Applications of artificial neural networks in microorganism image analysis: a comprehensive review from conventional multilayer perceptron to popular convolutional …

J Zhang, C Li, Y Yin, J Zhang, M Grzegorzek - Artificial Intelligence Review, 2023 - Springer
Microorganisms are widely distributed in the human daily living environment. They play an
essential role in environmental pollution control, disease prevention and treatment, and food …

A state-of-the-art survey of object detection techniques in microorganism image analysis: from classical methods to deep learning approaches

P Ma, C Li, MM Rahaman, Y Yao, J Zhang… - Artificial Intelligence …, 2023 - Springer
Microorganisms play a vital role in human life. Therefore, microorganism detection is of great
significance to human beings. However, the traditional manual microscopic detection …

A survey for cervical cytopathology image analysis using deep learning

MM Rahaman, C Li, X Wu, Y Yao, Z Hu, T Jiang… - IEEE …, 2020 - ieeexplore.ieee.org
Cervical cancer is one of the most common and deadliest cancers among women. Despite
that, this cancer is entirely treatable if it is detected at a precancerous stage. Pap smear test …

[HTML][HTML] An intelligent mobile-enabled expert system for tuberculosis disease diagnosis in real time

AM Shabut, MH Tania, KT Lwin, BA Evans… - Expert Systems with …, 2018 - Elsevier
This paper presents an investigation into the development of an intelligent mobile-enabled
expert system to perform an automatic detection of tuberculosis (TB) disease in real-time …

Computational techniques for the automated detection of mycobacterium tuberculosis from digitized sputum smear microscopic images: A systematic review

E Kotei, R Thirunavukarasu - Progress in Biophysics and Molecular Biology, 2022 - Elsevier
Background Tuberculosis is an infectious disease that is caused by Mycobacterium
tuberculosis (MTB), which mostly affects the lungs of humans. Bright-field microscopy and …

A state-of-the-art survey for microorganism image segmentation methods and future potential

F Kulwa, C Li, X Zhao, B Cai, N Xu, S Qi, S Chen… - Ieee …, 2019 - ieeexplore.ieee.org
Microorganisms play a great role in ecosystem, wastewater treatment, monitoring of
environmental changes, and decomposition of waste materials. However, some of them are …

Artificial neural networks for prediction of tuberculosis disease

MT Khan, AC Kaushik, L Ji, SI Malik, S Ali… - Frontiers in …, 2019 - frontiersin.org
Background: The global burden of tuberculosis (TB) and antibiotic resistance is attracting the
attention of researchers to develop some novel and rapid diagnostic tools. Although, the …

A review of automatic methods based on image processing techniques for tuberculosis detection from microscopic sputum smear images

RO Panicker, B Soman, G Saini, J Rajan - Journal of medical systems, 2016 - Springer
Tuberculosis (TB) is an infectious disease caused by the bacteria Mycobacterium
tuberculosis. It primarily affects the lungs, but it can also affect other parts of the body. TB …

A review of clustering methods in microorganism image analysis

C Li, F Kulwa, J Zhang, Z Li, H Xu, X Zhao - Information technology in …, 2021 - Springer
Clustering plays a great role in microorganism image segmentation, feature extraction and
classification, in all major application areas of microorganisms (medical, environmental …

Automated identification of mycobacterium bacillus from sputum images for tuberculosis diagnosis

KS Mithra, WR Sam Emmanuel - Signal, Image and Video Processing, 2019 - Springer
Tuberculosis is a terrible, transferrable disease instigated by infection with Mycobacterium
tuberculosis bacillus. A common diagnosis of this infection is the microscopic examination of …