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A Semi-Autonomous Robotic System for Remote Trauma Assessment

Bharat Mathur, Anirudh Topiwala, Saul Schaffer, Michael Kam, Hamed Saeidi, Thorsten Fleiter, Axel Krieger

Year
2019
Citations
19

Abstract

Trauma is among the leading causes of death in the United States with up to 29% of pre-hospital trauma deaths attributed to uncontrolled hemorrhages. This paper reports a semi-autonomous robotic system capable of assessing trauma using 2D and 3D image analysis and enabling remote focused assessment with sonography for trauma (FAST) en route to the hospital for earlier trauma diagnosis and faster initialization of life saving care. The system was able to accurately calculate FAST scan positions of patient specific phantoms using the measured phantom sizes and positions of the umbilicus. The system was capable of accurately classifying and localizing wounds, so they can be avoided during the ultrasound scan. These objects were localized with an accuracy of 0.94 ± 0.179cm and FAST exam locations were estimated with an accuracy of 2.2 ± 1.88cm. A radiologist successfully completed a remote FAST scan of the phantom using the system with improved image quality over manual scans, demonstrating feasibility of the system.

Keywords

Imaging phantomInitializationComputer scienceArtificial intelligenceComputer visionImage qualityMedicineRadiologyImage (mathematics)

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