Evaluation of Time-of-Flight Camera Positioning for AI-based Patient Pose Assessment in Radiography

Manuel Laufer, Julius M. Haas, Dominik Mairhöfer, Hauke Gerdes, Jörg Barkhausen, Erhardt Barth, Thomas Martinetz

Keywords: Time-of-Flight cameras, camera positioning evaluation, patient positioning, radiography, synthetic data

TL;DR: This paper evaluates different positions for Time-of-Flight cameras that can help assist medical staff in positioning patients for radiography.

Abstract: In recent years, medical technology companies have increasingly been integrating Time-of-Flight cameras into their X-ray devices to support optimal collimation and patient positioning process. However, for many hospitals, it is not financially viable to acquire a new X-ray device with such a camera for those features. In order to still have support for e.g. patient positioning, without having to buy a new X-ray device and be dependent on proprietary algorithms, it is possible to only acquire a Time-of-Flight camera, attach it to the X-ray device, and use custom algorithms. In this work, we evaluated the ideal camera position for AI-supported patient pose assessment based on depth images for such a setup and assessed the usefulness of a setup with multiple cameras. For this, we generated a total of 461,550 synthetic depth images from CT data with 50 different camera positions and synthetic radiographs in order to investigate in 1,500 experiments how accurately patients' poses can be assessed from different camera positions. We found that a camera position perpendicular to the target anatomy being X-rayed is particularly well suited, and that adding a second camera does not improve performance.

Submission Number: 31