  Positioning patients for scanning and interventional procedures is a critical
task that requires high precision and accuracy. The conventional workflow
involves manually adjusting the patient support to align the center of the
target body part with the laser projector or other guiding devices. This
process is not only time-consuming but also prone to inaccuracies. In this
work, we propose an automated patient positioning system that utilizes a camera
to detect specific hand gestures from technicians, allowing users to indicate
the target patient region to the system and initiate automated positioning. Our
approach relies on a novel multi-stage pipeline to recognize and interpret the
technicians' gestures, translating them into precise motions of medical
devices. We evaluate our proposed pipeline during actual MRI scanning
procedures, using RGB-Depth cameras to capture the process. Results show that
our system achieves accurate and precise patient positioning with minimal
technician intervention. Furthermore, we validate our method on HaGRID, a
large-scale hand gesture dataset, demonstrating its effectiveness in hand
detection and gesture recognition.
