Future of Information and Communication Conference (FICC) 2025
28-29 April 2025
Publication Links
IJACSA
Special Issues
Future of Information and Communication Conference (FICC)
Computing Conference
Intelligent Systems Conference (IntelliSys)
Future Technologies Conference (FTC)
International Journal of Advanced Computer Science and Applications(IJACSA), Volume 15 Issue 5, 2024.
Abstract: Parasites are disease-causing agents both in Peru and worldwide. In many contexts, diagnosis is done manually by observing microscopic images, where it's necessary to identify parasite eggs. However, this process is notably slow, and sometimes image clarity may be insufficient, making rapid and accurate identification challenging. This can be due to various factors, such as image quality or the presence of noise. This paper focused on a Convolutional Neural Network (CNN) model. Through this approach, the training, testing, and validation stages of our CNN model to detect and identify Ascaris lumbricoides parasite eggs. The results show that the proposed CNN model, combined with image preprocessing, yielded highly favorable results in parasite egg identification. Additionally, very satisfactory values were achieved in model testing and validation, indicating its effectiveness and precision in diagnosing parasite presence. This research represents a significant advancement in the field of parasitological diagnosis, offering an efficient and accurate solution for parasite detection through microscopic image analysis. It is hoped that these results contribute to improving diagnosis and treatment methods for parasitic diseases.
Giovanni Gelber Martinez Pastor, Cesar Roberto Ancco Ruelas, Eveling Castro-Gutierrez and Victor Luis Vásquez Huerta, “Automatic Detection of Ascaris Lumbricoides in Microscopic Images using Convolutional Neural Networks (CNN)” International Journal of Advanced Computer Science and Applications(IJACSA), 15(5), 2024. http://dx.doi.org/10.14569/IJACSA.2024.0150590
@article{Pastor2024,
title = {Automatic Detection of Ascaris Lumbricoides in Microscopic Images using Convolutional Neural Networks (CNN)},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0150590},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0150590},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {5},
author = {Giovanni Gelber Martinez Pastor and Cesar Roberto Ancco Ruelas and Eveling Castro-Gutierrez and Victor Luis Vásquez Huerta}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.