Open-source translational framework for AI-powered ultrasound-guided kidney interventions

This project aims to democratize access to advanced surgical navigation by developing an open-source, AI-enabled training and guidance system for ultrasound-guided kidney procedures. Built entirely within the free 3D Slicer platform, the system combines real-time tracking and deep-learning segmentation to help trainees and clinicians visualize kidney structures and plan safer, more precise punctures. The collaboration between Queen’s University in Canada and Cheikh Anta Diop University in Senegal will produce a scalable tool that supports equitable surgical training and safer care worldwide, reinforcing both institutions’ shared commitment to accessible medical innovation.

Faculty Supervisor:

Gabor Fichtinger

Student:

Partner:

Université Cheikh Anta Diop de Dakar

Discipline:

Computer science

Sector:

Artificial Intelligence; Health and Related Sciences & Technology; Social Innovation

University:

Queen's University

Program: