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Rapid 3D imaging at cellular resolution for digital cytopathology with a multi-camera array scanner (MCAS)

Medicine and Health

Rapid 3D imaging at cellular resolution for digital cytopathology with a multi-camera array scanner (MCAS)

K. Kim, A. Chaware, et al.

Discover the revolutionary Multi-Camera Array Scanner (MCAS), designed for rapid 3D imaging of thick specimens with stunning high resolution. This breakthrough research by Kanghyun Kim and colleagues from Duke University Medical Center demonstrates how MCAS digitizes cytology samples while integrating machine learning for effective adenocarcinoma detection.

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Playback language: English
Abstract
Optical microscopy is the standard for cytopathology diagnosis, but whole slide scanners are slow and expensive. This paper introduces a Multi-Camera Array Scanner (MCAS) for rapid 3D imaging of thick specimens at high resolution. MCAS uses 48 micro-cameras for parallelized imaging, achieving significantly faster scanning than conventional methods. The authors demonstrate MCAS's use in digitizing entire cytology samples and integrating machine learning for adenocarcinoma detection (0.73 recall) and slide-level classification (0.969 AUC) in lung specimens.
Publisher
npj Imaging
Published On
Oct 01, 2024
Authors
Kanghyun Kim, Amey Chaware, Clare B. Cook, Shiqi Xu, Monica Abdelmalak, Colin Cooke, Kevin C. Zhou, Mark Harfouche, Paul Reamey, Veton Saliu, Jed Doman, Clay Dugo, Gregor Horstmeyer, Richard Davis, Ian Taylor-Cho, Wen-Chi Foo, Lucas Kreiss, Xiaoyin Sara Jiang, Roarke Horstmeyer
Tags
Optical microscopy
Multi-Camera Array Scanner
3D imaging
adenocarcinoma detection
machine learning
cytopathology
high resolution
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