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Morphometric evaluation of two-pronucleus zygote images using image-processing techniques

Published online by Cambridge University Press:  17 August 2022

Niloofar Sayadi ,
Sara Monji-Azad ,
Seyed Abolghasem Mirroshandel Open the ORCID record for Seyed Abolghasem Mirroshandel [Opens in a new window]  and
Fatemeh Ghasemian
Niloofar Sayadi
Affiliation:
Department of Computer Engineering, University of Guilan, Rasht, Iran
Sara Monji-Azad
Affiliation:
Mannheim Institute for Intelligent Systems in Medicine, Heidelberg University, Heidelberg, Germany
Seyed Abolghasem Mirroshandel*
Affiliation:
Department of Computer Engineering, University of Guilan, Rasht, Iran
Fatemeh Ghasemian
Affiliation:
Department of Biology, University of Guilan, Rasht, Iran
*
Author for correspondence: S.A. Mirroshandel. Department of Computer Engineering, University of Guilan, Rasht, P.O. Box: 1841, Iran. Tel.: +98 13 33690274. Fax: +98 13 33690271. E-mail: [email protected]
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Summary

Identifying embryos with a high potential for implementation remains a challenge in in vitro fertilization (IVF) cycles. Despite progress in IVF treatment, only a minority of generated embryos has the ability to implant. Another drawback of this practice is the high frequency of multiple pregnancies. This problem leads to economic and health problems. Therefore, the transfer of a single embryo with high implantation potential is the ideal strategy. Morphometric evaluation of two-pronucleus zygote images is a helpful technique when aiming to transfer a single embryo with a high implantation potential. In this study, an automated zygote morphometric evaluation algorithm, called the zygote morphology evaluation (ZME) algorithm, was created to analyze the zygote and provide morphological measurements. The first and most crucial step of the ZME algorithm is the noise reduction step, which was first applied to zygote images. After that, the proposed algorithm detects different parts of the zygote that are indicators of embryo viability and normality, that is the oolemma, perivitelline space, zona pellucida, and nucleolar precursor bodies (NPBs). In addition, a novel dataset was prepared for this task. This dataset consisted of 703 human zygote images, and called the human zygote morphometric evaluation dataset (HZME-DS). Our experimental results in the HZME-DS showed that the ZME algorithm was able to achieve 79.58% average accuracy in identifying the oolemma region, 79.40% average accuracy in determining the perivitelline space, and 79.72% accuracy in identifying the zona pellucida. To calculate the accuracy of identifying NPBs, the proposed algorithm uses Recall and Precision measures, and their harmonic average (F1 measure) reached values of 81.14% and 79.53%, respectively. These encouraging results for our proposed method, which is an automatic and very fast method, showed that the ZME algorithm could help embryologists to evaluate the best zygotes in real time and the best embryos subsequently.

Keywords

In vitro fertilizationImage processingMorphometric evaluationPronucleus morphologyZygote
Type
Research Article
Information
Zygote , Volume 30 , Issue 6 , December 2022 , pp. 819 - 829
Copyright
© The Author(s), 2022. Published by Cambridge University Press

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