Development of Gestational Age-Based Fetal Brain and Intracranial Volume Reference Norms Using Deep Learning.

Journal: AJNR. American journal of neuroradiology
Published Date: Dec 22, 2022

Abstract

BACKGROUND AND PURPOSE: Fetal brain MR imaging interpretations are subjective and require subspecialty expertise. We aimed to develop a deep learning algorithm for automatically measuring intracranial and brain volumes of fetal brain MRIs across gestational ages.

Authors

  • C B N Tran
    From the Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, California.
  • P Nedelec
    From the Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, California.
  • D A Weiss
    From the Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, California.
  • J D Rudie
    From the Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.
  • L Kini
    From the Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, California.
  • L P Sugrue
    From the Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, California.
  • O A Glenn
    From the Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, California.
  • C P Hess
    Department of Radiology and Biomedical Imaging (C.P.H.), University of California, San Francisco, San Francisco, California.
  • A M Rauschecker
    From the Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania. andreas.rauschecker@gmail.com.

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