John Efromson, Giuliano Ferrero, Aurélien Bègue, Thomas Jedidiah Jenks Doman, Clay Dugo, Andi Barker, Veton Saliu, Paul Reamey, Kanghyun Kim, Mark Harfouche, Jeffrey A. Yoder

This study introduces a rapid, high-throughput approach using the Multi-Camera Array Microscope (MCAM™) to image and quantify neutrophils in zebrafish embryos—a key indicator of environmental impacts on immune function. Using advanced machine learning, the system is able to process and count individual fluorescent neutrophils across a 96-well plate in just over 5 minutes, offering a rapid and accurate alternative to traditional manual counting methods.

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NATURE PHOTONICS

Mar 2023

Parallelized computational 3D video microscopy of freely moving organisms at multiple gigapixels per second

AUTHORS:

Kevin C. Zhou, Mark Harfouche, Colin L. Cooke, Jaehee Park, Pavan C. Konda, Lucas Kreiss, Kanghyun Kim, Joakim Jönsson, Thomas Doman, Paul Reamey, Veton Saliu, Clare B. Cook, Maxwell Zheng, John P. Bechtel, Aurélien Bègue, Matthew McCarroll, Jennifer Bagwell, Gregor Horstmeyer, Michel Bagnat & Roarke Horstmeyer

This article demonstrates how wide-field-of-view microscopy with Ramona’s Multi-Camera Array Microscope (MCAM™) can resolve three-dimensional information at high speed and spatial resolution. It then shows how this technology can serve as a powerful tool for studying the behavior of freely moving organisms, such as ants, fruit flies, and zebrafish larvae.

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OPTICA

Feb 2023

Imaging across multiple spatial scales with the multi-camera array microscope

AUTHORS:

Mark Harfouche, Kanghyun Kim, Kevin C. Zhou, Pavan Chandra Konda, Sunanda Sharma, Eric E. Thomson, Colin Cooke, Shiqi Xu, Lucas Kreiss, Amey Chaware, Xi Yang, Xing Yao, Vinayak Pathak, Martin Bohlen, Ron Appel, Aurélien Bègue, Clare Cook, Jed Doman, John Efromson, Gregor Horstmeyer, Jaehee Park, Paul Reamey, Veton Saliu, Eva Naumann, and Roarke Horstmeyer

This publication presents results from three unique Multi-Camera Array Microscope (MCAM™) configurations for different use cases. These configurations include simultaneous capture with 3D object depth estimation, continuous video capture at high resolution over a large field of view, and a high-resolution configuration to produce 9.8 GP composites of large histopathology specimens.

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ELIFE

Dec 2022

Gigapixel imaging with a novel multi-camera array microscope

AUTHORS:

Eric E Thomson, Mark Harfouche, Kanghyun Kim, Pavan C Konda, Catherine W Seitz, Colin Cooke, Shiqi Xu, Whitney S Jacobs, Robin Blazing, Yang Chen, Sunanda Sharma, Timothy W Dunn, Jaehee Park, Roarke W Horstmeyer, Eva A Naumann

This paper details how Ramona’s Multi-Camera Array Microscope (MCAM™) enables comprehensive high-resolution recording from multiple spatial scales simultaneously, ranging from cellular-scale structures to large-group behavioral dynamics. This allows researchers to observe the behavior and fine anatomical features of numerous freely moving model organisms on multiple spatial scales, including larval zebrafish, fruit flies, nematodes, carpenter ants, and slime mold.

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MDPI AGRICULTURE

Sep 2022

Species Identification of Caterpillar Eggs by Machine Learning Using a Convolutional Neural Network and Massively Parallelized Microscope

AUTHORS:

John Efromson, Roger Lawrie, Thomas Jedidiah Jenks Doman, Matthew Bertone, Aurélien Bègue, Mark Harfouche, Dominic Reisig and R. Michael Roe

This research demonstrates a machine learning technique for swift and precise insect egg identification using Ramona's Multi-Camera Array Microscope (MCAM™), distinguishing two crucial pest species with more than 99% accuracy. Validated with around 5500 images, the approach suggests new avenues for real-time agricultural pest diagnostics.

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OPTICA

Aug 2021

High throughput acquisition and analysis of bacterial colony features using gigapixel microscopy

AUTHORS:

Sunanda Sharma, Aurélien Bègue, Jed Doman, Mark Harfouche, Gregor Horstmeyer, and Roarke Horstmeyer

This paper details how Ramona’s Multi-Camera Array Microscope (MCAM™) can quantify morphological features in bacterial colonies across multi-well plates. It shows how the system can be used to augment high-throughput assays by synchronously capturing valuable phenotypic information throughout an acquisition and analysis pipeline.

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