Peer-Reviewed Publication
Ultrasound Med Biol2025;51(9):1555-1563.September 1, 2025Journal Article
Deep Learning-Based Automated Detection of the Middle Cerebral Artery in Transcranial Doppler Ultrasound Examinations.
HyeonWoo Lee1, William Shi2, Rashid Al Mukaddim2, Elizabeth Brunelle2, Abhinav Palisetti2, Syed M Imaduddin3, Phavalan Rajendram4, Diego Incontri5, Vasileios-Arsenios Lioutas5, Thomas Heldt6, Balasundar I Raju2
1Philips Ultrasound, Philips North America, Cambridge, MA, USA. Electronic address: hyeonwoo.lee@philips.com.
2Philips Ultrasound, Philips North America, Cambridge, MA, USA.
3Department 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.
4Department of Medicine, University of Toronto, Toronto, Canada.
5Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA.
6Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA.
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.
METHODS: Two state-of-the-art ob…
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