Multistage optimization using a modified Gaussian Mixture Model in sperm motility tracking

Alameri, Mohammed and Hasikin, Khairunnisa and Kadri, Nahrizul Adib and Nasir, Nashrul Fazli Mohd and Mohandas, Prabu and Anni, Jerline Sheeba and Azizan, Muhammad Mokhzaini (2021) Multistage optimization using a modified Gaussian Mixture Model in sperm motility tracking. Computational and Mathematical Methods in Medicine, 2021. ISSN 1748-670X, DOI

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Infertility is a condition whereby pregnancy does not occur despite having unprotected sexual intercourse for at least one year. The main reason could originate from either the male or the female, and sometimes, both contribute to the fertility disorder. For the male, sperm disorder was found to be the most common reason for infertility. In this paper, we proposed male infertility analysis based on automated sperm motility tracking. The proposed method worked in multistages, where the first stage focused on the sperm detection process using an improved Gaussian Mixture Model. A new optimization protocol was proposed to accurately detect the motile sperms prior to the sperm tracking process. Since the optimization protocol was imposed in the proposed system, the sperm tracking and velocity estimation processes are improved. The proposed method attained the highest average accuracy, sensitivity, and specificity of 92.3%, 96.3%, and 72.4%, respectively, when tested on 10 different samples. Our proposed method depicted better sperm detection quality when qualitatively observed as compared to other state-of-the-art techniques.

Item Type: Article
Funders: Universiti Malaya [Grant No: RF010-2018A], International Funding of Motorola Solution Foundation [Grant No: IF014-2019]
Uncontrolled Keywords: Infertility; Fertility disorder; Sperm disorder; Automated sperm motility tracking
Subjects: Q Science > QA Mathematics
Q Science > QH Natural history > QH301 Biology
Divisions: Faculty of Engineering
Depositing User: Ms Zaharah Ramly
Date Deposited: 21 Aug 2022 03:03
Last Modified: 21 Aug 2022 03:03

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