The objective was to study the relationship between laser fluence and ablation efficiency of a femtosecond laser with a Gaussian-shaped pulse used to ablate dentin and enamel for prosthodontic tooth preparation. A diode-pumped thin-disk femtosecond laser with wavelength of 1025 nm and pulse width of 400 fs was used for the ablation of dentin and enamel. The laser spot was guided in a line on the dentin and enamel surfaces to form a groove-shaped ablation zone under a series of laser pulse energies. The width and volume of the ablated line were measured under a three-dimensional confocal microscope to calculate the ablation efficiency. Ablation efficiency for dentin reached a maximum value of 0.020 mm3∕J when the laser fluence was set at 6.51 J∕cm2. For enamel, the maximum ablation efficiency was 0.009 mm3∕J at a fluence of 7.59 J∕cm2.Ablation efficiency of the femtosecond laser on dentin and enamel is closely related to the laser fluence and may reach a maximum when the laser fluence is set to an appropriate value.
The successful application of robots in surgery and other medical fields prompts us that robots can also play an important role in oral restoration. The traditional way of complete denture manufacturing is manual and only high‐level dentists and skilled technicians can do this work well. But we believe that a robot can do this work better and more easily. Artificial teeth are very complicated in shape, and not easy to be grasped and manipulated accurately by a robot gripper. Aiming at improving our previous robot manufacturing system of complete dentures, we present a new method to perform teeth implanting. We improve the previous manufacturing procedure by adding several components in the operating process. By this method, the robot gripper only needs to grasp and implant intermediate blocks, which have very simple shapes and are easy to handle precisely. The 3D human‐machine tooth arrangement software performs the calculation of intermediate blocks’ positions and orientations. We perform the experiment of tooth arrangement for a patient, and obtain a pair of ideal tooth arches. A complete denture can be manufactured according to this result.
Background and ObjectiveTo 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.MethodsA 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.ResultsThe 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)ConclusionsUse 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.
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