This sponsored session will present a QUT-led research project exploring AI-assisted abdominal ultrasound, with a focus on human–AI partnership. The presentation will outline how the project was developed, including the contribution of a VRES student who helped build a custom hand-tracking system to capture sonographer movement and console interaction during scanning. It will also briefly introduce the broader work of the QUT ultrasound lab and how this study sits within a wider program of research focused on workflow, technology, and innovation in sonographic practice.

The session will then step through the study design, the metrics used, and some early findings. These include workflow and movement measures such as scan time, keystrokes, hand travel, and jerk, alongside cognitive workload measured with NASA-TLX. The discussion will consider what happens when AI is introduced into a real-time, operator-dependent task such as abdominal ultrasound. The presentation examines how AI may reshape the sonographer’s work, shifting effort away from some manual tasks and toward supervision, verification, and quality assurance.