iTB-test: An Intelligent Image-enabled Diagnostic System for In Vitro Screening of Infectious Diseases

Marzia Hoque Tania; M. Shamim Kaiser; Antesar M. Shabut; Kamal Abu-Hassan; Mufti Mahmud; M. A. Hossain

doi:10.1109/SKIMA57145.2022.10029556

iTB-test: An Intelligent Image-enabled Diagnostic System for In Vitro Screening of Infectious Diseases

Marzia Hoque Tania, M. Shamim Kaiser, Antesar M. Shabut, Kamal Abu-Hassan, Mufti Mahmud, M. A. Hossain

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper performs an investigation into the development of an intelligent image-based automatic in vitro diagnostic system for infectious diseases using personal devices. The proposed framework of the image-based diagnostic system is demonstrated using the case study of Tuberculosis (TB)-specific antibody detection. The developed system, denoted as the iTB-test, is an intelligent bio-sensing system, comprised of a plasmonic Enzyme-Linked Immunosorbent Assay based colourimetric test in combination with an artificial intelligence-enabled image-based system. The presented system can separate the region of interest with 99.62% accuracy using clustering-based hybrid image processing algorithms, whereas the classification accuracy of antibody detection using a supervised machine learning technique is 100% based on the experiments conducted for the case study.

Original language	English
Title of host publication	14th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-6
Number of pages	6
ISBN (Electronic)	9781665493345
DOIs	https://doi.org/10.1109/SKIMA57145.2022.10029556
State	Published - 2022
Externally published	Yes
Event	14th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2022 - Phnom Penh, Cambodia Duration: 2 Dec 2022 → 4 Dec 2022

Publication series

Name	International Conference on Software, Knowledge Information, Industrial Management and Applications, SKIMA
Volume	2022-December
ISSN (Print)	2373-082X
ISSN (Electronic)	2573-3214

Conference

Conference	14th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2022
Country/Territory	Cambodia
City	Phnom Penh
Period	2/12/22 → 4/12/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

artificial intelligence
digital health
histogram thresholding
machine learning
mobile health

ASJC Scopus subject areas

Computer Science Applications
Software
Information Systems
Information Systems and Management

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/SKIMA57145.2022.10029556

Cite this

Tania, M. H., Kaiser, M. S., Shabut, A. M., Abu-Hassan, K., Mahmud, M., & Hossain, M. A. (2022). iTB-test: An Intelligent Image-enabled Diagnostic System for In Vitro Screening of Infectious Diseases. In 14th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2022 (pp. 1-6). (International Conference on Software, Knowledge Information, Industrial Management and Applications, SKIMA; Vol. 2022-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SKIMA57145.2022.10029556

Tania, Marzia Hoque ; Kaiser, M. Shamim ; Shabut, Antesar M. et al. / iTB-test : An Intelligent Image-enabled Diagnostic System for In Vitro Screening of Infectious Diseases. 14th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2022. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 1-6 (International Conference on Software, Knowledge Information, Industrial Management and Applications, SKIMA).

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title = "iTB-test: An Intelligent Image-enabled Diagnostic System for In Vitro Screening of Infectious Diseases",

abstract = "This paper performs an investigation into the development of an intelligent image-based automatic in vitro diagnostic system for infectious diseases using personal devices. The proposed framework of the image-based diagnostic system is demonstrated using the case study of Tuberculosis (TB)-specific antibody detection. The developed system, denoted as the iTB-test, is an intelligent bio-sensing system, comprised of a plasmonic Enzyme-Linked Immunosorbent Assay based colourimetric test in combination with an artificial intelligence-enabled image-based system. The presented system can separate the region of interest with 99.62% accuracy using clustering-based hybrid image processing algorithms, whereas the classification accuracy of antibody detection using a supervised machine learning technique is 100% based on the experiments conducted for the case study.",

keywords = "artificial intelligence, digital health, histogram thresholding, machine learning, mobile health",

author = "Tania, {Marzia Hoque} and Kaiser, {M. Shamim} and Shabut, {Antesar M.} and Kamal Abu-Hassan and Mufti Mahmud and Hossain, {M. A.}",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 14th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2022 ; Conference date: 02-12-2022 Through 04-12-2022",

year = "2022",

doi = "10.1109/SKIMA57145.2022.10029556",

language = "English",

series = "International Conference on Software, Knowledge Information, Industrial Management and Applications, SKIMA",

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Tania, MH, Kaiser, MS, Shabut, AM, Abu-Hassan, K, Mahmud, M & Hossain, MA 2022, iTB-test: An Intelligent Image-enabled Diagnostic System for In Vitro Screening of Infectious Diseases. in 14th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2022. International Conference on Software, Knowledge Information, Industrial Management and Applications, SKIMA, vol. 2022-December, Institute of Electrical and Electronics Engineers Inc., pp. 1-6, 14th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2022, Phnom Penh, Cambodia, 2/12/22. https://doi.org/10.1109/SKIMA57145.2022.10029556

iTB-test: An Intelligent Image-enabled Diagnostic System for In Vitro Screening of Infectious Diseases. / Tania, Marzia Hoque; Kaiser, M. Shamim; Shabut, Antesar M. et al.
14th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 1-6 (International Conference on Software, Knowledge Information, Industrial Management and Applications, SKIMA; Vol. 2022-December).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Abu-Hassan, Kamal

AU - Mahmud, Mufti

AU - Hossain, M. A.

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N2 - This paper performs an investigation into the development of an intelligent image-based automatic in vitro diagnostic system for infectious diseases using personal devices. The proposed framework of the image-based diagnostic system is demonstrated using the case study of Tuberculosis (TB)-specific antibody detection. The developed system, denoted as the iTB-test, is an intelligent bio-sensing system, comprised of a plasmonic Enzyme-Linked Immunosorbent Assay based colourimetric test in combination with an artificial intelligence-enabled image-based system. The presented system can separate the region of interest with 99.62% accuracy using clustering-based hybrid image processing algorithms, whereas the classification accuracy of antibody detection using a supervised machine learning technique is 100% based on the experiments conducted for the case study.

AB - This paper performs an investigation into the development of an intelligent image-based automatic in vitro diagnostic system for infectious diseases using personal devices. The proposed framework of the image-based diagnostic system is demonstrated using the case study of Tuberculosis (TB)-specific antibody detection. The developed system, denoted as the iTB-test, is an intelligent bio-sensing system, comprised of a plasmonic Enzyme-Linked Immunosorbent Assay based colourimetric test in combination with an artificial intelligence-enabled image-based system. The presented system can separate the region of interest with 99.62% accuracy using clustering-based hybrid image processing algorithms, whereas the classification accuracy of antibody detection using a supervised machine learning technique is 100% based on the experiments conducted for the case study.

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Tania MH, Kaiser MS, Shabut AM, Abu-Hassan K, Mahmud M, Hossain MA. iTB-test: An Intelligent Image-enabled Diagnostic System for In Vitro Screening of Infectious Diseases. In 14th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 1-6. (International Conference on Software, Knowledge Information, Industrial Management and Applications, SKIMA). doi: 10.1109/SKIMA57145.2022.10029556

iTB-test: An Intelligent Image-enabled Diagnostic System for In Vitro Screening of Infectious Diseases

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

Fingerprint

Cite this