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Multiple-Object 2-D–3-D Registration for Noninvasive Pose Identification of Fracture Fragments

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3 Author(s)
Ren Hui Gong ; School of Computing, Queen’s University, Kingston, Canada ; James Stewart ; Purang Abolmaesumi

This paper presents a multiple-object 2-D-3-D registration technique for noninvasively identifying the poses of fracture fragments in the space of a preoperative treatment plan. The plan is made by manipulating and aligning computer models of individual fracture fragments that are segmented from a diagnostic computed tomography. The registration technique iteratively updates the treatment plan and matches its digitally reconstructed radiographs to a small number of intraoperative fluoroscopic images. The proposed approach combines an image similarity metric that integrates edge information with mutual information, and a global-local optimization scheme, to deal with challenges associated with the registration of multiple small fragments and limited imaging orientations in the operating room. The method is easy to use as minimum user interaction is required. Experiments on simulated fractures and two distal radius fracture phantoms demonstrate clinically acceptable target registration errors with capture range as large as 10 mm.

Published in:

IEEE Transactions on Biomedical Engineering  (Volume:58 ,  Issue: 6 )