-camera array microscope (MCAM) imaging technology. The MCAM is based upon a densely packed array of “micro-cameras” to jointly image across a large field-of-view (FOV) at high resolution. Each micro-camera within the array images a unique area of a sample of interest, and then all acquired data with 54 micro-cameras are digitally combined into composite frames, whose total pixel counts significantly exceed the pixel counts of standard microscope systems. We present results from three unique MCAM configurations for different use cases. First, we demonstrate a configuration that simultaneously images and estimates the 3D object depth across a 100×135mm2FOV at approximately 20 µm resolution, which results in 0.15 gigapixels (GP) per snapshot. Second, we demonstrate an MCAM configuration that records video across a continuous 83×123mm2FOV with twofold increased resolution (0.48 GP per frame). Finally, we report a third high-resolution configuration (2 µm resolution) that can rapidly produce 9.8 GP composites of large histopathology specimens.

     
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