iTB-test: an intelligent image-enabled diagnostic system for in vitro screening of infectious diseases

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

School of Computer Science

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	2022 14th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)
Publisher	IEEE
Pages	1-6
Number of pages	6
DOIs	https://doi.org/10.1109/SKIMA57145.2022.10029556
Publication status	Published - 6 Feb 2023
Event	14th International Conference on Software, Knowledge, Information Management and Applications - CamTech University, Phnom Penh, Cambodia Duration: 2 Dec 2022 → 4 Dec 2022

Academic conference

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

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10.1109/SKIMA57145.2022.10029556Licence: Unspecified

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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.",

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

year = "2023",

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doi = "10.1109/SKIMA57145.2022.10029556",

language = "English",

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booktitle = "2022 14th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)",

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address = "United States",

note = "14th International Conference on Software, Knowledge, Information Management and Applications, SKIMA ; Conference date: 02-12-2022 Through 04-12-2022",

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Hoque Tania, M, Shamim Kaiser, M, Shabut, A, Abu-Hassan, K & Hossain, MA 2023, iTB-test: an intelligent image-enabled diagnostic system for in vitro screening of infectious diseases. in 2022 14th International Conference on Software, Knowledge, Information Management and Applications (SKIMA). IEEE, pp. 1-6, 14th International Conference on Software, Knowledge, Information Management and Applications, 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. / Hoque Tania, Marzia; Shamim Kaiser, M.; Shabut, Antesar et al.
2022 14th International Conference on Software, Knowledge, Information Management and Applications (SKIMA). IEEE, 2023. p. 1-6.

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

TY - GEN

T1 - iTB-test

T2 - 14th International Conference on Software, Knowledge, Information Management and Applications

AU - Hoque Tania, Marzia

AU - Shamim Kaiser, M.

AU - Shabut, Antesar

AU - Abu-Hassan, Kamal

AU - Hossain, M.A.

PY - 2023/2/6

Y1 - 2023/2/6

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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DO - 10.1109/SKIMA57145.2022.10029556

M3 - Conference contribution

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BT - 2022 14th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)

PB - IEEE

Y2 - 2 December 2022 through 4 December 2022

ER -

iTB-test: an intelligent image-enabled diagnostic system for in vitro screening of infectious diseases

Abstract

Academic conference

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