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Diagnoses of Neisseria Bacteria via Neural Networks Techniques

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  • Diagnoses of Neisseria Bacteria via Neural Networks Techniques

Kalthom Ibrahim 1, *, Mohammed Abdallah Almaleeh 2, Moaawia Mohamed Ahmed 2 and Dalia Mahmoud Adam 1

1 Faculty of Engineering, Department of Electrical Control, El neelain University, Khartoum, Sudan.
2 Faculty of Computer and Information Technology, Department of Computer Engineering, Tabuk University, Tabuk, KSA.

Research Article
 

World Journal of Advanced Research and Reviews, 2021, 12(03), 587–593
Article DOI: 10.30574/wjarr.2021.12.3.0673
DOI url: https://doi.org/10.30574/wjarr.2021.12.3.0673

Received on 06 November 2021; revised on 18 December 2021; accepted on 20 December 2021

This paper presented simple approach that automatically detects Neisseria Bacteria cell in the cerebrospinal fluid smear images. The proposed methodology mainly consists of cerebrospinal fluid smear images acquisition, transformation form red, green, blue smear images in to other color spaces. This step followed by subbing images and segmenting the images to extracting the images features then validation and classifying the Bacteria images based in features extracted using neural networks. The proposed diagnosis for Neisseria Bacteria through neural network techniques has performed high-precision performance in some suggested groups.

Diseases; Neisseria bacteria cell; Cerebrospinal fluid; Classification; Diagnosis

https://wjarr.co.in/sites/default/files/fulltext_pdf/WJARR-2021-0673.pdf

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Kalthom Ibrahim, Mohammed Abdallah Almaleeh, Moaawia Mohamed Ahme and Dalia Mahmoud Adam. Diagnoses of Neisseria Bacteria via Neural Networks Techniques. World Journal of Advanced Research and Reviews, 2021, 12(03), 587–593. Article DOI: https://doi.org/10.30574/wjarr.2021.12.3.0673

Copyright © 2021 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0

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