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Detection and Identification of the Stages of DH5-Alpha Escherichia coli Biofilm Formation on Metal by Using an Artificial Intelligence System

Published online by Cambridge University Press:  04 August 2021

Pei-Chun Wong ,
Tai-En Fan ,
Yu-Lin Lee Open the ORCID record for Yu-Lin Lee [Opens in a new window] ,
Chun-Yu Lai ,
Jia-Lin Wu ,
Ling-Hua Chang  and
Tai-Yuan Su
Pei-Chun Wong
Affiliation:
Department of Orthopedics, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan Department of Orthopedics, Taipei Medical University Hospital, Taipei, Taiwan Orthopedics Research Center, Taipei Medical University Hospital, Taipei, Taiwan
Tai-En Fan
Affiliation:
Department Electrical Engineering, Yuan-Ze University, No. 135, Yuandong Road, Zhongli District, Taoyuan City 320070, Taiwan (R.O.C.)
Yu-Lin Lee
Affiliation:
Department Electrical Engineering, Yuan-Ze University, No. 135, Yuandong Road, Zhongli District, Taoyuan City 320070, Taiwan (R.O.C.)
Chun-Yu Lai
Affiliation:
Department Electrical Engineering, Yuan-Ze University, No. 135, Yuandong Road, Zhongli District, Taoyuan City 320070, Taiwan (R.O.C.)
Jia-Lin Wu
Affiliation:
Department of Orthopedics, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan Department of Orthopedics, Taipei Medical University Hospital, Taipei, Taiwan Orthopedics Research Center, Taipei Medical University Hospital, Taipei, Taiwan Centers for Regional Anesthesia and Pain Medicine, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan
Ling-Hua Chang*
Affiliation:
Department Electrical Engineering, Yuan-Ze University, No. 135, Yuandong Road, Zhongli District, Taoyuan City 320070, Taiwan (R.O.C.)
Tai-Yuan Su*
Affiliation:
Department Electrical Engineering, Yuan-Ze University, No. 135, Yuandong Road, Zhongli District, Taoyuan City 320070, Taiwan (R.O.C.)
*
*Corresponding authors: Ling-Hua Chang, E-mail: iamjaung@ee.yzu.edu.tw; Tai-Yuan Su, E-mail: sutai.tw@gmail.com
*Corresponding authors: Ling-Hua Chang, E-mail: iamjaung@ee.yzu.edu.tw; Tai-Yuan Su, E-mail: sutai.tw@gmail.com
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Abstract

In clinical environments, orthopedic implants are associated with a risk of infection during implantation. However, the growth paths of bacteria on metal, which is nontransparent, are difficult to observe. In this study, we visualized the DH5-alpha Escherichia coli bacterial growth path on the surface of magnesium by using scanning electron microscope (SEM) images and constructed a convolutional neural network-based artificial intelligence (AI) system to identify metal surfaces, bacteria, and its generated products to grade the growth stage of the bacteria implanted on the magnesium. The detection result of the E. coli growth stage by the AI system was close to that manually marked by experts, and it may greatly accelerate the investigation of the bacterial growth process in various types of metallic material.

Keywords

bacterialbiofilmDH5-alphaE. coliSEM
Type
Biological Applications
Information
Microscopy and Microanalysis , Volume 27 , Issue 5 , October 2021 , pp. 1218 - 1225
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Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Microscopy Society of America

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