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 …

LCU-Net: A novel low-cost U-Net for environmental microorganism image segmentation

J Zhang, C Li, S Kosov, M Grzegorzek, K Shirahama… - Pattern Recognition, 2021 - Elsevier
In this paper, we propose a novel Low-cost U-Net (LCU-Net) for the Environmental
Microorganism (EM) image segmentation task to assist microbiologists in detecting and …

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 …

Identification of tuberculosis bacteria based on shape and color

MG Forero, F Sroubek, G Cristóbal - Real-time imaging, 2004 - Elsevier
Tuberculosis and other mycobacteriosis are serious illnesses which control is based on
early diagnosis. A technique commonly used consists of analyzing sputum images for …

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 …

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 …

Classification of Mycobacterium tuberculosis in Images of ZN-Stained Sputum Smears

R Khutlang, S Krishnan, R Dendere… - IEEE transactions on …, 2009 - ieeexplore.ieee.org
Screening for tuberculosis (TB) in low-and middle-income countries is centered on the
microscope. We present methods for the automated identification of Mycobacterium …

Image processing techniques for identifying Mycobacterium tuberculosis in Ziehl-Neelsen stains

P Sadaphal, J Rao, GW Comstock… - … International Journal of …, 2008 - ingentaconnect.com
Worldwide, laboratory technicians tediously read sputum smears for tuberculosis (TB)
diagnosis. We demonstrate proof of principle of an innovative computational algorithm that …

[PDF][PDF] Color thresholding method for image segmentation of natural images

N Kulkarni - International Journal of Image, Graphics and Signal …, 2012 - academia.edu
Most of the thresholding procedures involved setting of boundaries based on grey values or
intensities of image pixels. In this paper, the thresholding is to be done based on color …