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Reduced Projection Algorithm for 2D Cephalograms Derived from 3D CBCT Images in Orthodontics

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posted on 20.06.2014, 00:00 by Abdelrahman Salem
Cone Beam Computed Tomography (CBCT) has become an increasingly important tool in treatment planning and diagnosis in orthodontics. The popularity of CBCT has increased tremendously among dentists and orthodontists. Unfortunately, the increase in the ionizing radiation and reports in the lay press about radiation overdose with CT scanners created arguments against CBCT as the imaging technique of choice for comprehensive orthodontic assessment. The purpose of this feasibility study is to find a threshold number of projections produced by the Adaptive-Steepest-Descent-Projection-Onto-Convex-Sets (ASD-POCS) algorithm from the original iCAT 3D CBCT to be used reliably for 2D evaluation of orthodontic diagnostic records. Virtual 3D digital images of craniofacial structures were made by the iCAT CBCT machine (Imaging Sciences International, Hatfield, Pa) of four subjects. The ASD-POCS algorithm was used to derive different compression rates by reconstructing the 3D digital images using lower number of projections. Five different compression rates were compared (320iCAT, 300 UC, 151 UC, 76 UC, and 39 UC). Dolphin 3D (Version 11.7, Dolphin Imaging, Chartsworth, CA) was used to project the 3D images of different compression rates into lateral and postero-anterior (PA) cephalograms. The accuracy of landmark identification in cepahlograms derived from different compression rates was used to evaluate the quality of compressions. The preliminary results of this feasibility study based on the small sample (n=4), showed that there is no mean difference of error distances between a set of landmark locations in both lateral and PA cephalometric radiographs derived from CBCT images at different compression rates. None of the means of error distances of landmark locations in different compressions rates exceeded 1.5 mm error margin for both lateral and PA cephalometric radiographs.



Kusnoto, Budi



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University of Illinois at Chicago

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Evans, Carla Pan, Xiaochuan

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