AI-Assisted Smart Interventional Needles with Engineered Acoustic Surfaces for Robust Ultrasound Visualization

Ultrasound-guided medical procedures often suffer from limited needle visibility, particularly when the needle is viewed at steep or oblique angles. This poor visibility can obscure the needle tip, leading to diagnostic uncertainty, longer procedures, and, in some cases, the need to switch to more expensive or radiation-based imaging methods. This project explores a new generation of smart medical needles that use advanced acoustic engineering and artificial intelligence to achieve clear, consistent visibility under ultrasound imaging. The design employs structured surfaces with directional acoustic return and machine-learning algorithms that recognize and track the needle’s position in real time. Together, these innovations aim to deliver sharper, more angle-independent imaging performance and more reliable tip localization during interventions. By improving ultrasound guidance, the work supports safer, faster, and more cost-effective procedures such as biopsies and regional anesthesia. The outcomes will contribute to Qatar’s growing leadership in medical technology and intelligent healthcare systems while laying the foundation for future integration with robotic and minimally invasive platforms.

Hamad Bin Khalifa University (HBKU)