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

Marzia Hoque Tania, M. Kaiser, A. Shabut, Kamal Abu-Hassan, M. Mahmud, M. A. Hossain
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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.
iTB-test:一种用于体外筛查传染病的智能图像诊断系统
本文研究了一种基于个人设备的基于图像的传染病智能体外自动诊断系统的开发。提出的基于图像的诊断系统的框架是使用结核病(TB)特异性抗体检测的案例研究证明。开发的系统被称为itb测试,是一种智能生物传感系统,由基于等离子体酶联免疫吸附测定的比色测试与基于人工智能的图像系统相结合组成。使用基于聚类的混合图像处理算法,该系统可以以99.62%的准确率分离感兴趣的区域,而基于案例研究的实验,使用监督机器学习技术的抗体检测的分类准确率为100%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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