Automated Identification of Bacteria using Three-Dimensional Holographic Imaging and Convolutional Neural Network

Rapid identification of microbial pathogens is crucial for treating infections. Here we present a rapid method for identification of bacteria. In our method, a trained convolutional neural network classifier can accurately determine the bacterial species from a given three-dimensional refractive ind...

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Bibliographic Details
Main Authors: Kim, Geon, Jo, YoungJu, Cho, Hyungjoo, Choi, Gunho, Kim, Beom-Soo, Min, Hyun-seok, Park, YongKeun
Format: Conference Proceeding
Language:English
Subjects:
3D imaging
artificial intelligence
bacteria
Convolutional neural networks
Microorganisms
neural network
Optical diffraction
quantitative phase imaging
Refractive index
Three-dimensional displays
Tomography
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Description
Summary:Rapid identification of microbial pathogens is crucial for treating infections. Here we present a rapid method for identification of bacteria. In our method, a trained convolutional neural network classifier can accurately determine the bacterial species from a given three-dimensional refractive index image.
ISSN:2575-274X
DOI:10.1109/IPCon.2018.8527133