Motion correction for separate mandibular and cranial movements in cone beam CT reconstructions.

Background: Patient motions are a repeatedly reported phenomenon in oral and maxillofacial cone beam CT scans, leading to reconstructions of limited usability. In certain cases, independent movements of the mandible induce unpredictable motion patterns. Previous motion correction methods are not able to handle such complex cases of patient movements.

Projection-based improvement of 3D reconstructions from motion-impaired dental cone beam CT data.

Purpose: Computed tomography (CT) and, in particular, cone beam CT (CBCT) have been increasingly used as a diagnostic tool in recent years. Patient motion during acquisition is common in CBCT due to long scan times. This results in degraded image quality and may potentially increase the number of retakes.

A method for automatic forensic facial reconstruction based on dense statistics of soft tissue thickness.

In this paper, we present a method for automated estimation of a human face given a skull remain. Our proposed method is based on three statistical models. A volumetric (tetrahedral) skull model encoding the variations of different skulls, a surface head model encoding the head variations, and a dense statistic of facial soft tissue thickness (FSTT).

A Region-Based Gauss-Newton Approach to Real-Time Monocular Multiple Object Tracking.

We propose an algorithm for real-time 6DOF pose tracking of rigid 3D objects using a monocular RGB camera. The key idea is to derive a region-based cost function using temporally consistent local color histograms. While such region-based cost functions are commonly optimized using first-order gradient descent techniques, we systematically derive a Gauss-Newton optimization scheme which gives rise to drastically faster convergence and highly accurate and robust tracking performance.

Ultrahigh temporal resolution of visual presentation using gaming monitors and G-Sync.

Vision unfolds as an intricate pattern of information processing over time. Studying vision and visual cognition therefore requires precise manipulations of the timing of visual stimulus presentation. Although standard computer display technologies offer great accuracy and precision of visual presentation, their temporal resolution is limited.

Automated detection of patient movement during a CBCT scan based on the projection data.

Objectives: To develop an automated procedure to detect patient motion on the projection images acquired during a cone beam computed tomography (CBCT) scan and to evaluate the method's feasibility on small real-world CBCT images in relation to visual assessment.

Methods: Based on optical flow theory, software was developed using the sequence of the projection images of a CBCT machine for automated detection of patient motion. Averaged acceleration vectors were used as measurement data and compared with visual assessment of the projection images displayed as video.

Auto calibration of a cone-beam-CT.

Purpose: This paper introduces a novel autocalibration method for cone-beam-CTs (CBCT) or flat-panel CTs, assuming a perfect rotation. The method is based on ellipse-fitting. Autocalibration refers to accurate recovery of the geometric alignment of a CBCT device from projection images alone, without any manual measurements.

A contact-free volumetric measurement of facial volume after third molar osteotomy: proof of concept.

Objective: The present study tested the reliability of an optical scanning device for the objective assessment of postoperative facial swelling.

Study Design: Twenty control subjects bearing a defined volume of water (10-30 mL) in an intraorally carried balloon were tested to assess the measurement accuracy of the device. As a proof of concept, facial volumes of 59 surgical cases were recorded before osteotomy and 1 and 7 days after intervention with the use of a structured light scanner.

An optimized video system for augmented reality in endodontics: a feasibility study.

Objectives: We propose an augmented reality system for the reliable detection of root canals in video sequences based on a k-nearest neighbor color classification and introduce a simple geometric criterion for teeth.

Material And Methods: The new software was implemented using C++, Qt, and the image processing library OpenCV. Teeth are detected in video images to restrict the segmentation of the root canal orifices by using a k-nearest neighbor algorithm.

Artefacts in CBCT: a review.

Artefacts are common in today's cone beam CT (CBCT). They are induced by discrepancies between the mathematical modelling and the actual physical imaging process. Since artefacts may interfere with the diagnostic process performed on CBCT data sets, every user should be aware of their presence.

Alignment of cone beam computed tomography data using intra-oral fiducial markers.

This article illustrates a new method to align and merge two partially overlapping volumes each of them generated by cone beam computed tomography (CBCT). The aggregate volume covers a larger area of investigation and is determined by localizing one fixed LEGO brick in both of the primal volumes. Based on the LEGO brick an approximate registration of the volumes is determined.

Accurate registration of random radiographic projections based on three spherical references for the purpose of few-view 3D reconstruction.

Precise registration of radiographic projection images acquired in almost arbitrary geometries for the purpose of three-dimensional (3D) reconstruction is beset with difficulties. We modify and enhance a registration method [R. Schulze, D.