[HTML][HTML] A comprehensive review of image analysis methods for microorganism counting: from classical image processing to deep learning approaches

J Zhang, C Li, MM Rahaman, Y Yao, P Ma… - Artificial Intelligence …, 2022 - Springer
Microorganisms such as bacteria and fungi play essential roles in many application fields,
like biotechnique, medical technique and industrial domain. Microorganism counting …

[HTML][HTML] 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 …

Automatic detection of tuberculosis bacilli from microscopic sputum smear images using deep learning methods

RO Panicker, KS Kalmady, J Rajan, MK Sabu - … and Biomedical Engineering, 2018 - Elsevier
An automatic method for the detection of Tuberculosis (TB) bacilli from microscopic sputum
smear images is presented in this paper. According to WHO, TB is the ninth leading cause of …

[HTML][HTML] Tuberculosis bacteria detection and counting in fluorescence microscopy images using a multi-stage deep learning pipeline

M Zachariou, O Arandjelović, W Sabiiti, B Mtafya… - Information, 2022 - mdpi.com
The manual observation of sputum smears by fluorescence microscopy for the diagnosis
and treatment monitoring of patients with tuberculosis (TB) is a laborious and subjective …

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 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 …

Ziehl–Neelsen sputum smear microscopy image database: a resource to facilitate automated bacilli detection for tuberculosis diagnosis

MI Shah, S Mishra, VK Yadav… - Journal of Medical …, 2017 - spiedigitallibrary.org
Ziehl–Neelsen stained microscopy is a crucial bacteriological test for tuberculosis detection,
but its sensitivity is poor. According to the World Health Organization (WHO) …

Automatic classification of light field smear microscopy patches using Convolutional Neural Networks for identifying Mycobacterium Tuberculosis

YP López, CFF Costa Filho… - 2017 CHILEAN …, 2017 - ieeexplore.ieee.org
Tuberculosis (TB) has been included among the top ten leading causes of death worldwide.
Since 2008, several investigations have been developed by scientific community for …

[HTML][HTML] Automatic identification of tuberculosis mycobacterium

CFF Costa Filho, PC Levy, CM Xavier… - Research on …, 2015 - SciELO Brasil
Introduction According to the Global TB control report of 2013,“Tuberculosis (TB) remains a
major global health problem. In 2012, an estimated 8.6 million people developed TB and 1.3 …

[HTML][HTML] GFNN: Gaussian-Fuzzy-Neural network for diagnosis of tuberculosis using sputum smear microscopic images

KS Mithra, WRS Emmanuel - Journal of King Saud University-Computer …, 2021 - Elsevier
Tuberculosis (TB) is one of the infectious diseases spread by the infectious agent,
Mycobacterium tuberculosis. Sputum smear microscopy is a primary tool used for the …