Advancements in the future of automating micromanipulation techniques in the IVF laboratory using deep convolutional neural networks.

Journal: Journal of assisted reproduction and genetics
Published Date: Dec 31, 2022

Abstract

PURPOSE: To determine if deep learning artificial intelligence algorithms can be used to accurately identify key morphologic landmarks on oocytes and cleavage stage embryo images for micromanipulation procedures such as intracytoplasmic sperm injection (ICSI) or assisted hatching (AH).

Authors

  • Victoria S Jiang
    Division of Reproductive Endocrinology and Infertility, Obstetrics and Gynecology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Suite 10A, Boston, MA, 02114, USA. vjiang2@mgh.harvard.edu.
  • Deeksha Kartik
    Division of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02139, United States.
  • Prudhvi Thirumalaraju
    Division of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. hshafiee@bwh.harvard.edu.
  • Hemanth Kandula
    Division of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. hshafiee@bwh.harvard.edu.
  • Manoj Kumar Kanakasabapathy
    Division of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. hshafiee@bwh.harvard.edu.
  • Irene Souter
    Division of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynaecology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Irene Dimitriadis
    Division of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynaecology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Charles L Bormann
    Department of Obstetrics and Gynecology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Hadi Shafiee
    Division of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. hshafiee@bwh.harvard.edu and Department of Medicine, Harvard Medical School, Boston, MA, USA.

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