Detection of protozoan and helminth parasites in concentrated wet mounts of stool using a deep convolutional neural network.

Blaine A Mathison^1,2, Katie Knight³, Jill Potts⁴, Ben Black⁴, John F Walker⁴, Falon Markow⁴, Amy Wood⁴, Dustin Bess⁴, Ken Dixon⁴, Brian Cahoon⁴, Weston Hymas¹, Marc Roger Couturier^1,2

¹Institute for Clinical and Experimental Pathology, ARUP Laboratories, Salt Lake City, Utah, USA.

²Department of Pathology, University of Utah School of Medicine, Salt Lake City, Utah, USA.

³Institute for Research and Innovation in Diagnostic and Precision Medicine, ARUP Laboratories, Salt Lake City, Utah, USA.

⁴Techcyte Inc., Orem, Utah, USA.

PubMed PMC DOI PDF

Abstract

Comprehensive diagnosis of gastrointestinal parasites is largely reliant on traditional stool microscopy, despite gains in molecular diagnostics. Wet-mount examinations remain a significant challenge for traditional microscopy, digital microscopy, and artifical intelligence (AI). We developed and validated a deep convolutional neural network (CNN) model that provides highly sensitive detection and…

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