2019
DOI: 10.1016/j.jcms.2018.10.016
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Real-time augmented model guidance for mandibular proximal segment repositioning in orthognathic surgery, using electromagnetic tracking

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Cited by 19 publications
(27 citation statements)
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“…The computer-assisted navigation system often consisted of several optical localizers and provided surgeons with quantitative and intuitive screen outcomes, achieving immediate intraoperative revise of condylar malpositioning without mechanical stress. 5,28,29,35,36 However, the localizers attaching to the bone once loosened after osteotomy, the navigation system had to abort. 5 Due to the instability of sensors, the navigation system was recommended for senior surgeons in difficult cases.…”
Section: Computer-assisted Navigation Systemmentioning
confidence: 99%
“…The computer-assisted navigation system often consisted of several optical localizers and provided surgeons with quantitative and intuitive screen outcomes, achieving immediate intraoperative revise of condylar malpositioning without mechanical stress. 5,28,29,35,36 However, the localizers attaching to the bone once loosened after osteotomy, the navigation system had to abort. 5 Due to the instability of sensors, the navigation system was recommended for senior surgeons in difficult cases.…”
Section: Computer-assisted Navigation Systemmentioning
confidence: 99%
“…Previously, we reported an orthognathic surgery system using an image-guided navigation using optical tracking or electromagnetic tracking, and the navigation-based orthognathic surgery could help to accurately reposition the maxilla in the target position [13,27]. Mazzoni et al [28] reported that preoperative surgical plan reproducibility was 86.5% with the help of intraoperative navigation based on the optical tracking, and 80% without the navigation.…”
Section: Discussionmentioning
confidence: 99%
“…To obtain skeletal models with artifact-free, high-resolution dentitions, the dental plaster casts of the patients were scanned using an optical model scanner (Maestro 3D, Maestro, Pisa, Italy) [23] and the scanned dentitions were fused with the corresponding maxillary and mandibular models using a modified iterative closest point (ICP) algorithm combined with a coherent point drift (CPD) algorithm [24][25][26][27][28]. A k-dimensional tree algorithm was used to accelerate and optimize the ICP algorithm process used for finding the closest points in the corresponding models by searching for the nearest neighbors [29].…”
Section: Acquisition Of Patients' Ct and 3d Dentition Datamentioning
confidence: 99%