Deep Learning-Based Automated Detection of the Middle Cerebral Artery in Transcranial Doppler Ultrasound Examinations.

Journal: Ultrasound in medicine & biology
Published Date: Jun 29, 2025

Abstract

OBJECTIVE: Transcranial Doppler (TCD) ultrasound has significant clinical value for assessing cerebral hemodynamics, but its reliance on operator expertise limits broader clinical adoption. In this work, we present a lightweight real-time deep learning-based approach capable of automatically identifying the middle cerebral artery (MCA) in TCD Color Doppler images.

Authors

  • HyeonWoo Lee
    Philips Ultrasound, Philips North America, Cambridge, MA, USA. Electronic address: hyeonwoo.lee@philips.com.
  • William Shi
    Shiley Eye Institute, Institute for Engineering in Medicine, Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA 92093, USA.
  • Rashid Al Mukaddim
  • Elizabeth Brunelle
    Philips Ultrasound, Philips North America, Cambridge, MA, USA.
  • Abhinav Palisetti
    Philips Ultrasound, Philips North America, Cambridge, MA, USA.
  • Syed M Imaduddin
    Department of Biomedical Engineering and Biotechnology, Khalifa University of Science and Technology, Abu Dhabi, UAE; Healthcare Engineering Innovation Group, Khalifa University of Science and Technology, Abu Dhabi, UAE; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Phavalan Rajendram
    Department of Medicine, University of Toronto, Toronto, Canada.
  • Diego Incontri
    Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA.
  • Vasileios-Arsenios Lioutas
    Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA.
  • Thomas Heldt
  • Balasundar I Raju

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