Majority of the pre-scan errors in MRI radiological workflows are due to a) in-appropriate patient positioning, b) incorrect protocol selection for the anatomy to be scanned, c) operator/technologist negligence. In this work, we propose and develop an AI (Artificial Intelligence) based computer vision solution to correct patient positioning errors and reduce the scan time. Our approach relies on identification of RF coil and anatomy of the patient when occluded with coils using a 3D depth camera. Camera based solution has shown significant improvements in some of the critical MRI based workflow such as auto-landmarking, coil/protocol selection and scan range overlay.
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