The C-Arm x-ray system (C-Arm) is a useful medical device commonly used in surgeries that require the use of x-ray images during operations. In some operations, surgeons rely heavily on the mobile C-Arm to effectively execute the surgery. In some cases, the success of the operation is directly correlated with the C-Arm and its ability to be repositioned to any desired position relative to the patient. In this paper, an integrated approach is provided for the automatic and accurate repositioning of a mobile C-Arm. The development of a C-Arm prototype is explained through the use of computer-aided design and manufacturing. To automatically reposition the C-Arm, a two-step integrated approach is introduced that uses motion capture systems and artificial intelligence-based repositioning. In the first step, the C-Arm is repositioned using Vicon motion capture along with a virtual platform and graphic user interface. In the second step, the accuracy of the repositioning of the C-Arm is further improved by incorporating a deep learning convolutional neural network with image processing and point feature matching. Key results indicate successful integration of the proposed method with the C-Arm prototype for the purpose of automatic and accurate repositioning.

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