Dataset Information

A Method of Three-Dimensional Recording of Mandibular Movement Based on Two-Dimensional Image Feature Extraction.

ABSTRACT:

Background and objective

To develop a real-time recording system based on computer binocular vision and two-dimensional image feature extraction to accurately record mandibular movement in three dimensions.

Methods

A computer-based binocular vision device with two digital cameras was used in conjunction with a fixed head retention bracket to track occlusal movement. Software was developed for extracting target spatial coordinates in real time based on two-dimensional image feature recognition. A plaster model of a subject's upper and lower dentition were made using conventional methods. A mandibular occlusal splint was made on the plaster model, and then the occlusal surface was removed. Temporal denture base resin was used to make a 3-cm handle extending outside the mouth connecting the anterior labial surface of the occlusal splint with a detection target with intersecting lines designed for spatial coordinate extraction. The subject's head was firmly fixed in place, and the occlusal splint was fully seated on the mandibular dentition. The subject was then asked to make various mouth movements while the mandibular movement target locus point set was recorded. Comparisons between the coordinate values and the actual values of the 30 intersections on the detection target were then analyzed using paired t-tests.

Results

The three-dimensional trajectory curve shapes of the mandibular movements were consistent with the respective subject movements. Mean XYZ coordinate values and paired t-test results were as follows: X axis: -0.0037 ± 0.02953, P = 0.502; Y axis: 0.0037 ± 0.05242, P = 0.704; and Z axis: 0.0007 ± 0.06040, P = 0.952. The t-test result showed that the coordinate values of the 30 cross points were considered statistically no significant. (P<0.05).

Conclusions

Use of a real-time recording system of three-dimensional mandibular movement based on computer binocular vision and two-dimensional image feature recognition technology produced a recording accuracy of approximately ± 0.1 mm, and is therefore suitable for clinical application. Certainly, further research is necessary to confirm the clinical applications of the method.

SUBMITTER: Yuan F

PROVIDER: S-EPMC4573517 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Publications

A Method of Three-Dimensional Recording of Mandibular Movement Based on Two-Dimensional Image Feature Extraction.

Yuan Fusong F Sui Huaxin H Li Zhongke Z Yang Huifang H Lü Peijun P Wang Yong Y Sun Yuchun Y

PloS one 20150916 9

<h4>Background and objective</h4>To develop a real-time recording system based on computer binocular vision and two-dimensional image feature extraction to accurately record mandibular movement in three dimensions.<h4>Methods</h4>A computer-based binocular vision device with two digital cameras was used in conjunction with a fixed head retention bracket to track occlusal movement. Software was developed for extracting target spatial coordinates in real time based on two-dimensional image feature ...[more]

PMID: 26375800

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Project description:ObjectiveDevelopments in digital technology have permitted researchers to study mandibular movements. Here, the accuracy of a real-time, computerized, binocular, three-dimensional (3D) trajectory-tracking device for recording functional mandibular movements was evaluated.MethodsAn occlusal splint without the occlusal region was created based on a plaster cast of the lower dentition. The splint was rigidly connected with a target on its labial side and seated on the cast. The cast was then rigidly attached to the stage of a high-precision triaxial electronic translator, which was used to move the target-cast-stage complex. Half-circular movements (5.00-mm radius) in three planes (XOY, XOZ, YOZ) and linear movements along the x-axis were performed at 5.00 mm/s. All trajectory points were recorded with the binocular 3D trajectory-tracking device and fitted to arcs or lines, respectively, with the Imageware software. To analyze the accuracy of the trajectory-tracking device, the mean distances between the trajectory points and the fitted arcs or lines were measured, and the mean differences between the lengths of the fitted arcs' radii and a set value (5.00 mm) were then calculated. A one-way analysis of variance was used to evaluate the spatial consistency of the recording accuracy in three different planes.ResultsThe mean distances between the trajectory points and fitted arcs or lines were 0.076 ± 0.033 mm or 0.089 ± 0.014 mm. The mean difference between the lengths of the fitted arcs' radii and the set value (5.00 mm) was 0.025 ± 0.071 mm. A one-way ANOVA showed that the recording errors in three different planes were not statistically significant.ConclusionThese results suggest that the device can record certain movements at 5.00 mm/s, which is similar to the speed of functional mandibular movements. In addition, the recordings had an error of <0.1 mm and good spatial consistency. Thus, the device meets some of the requirements necessary for recording human mandibular movements.

Project description:Traditional histology is the gold standard for tissue studies, but it is intrinsically reliant on two-dimensional (2D) images. Study of volumetric tissue samples such as whole hearts produces a stack of misaligned and distorted 2D images that need to be reconstructed to recover a congruent volume with the original sample's shape. In this paper, we develop a mathematical framework called Transformation Diffusion (TD) for stack alignment refinement as a solution to the heat diffusion equation. This general framework does not require contour segmentation, is independent of the registration method used, and is trivially parallelizable. After the first stack sweep, we also replace registration operations by operations in the space of transformations, several orders of magnitude faster and less memory-consuming. Implementing TD with operations in the space of transformations produces our Transformation Diffusion Reconstruction (TDR) algorithm, applicable to general transformations that are closed under inversion and composition. In particular, we provide formulas for translation and affine transformations. We also propose an Approximated TDR (ATDR) algorithm that extends the same principles to tensor-product B-spline transformations. Using TDR and ATDR, we reconstruct a full mouse heart at pixel size 0.92µm×0.92µm, cut 10µm thick, spaced 20µm (84G). Our algorithms employ only local information from transformations between neighboring slices, but the TD framework allows theoretical analysis of the refinement as applying a global Gaussian low-pass filter to the unknown stack misalignments. We also show that reconstruction without an external reference produces large shape artifacts in a cardiac specimen while still optimizing slice-to-slice alignment. To overcome this problem, we use a pre-cutting blockface imaging process previously developed by our group that takes advantage of Brewster's angle and a polarizer to capture the outline of only the topmost layer of wax in the block containing embedded tissue for histological sectioning.

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Dataset Information

A Method of Three-Dimensional Recording of Mandibular Movement Based on Two-Dimensional Image Feature Extraction.

Background and objective

Methods

Results

Conclusions

Publications

A Method of Three-Dimensional Recording of Mandibular Movement Based on Two-Dimensional Image Feature Extraction.

Similar Datasets

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