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In preclinical radiation research, it is challenging to localize soft tissue targets based on cone beam computed tomography (CBCT) guidance.
Inaccurate visualization of the inter-occlusal relationship has raised an important challenge to virtual planning for orthognathic surgery based on cone beam computerized tomography (CBCT).
We used a navigation system for computer-assisted preoperative planning based on cone beam tomography with virtual reconstruction to obtain symmetry of the orbit and intraoperative control of virtual contours.
The objective of this study was to verify if accurate patient-to-image registration for precision navigation in maxillofacial surgery is possible based on cone beam computed tomography (CBCT) image data.
Computer-designed surgical templates based on (cone beam) computer tomographic ((CB CT) images have enabled higher precision and accuracy in implant planning [3].
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The aim of the study was to compare image quality of two different systems based on cone-beam computed tomography (CBCT).
The use of surgical guides based on cone-beam computed tomography is indicated especially in patients with risky or difficult anatomic situations.
Experiments with phantoms and real data showed the suitability of the proposed software architecture for an X-ray small animal CT based on cone-beam geometry.
Most small-animal X-ray computed tomography (CT) scanners are based on cone-beam geometry with a flat-panel detector orbiting in a circular trajectory.
This work presents a comprehensive, novel software architecture for small-animal CT scanners based on cone-beam geometry with circular scanning trajectory.
In this paper we present the massively parallel implementation and optimization of Mangoose++, a CT application for reconstructing 3D volumes from 2D images collected by scanners based on cone-beam geometry.
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