Diagnoses of Neisseria Bacteria via Neural Networks Techniques
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
Publication history:
Received on 06 November 2021; revised on 18 December 2021; accepted on 20 December 2021
Abstract:
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.
Keywords:
Diseases; Neisseria bacteria cell; Cerebrospinal fluid; Classification; Diagnosis
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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