Motion detection for patient safety in CT scanner - Zaynab Boujelb; Ahmed Idrissi; Achraf Benba; El Mahjoub Chakir (Results in Engineering)
Developing dependable monitoring systems is essential for ensuring the security and safety of patients. In the last decades, recent progress in IoT and embedded devices has enabled the conception of cost-effective real-time systems. Patient motion, which occurs owing to breath, cough, sneezing, or other activities, during the Computed Tomography (CT) scan is a serious authoritative complication that produces image degradation, elevation of radiation exposure, and repetition of scans. The study developed an automatic motion detection system by using sensors to develop such systems to ensure both patient safety and diagnostic accuracy. A prototype was created to establish real-time monitoring of patient mobility during computed tomography scans using Raspberry Pi. It uses advanced image processing techniques to detect motion and stop the emission of X-rays from the machine as soon as the motion of the patient is detected. The prototype has been assessed under several conditions, and values such as motion detection accuracy and response time were evaluated. The deployment of the prototype of the motion detection reduced kinetic blur, which is one of the main causes of repeated examinations. The system has been 90 % accurate while detecting movements of patients significantly improving the quality of images produced from diagnostic facilities and less unnecessary exposure to radiation. The incorporation of real-time motion detection in CT scanners achieves greater image quality and reduction of patient radiation risks. The authors argue that such technologies should be adopted for clinical practice: in essence, they lead to superior patient care at reduced costs.