@article{b949bc65be794ba098004029780083c3,
title = "RGB-D camera-based clinical workflow optimization for rotational angiography",
abstract = "High-speed Rotational Angiography scans are prone to potential collisions between the C-arm X-ray system and the patient. A key factor during rotational angiography clinical workflow is thus the initial patient positioning to ensure a collision-free scan. The current practice for this involves multiple manual iterations of a low speed safety-run prior to the actual scan. Several iterations are often required before a scan is collision-free leading to a suboptimal clinical workflow. This work proposes a RGB-D camera based safety system which automates the patient positioning process. The camera determines collisions between the C-arm and patient and a re-positioning algorithm determines the movement of the patient table required to ensure a collisoin-free scan. A unique feature of the solution is the ability to warn clinical staff when a collision-free scan is not possible. The efficacy of the proposed system is illustrated experimentally for two major RA scan types.",
keywords = "Collision prediction, RGB-D camera, clinical workflow, collision avoidance, patient safety",
author = "K. İncetan and Rishi Mohan and Henry Stoutjesdijk and Nelson Fernandes and {de Jager}, Bram",
year = "2020",
month = aug,
day = "1",
doi = "10.1109/JSEN.2020.2985502",
language = "English",
volume = "20",
pages = "8867 -- 8874",
journal = "IEEE Sensors Journal",
issn = "1530-437X",
publisher = "Institute of Electrical and Electronics Engineers",
number = "15",
}