
Proceedings Paper
Voxel-based registration of simulated and real patient CBCT data for accurate dental implant pose estimationFormat | Member Price | Non-Member Price |
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Paper Abstract
The success of dental implant-supported prosthesis is directly linked to the accuracy obtained during implant’s pose estimation (position and orientation). Although traditional impression techniques and recent digital acquisition methods are acceptably accurate, a simultaneously fast, accurate and operator-independent methodology is still lacking. Hereto, an image-based framework is proposed to estimate the patient-specific implant’s pose using cone-beam computed tomography (CBCT) and prior knowledge of implanted model. The pose estimation is accomplished in a threestep approach: (1) a region-of-interest is extracted from the CBCT data using 2 operator-defined points at the implant’s main axis; (2) a simulated CBCT volume of the known implanted model is generated through Feldkamp-Davis-Kress reconstruction and coarsely aligned to the defined axis; and (3) a voxel-based rigid registration is performed to optimally align both patient and simulated CBCT data, extracting the implant’s pose from the optimal transformation. Three experiments were performed to evaluate the framework: (1) an in silico study using 48 implants distributed through 12 tridimensional synthetic mandibular models; (2) an in vitro study using an artificial mandible with 2 dental implants acquired with an i-CAT system; and (3) two clinical case studies. The results shown positional errors of 67±34μm and 108μm, and angular misfits of 0.15±0.08° and 1.4°, for experiment 1 and 2, respectively. Moreover, in experiment 3, visual assessment of clinical data results shown a coherent alignment of the reference implant. Overall, a novel image-based framework for implants’ pose estimation from CBCT data was proposed, showing accurate results in agreement with dental prosthesis modelling requirements.
Paper Details
Date Published: 20 March 2015
PDF: 6 pages
Proc. SPIE 9414, Medical Imaging 2015: Computer-Aided Diagnosis, 94143H (20 March 2015); doi: 10.1117/12.2082806
Published in SPIE Proceedings Vol. 9414:
Medical Imaging 2015: Computer-Aided Diagnosis
Lubomir M. Hadjiiski; Georgia D. Tourassi, Editor(s)
PDF: 6 pages
Proc. SPIE 9414, Medical Imaging 2015: Computer-Aided Diagnosis, 94143H (20 March 2015); doi: 10.1117/12.2082806
Show Author Affiliations
António H. J. Moreira, ICVS/3B’s, PT Government Associate Lab. (Portugal)
Univ. do Minho (Portugal)
DIGARC, Polytechnic Institute of Cávado and Ave (Portugal)
Sandro Queirós, ICVS/3B’s, PT Government Associate Lab. (Portugal)
Univ. do Muno (Portugal)
Pedro Morais, ICVS/3B’s, PT Government Associate Lab. (Portugal)
Nuno F. Rodrigues, ICVS/3B’s, PT Government Associate Lab.. (Portugal)
Univ. of Minho (Portugal)
DIGARC, Polytechnic Institute of Cávado and Ave, (Portugal)
André Ricardo Correia, Univ. do Porto (Portugal)
Univ. do Minho (Portugal)
DIGARC, Polytechnic Institute of Cávado and Ave (Portugal)
Sandro Queirós, ICVS/3B’s, PT Government Associate Lab. (Portugal)
Univ. do Muno (Portugal)
Pedro Morais, ICVS/3B’s, PT Government Associate Lab. (Portugal)
Nuno F. Rodrigues, ICVS/3B’s, PT Government Associate Lab.. (Portugal)
Univ. of Minho (Portugal)
DIGARC, Polytechnic Institute of Cávado and Ave, (Portugal)
André Ricardo Correia, Univ. do Porto (Portugal)
Valter Fernandes, ICVS/3B’s, PT Government Associate Lab. (Portugal)
A. C. M. Pinho, Univ. do Minho (Portugal)
Jaime C. Fonseca, Univ. do Minho (Portugal)
João L. Vilaça, ICVS/3B’s - PT Government Associate Lab. (Portugal)
DIGARC, Instituto Politécnico do Cávado e do Ave (Portugal)
A. C. M. Pinho, Univ. do Minho (Portugal)
Jaime C. Fonseca, Univ. do Minho (Portugal)
João L. Vilaça, ICVS/3B’s - PT Government Associate Lab. (Portugal)
DIGARC, Instituto Politécnico do Cávado e do Ave (Portugal)
Published in SPIE Proceedings Vol. 9414:
Medical Imaging 2015: Computer-Aided Diagnosis
Lubomir M. Hadjiiski; Georgia D. Tourassi, Editor(s)
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