AI-Assisted Smart Interventional Needles with Engineered Acoustic Surfaces for Robust Ultrasound Visualization
Research collaboration led by Hamad Bin Khalifa University (HBKU), Qatar, with Sidra Medicine and the University of Bonn (2025–2027) — smart needles and AI that keep the needle tip visible in ultrasound-guided procedures.
Abstract
Lead: Hamad Bin Khalifa University (HBKU), Qatar · Partners: Sidra Medicine (Radiology), University of Bonn (associated partner) · Funding: HBKU research grant (HBKU-INT-VPR-TG-03-14), granted to the lead institution
In ultrasound-guided procedures such as biopsies and regional anaesthesia, the needle is often hard to see, especially at steep or oblique insertion angles, so the clinician can lose track of its tip. This project develops smart interventional needles that combine acoustic engineering with artificial intelligence: needle surfaces with engineered, directional acoustic reflection make the needle stand out in the ultrasound image, and machine-learning methods recognise and track the needle and its tip in real time. The aim is angle-independent needle visualisation and reliable tip localisation, and a basis for later integration into robotic and minimally invasive platforms.
Our role
The Albarqouni Lab is an associated partner: Prof. Albarqouni serves as co-PI, and the lab receives no share of the grant. We contribute expertise in deep learning for ultrasound and interventional imaging, in particular for needle and tip detection and tracking.
