DocumentCode :
1424510
Title :
Multiple-Object 2-D–3-D Registration for Noninvasive Pose Identification of Fracture Fragments
Author :
Gong, Ren Hui ; Stewart, James ; Abolmaesumi, Purang
Author_Institution :
Sch. of Comput., Queen´´s Univ., Kingston, ON, Canada
Volume :
58
Issue :
6
fYear :
2011
fDate :
6/1/2011 12:00:00 AM
Firstpage :
1592
Lastpage :
1601
Abstract :
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.
Keywords :
biomechanics; computerised tomography; fracture; image registration; image segmentation; medical image processing; optimisation; patient treatment; diagnostic computed tomography; distal radius fracture phantoms; fracture fragments; global-local optimization scheme; image segmentation; intraoperative fluoroscopic images; multiple-object 2D-3D registration; noninvasive pose identification; preoperative treatment plan; reconstructed radiographs; registration errors; treatment plan; Bones; Computed tomography; Image edge detection; Optimization; Planning; Shape; Transforms; Computer-assisted fracture reduction; covariance matrix adaptation evolution strategy (CMA-ES); digitally reconstructed radiograph (DRR); edge enhancement; fluoroscopic image; global–local alternating optimization; multiple-object 2-D–3-D registration; mutual information (MI); noninvasive pose identification; treatment plan; Algorithms; Fluoroscopy; Humans; Image Processing, Computer-Assisted; Phantoms, Imaging; Radiographic Image Interpretation, Computer-Assisted; Radius Fractures; Tomography, X-Ray Computed; Wrist;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2011.2105487
Filename :
5686916
Link To Document :
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