Patent classifications
A61C13/34
COMPENSATING DEVIATIONS USING A PARTIAL MANUFACTURING RESULT
The invention relates to method for manufacturing a dental prosthetic assembly. The dental prosthetic assembly comprises a first and a second element. The first element comprises a first connection portion with a reception configured to establish a mechanical connection between the first and the second element by receiving a protrusion of a second connection portion comprised by the second element.
COMPENSATING DEVIATIONS USING A PARTIAL MANUFACTURING RESULT
The invention relates to method for manufacturing a dental prosthetic assembly. The dental prosthetic assembly comprises a first and a second element. The first element comprises a first connection portion with a reception configured to establish a mechanical connection between the first and the second element by receiving a protrusion of a second connection portion comprised by the second element.
CAPTURING TRUE BITE AND OCCLUSION CONTACTS
A method for determining biting occlusion of a patient's teeth including generating a first 3D digital model of the patient's lower arch in non-occlusion. A second 3D digital model of the patient's upper arch in non-occlusion may be generated. A third 3D digital model of the patient's upper and lower arches in biting occlusion may be generated. The first and second 3D digital models May be aligned with corresponding teeth of the third 3D digital model to generate a fourth 3D model of the patient's teeth in biting occlusion.
CAPTURING TRUE BITE AND OCCLUSION CONTACTS
A method for determining biting occlusion of a patient's teeth including generating a first 3D digital model of the patient's lower arch in non-occlusion. A second 3D digital model of the patient's upper arch in non-occlusion may be generated. A third 3D digital model of the patient's upper and lower arches in biting occlusion may be generated. The first and second 3D digital models May be aligned with corresponding teeth of the third 3D digital model to generate a fourth 3D model of the patient's teeth in biting occlusion.
Operating intraoral scanner capable of constructing accurate dental model and method thereof
A method of operating an intraoral scanner. The intraoral scanner includes an image capturing device and a processor. The method includes the image capturing device sequentially capturing M images along a first dental arch, the processor establishing a first arch model of the first dental arch according to the M images, the image capturing device sequentially capturing N images along a straight-line path from a first anchor to a second anchor on the first dental arch, the processor generating first coordinates of the first anchor and second coordinates of the second anchor according to the N images, and the processor calibrating the first arch model according to the first coordinates and the second coordinates. The first anchor is located at one side of a dental midline of the first dental arch. The second anchor is located at the other side of the dental midline of the first dental arch.
Operating intraoral scanner capable of constructing accurate dental model and method thereof
A method of operating an intraoral scanner. The intraoral scanner includes an image capturing device and a processor. The method includes the image capturing device sequentially capturing M images along a first dental arch, the processor establishing a first arch model of the first dental arch according to the M images, the image capturing device sequentially capturing N images along a straight-line path from a first anchor to a second anchor on the first dental arch, the processor generating first coordinates of the first anchor and second coordinates of the second anchor according to the N images, and the processor calibrating the first arch model according to the first coordinates and the second coordinates. The first anchor is located at one side of a dental midline of the first dental arch. The second anchor is located at the other side of the dental midline of the first dental arch.
TOOTH ARRANGEMENT DECAL
A tooth arrangement decal constructed and arranged to facilitate the rapid communication of the placement of prostheses with respect to prosthetic teeth on a wax rim and a method of using the same is provided. The tooth arrangement decal may instruct the arrangement of teeth, and in particular, central incisors, lateral incisors, and canines. The tooth arrangement decal may be constructed and arranged to eliminate the need for tedious measurements and inscription of markings on a wax ring to indicate the appropriate location for prostheses during denture set-up.
TOOTH ARRANGEMENT DECAL
A tooth arrangement decal constructed and arranged to facilitate the rapid communication of the placement of prostheses with respect to prosthetic teeth on a wax rim and a method of using the same is provided. The tooth arrangement decal may instruct the arrangement of teeth, and in particular, central incisors, lateral incisors, and canines. The tooth arrangement decal may be constructed and arranged to eliminate the need for tedious measurements and inscription of markings on a wax ring to indicate the appropriate location for prostheses during denture set-up.
TRAINING MACHINE LEARNING MODELS TO PERFORM ALIGNER DAMAGE PREDICTION
Embodiments relate to an aligner breakage solution that tests damage to an aligner using machine learning. A method includes of training a machine learning model to predict damage to an orthodontic aligner includes gathering a training dataset comprising digital designs for a plurality of orthodontic aligners, wherein each digital design is associated with a respective orthodontic aligner of the plurality of orthodontic aligners, and wherein each digital design comprises metadata indicating whether the associated respective orthodontic aligner was damaged during manufacturing of the associated respective orthodontic aligner. The method further includes training the machine learning model using the training dataset, wherein the machine learning model is trained to process data from a digital design for an orthodontic aligner and to output a probability that the orthodontic aligner associated with the digital design will be damaged during manufacturing of the orthodontic aligner.
TRAINING MACHINE LEARNING MODELS TO PERFORM ALIGNER DAMAGE PREDICTION
Embodiments relate to an aligner breakage solution that tests damage to an aligner using machine learning. A method includes of training a machine learning model to predict damage to an orthodontic aligner includes gathering a training dataset comprising digital designs for a plurality of orthodontic aligners, wherein each digital design is associated with a respective orthodontic aligner of the plurality of orthodontic aligners, and wherein each digital design comprises metadata indicating whether the associated respective orthodontic aligner was damaged during manufacturing of the associated respective orthodontic aligner. The method further includes training the machine learning model using the training dataset, wherein the machine learning model is trained to process data from a digital design for an orthodontic aligner and to output a probability that the orthodontic aligner associated with the digital design will be damaged during manufacturing of the orthodontic aligner.