Repository of Research and Investigative Information

Repository of Research and Investigative Information

Ilam University of Medical Sciences

A machine learning-based system for detecting leishmaniasis in microscopic images

Wed Nov 30 17:52:46 2022

(2022) A machine learning-based system for detecting leishmaniasis in microscopic images. Bmc Infectious Diseases. p. 6.

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Abstract

Background Leishmaniasis, a disease caused by a protozoan, causes numerous deaths in humans each year. After malaria, leishmaniasis is known to be the deadliest parasitic disease globally. Direct visual detection of leishmania parasite through microscopy is the frequent method for diagnosis of this disease. However, this method is time-consuming and subject to errors. This study was aimed to develop an artificial intelligence-based algorithm for automatic diagnosis of leishmaniasis. Methods We used the Viola-Jones algorithm to develop a leishmania parasite detection system. The algorithm includes three procedures: feature extraction, integral image creation, and classification. Haar-like features are used as features. An integral image was used to represent an abstract of the image that significantly speeds up the algorithm. The adaBoost technique was used to select the discriminate features and to train the classifier. Results A 65 recall and 50 precision was concluded in the detection of macrophages infected with the leishmania parasite. Also, these numbers were 52 and 71, respectively, related to amastigotes outside of macrophages. Conclusion The developed system is accurate, fast, easy to use, and cost-effective. Therefore, artificial intelligence might be used as an alternative for the current leishmanial diagnosis methods.

Item Type: Article
Creators:
CreatorsEmail
Zare, M.UNSPECIFIED
Akbarialiabad, H.UNSPECIFIED
Parsaei, H.UNSPECIFIED
Asgari, Q.UNSPECIFIED
Alinejad, A.UNSPECIFIED
Bahreini, M. S.UNSPECIFIED
Hosseini, S. H.UNSPECIFIED
Ghofrani-Jahromi, M.UNSPECIFIED
Shahriarirad, R.UNSPECIFIED
Amirmoezzi, Y.UNSPECIFIED
Shahriarirad, S.UNSPECIFIED
Zeighami, A.UNSPECIFIED
Abdollahifard, G.UNSPECIFIED
Keywords: Leishmania Cutaneous leishmaniasis Artificial intelligence Image processing Adaboost Viola-Jones Algorithm cutaneous leishmaniasis diagnosis infection infantum pcr Infectious Diseases
Divisions:
Page Range: p. 6
Journal or Publication Title: Bmc Infectious Diseases
Journal Index: ISI
Volume: 22
Number: 1
Identification Number: https://doi.org/10.1186/s12879-022-07029-7
Depositing User: مهندس مهدی شریفی
URI: http://eprints.medilam.ac.ir/id/eprint/3849

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