Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-586b7cd67f-t7czq Total loading time: 0 Render date: 2024-11-22T18:00:58.376Z Has data issue: false hasContentIssue false

Chapter 13 - Automation Techniques and Systems for ICSI

Published online by Cambridge University Press:  02 December 2021

By
Changsheng Dai ,
Zhuoran Zhang ,
Guanqiao Shan  and
Yu Sun
Edited by
Gianpiero D. Palermo  and
Zsolt Peter Nagy
Gianpiero D. Palermo
Affiliation:
Cornell Institute of Reproductive Medicine, New York
Zsolt Peter Nagy
Affiliation:
Reproductive Biology Associates, Atlanta, GA
Get access

Summary

This chapter introduces automation techniques for intracytoplasmic sperm injection (ICSI). These techniques are used for sperm motility and morphology quantification, sperm immobilization, sperm aspiration, oocyte orientation control, and sperm injection. Emerging techniques are also described such as computer assisted sperm analysis, laser immobilization, deep learning based polar body detection, and piezo drilling for reducing cell deformation in penetration. Finally, outlooks for future development of automation techniques in ICSI are provided.

Keywords

AutomationRoboticsComputer visionICSI
Type
Chapter
Information
Manual of Intracytoplasmic Sperm Injection in Human Assisted Reproduction
With Other Advanced Micromanipulation Techniques to Edit the Genetic and Cytoplasmic Content of the Oocyte
 , pp. 129 - 140
Publisher: Cambridge University Press
Print publication year: 2021

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Amann, RP, Waberski, D. Computer-assisted sperm analysis (CASA): capabilities and potential developments. Theriogenology 2014; 81: 5–17.Google Scholar
Dai, C, Zhang, Z, Huang, J, et al. Automated non-invasive measurement of single sperm’s motility and morphology. IEEE Transactions on Medical Imaging 2018; 37: 2257–2265.CrossRefGoogle ScholarPubMed
Bartoov, B, Berkovitz, A, Eltes, F, et al. Real‐time fine morphology of motile human sperm cells is associated with IVF‐ICSI outcome. Journal of Andrology 2002; 23: 1–8.CrossRefGoogle ScholarPubMed
Bijar, A, Benavent, AP, Mikaeili, M. Fully automatic identification and discrimination of sperm’s parts in microscopic images of stained human semen smear. Journal of Biomedical Science and Engineering 2012; 5: 384–395.Google Scholar
Ghasemian, F, Mirroshandel, SA, Monji-Azad, S, Azarnia, M, Zahiri, Z. An efficient method for automatic morphological abnormality detection from human sperm images. Computer Methods and Programs in Biomedicine 2015; 122: 409–420.Google Scholar
Leung, C, Lu, Z, Esfandiari, N, Casper, RF, Sun, Y. Automated sperm immobilization for intracytoplasmic sperm injection. IEEE Transactions on Biomedical Engineering 2010; 58: 935–942.CrossRefGoogle ScholarPubMed
Zhang, Z, Dai, C, Huang, J, et al. Robotic immobilization of motile sperm for clinical intracytoplasmic sperm injection. IEEE Transactions on Biomedical Engineering 2018; 66: 444–452.Google Scholar
Zhang, Z, Dai, C, Wang, X, et al. Automated laser ablation of motile sperm for immobilization. IEEE Robotics and Automation Letters 2019; 4: 323–329.CrossRefGoogle Scholar
Shan, G, Zhang, Z, Dai, C, et al. Model-based robotic cell aspiration: tackling nonlinear dynamics and varying cell sizes. IEEE Robotics and Automation Letters 2019; 5: 173–178.CrossRefGoogle Scholar
Zhang, XP, Leung, C, Lu, Z, Esfandiari, N, Casper RF and Sun Y. Controlled aspiration and positioning of biological cells in a micropipette. IEEE Transactions on Biomedical Engineering 2012; 59: 1032–1040.CrossRefGoogle Scholar
Zhang, Z, Liu, J, Wang, X, et al. Robotic pick-and-place of multiple embryos for vitrification. IEEE Robotics and Automation Letters 2016; 2: 570–576.Google Scholar
Dai, C, Zhang, Z, Lu, Y, et al. Robotic manipulation of deformable cells for orientation control. IEEE Transactions on Robotics 2020; 36: 271–283Google Scholar
Leung, C, Lu, Z, Zhang, XP, Sun, Y. Three-dimensional rotation of mouse embryos. IEEE Transactions on Biomedical Engineering 2012; 59: 1049–1056.CrossRefGoogle ScholarPubMed
Hayakawa, T, Sakuma, S, Arai, F. On-chip 3D rotation of oocyte based on a vibration-induced local whirling flow. Microsystems and Nanoengineering 2015; 1:15001.Google Scholar
Hagiwara, M, Kawahara, T, Arai, F. Local streamline generation by mechanical oscillation in a microfluidic chip for noncontact cell manipulations. Applied Physics Letters 2012; 101: 074102.Google Scholar
Liu, X, Lu, Z, Sun, Y. Orientation control of biological cells under inverted microscopy. IEEE/ASME Transactions on Mechatronics 2010; 16: 918–924.Google Scholar
Feng, L, Turan, B, Ningga, U, Arai, F. Three dimensional rotation of bovine oocyte by using magnetically driven on-chip robot. IEEE/RSJ International Conference on Intelligent Robots and Systems 2014; 4668–4673.Google Scholar
Zhao, Q, Sun, M, Cui, M, Yu, J, Qin, Y, Zhao, X. Robotic cell rotation based on the minimum rotation force. IEEE Transactions on Automation Science and Engineering 2014; 12: 1504–1515.CrossRefGoogle Scholar
Lu, Z, Zhang, X, Leung, C, Esfandiari, N, Casper, RF, Sun, Y. Robotic ICSI (intracytoplasmic sperm injection). IEEE Transactions on Biomedical Engineering 2011; 58: 2102–2108.Google Scholar
Yanagida, K, Katayose, H, Yazawa, H, Kimura, Y, Konnai, K, Sato, A. The usefulness of a piezo-micromanipulator in intracytoplasmic sperm injection in humans. Human Reproduction 1999; 14: 448–453.Google Scholar
Hiraoka, K, Kitamura, S. Clinical efficiency of Piezo-ICSI using micropipettes with a wall thickness of 0.625 μm. Journal of Assisted Reproduction and Genetics 2015; 32: 1827–1833.CrossRefGoogle Scholar
Johnson, W, Dai, C, Liu, J, et al. A flexure-guided piezo drill for penetrating the zona pellucida of mammalian oocytes. IEEE Transactions on Biomedical Engineering 2017; 65: 678–686.CrossRefGoogle ScholarPubMed
Dai, C, Xin, L, Zhang, Z, et al. Design and control of a piezo drill for robotic piezo-driven cell penetration. IEEE Robotics and Automation Letters 2020; 5: 339–345.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×