Computer-Assisted Intramedullary Nailing Using Real-Time Bone Detection in 2D Ultrasound Images

In this paper, we propose a new method for bone surface detection in 2D ultrasound (US) images, and its application in a Computer Assisted Orthopaedic Surgery system to assist the surgeon during the locking of the intramedullary nail in tibia fractures reduction. It is a three main steps method: first, a vertical gradient is applied to extract potential segments of bone from 2D US images, and then, a new method based on shortest path is used to eliminate all segments that do not belong to the final contour. Finally, the contour is closed using least square polynomial approximation. The first validation of the method has been done using US images of anterior femoral condyles from 9 healthy volunteers. To calculate the accuracy of the method, we compared our results to a manual segmentation performed by an expert. The Misclassification Error (ME) is between 0.10% and 0.26% and the average computation time was 0.10 second per image.

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