Abstract: Methods and apparatuses for generating and displaying a model of a subject's teeth. Described herein are intraoral scanning methods and apparatuses for generating a three-dimensional model of a subject's intraoral region (e.g., teeth). These methods and apparatuses may be used for identifying and evaluating lesions, caries and cracks in the teeth.

Abstract: Provided herein are devices and methods generating synthetic views of a subject's teeth. Methods and processes are provided to image the subject's teeth with a dental scan. Methods and processes are also provided to automatically 3D render the subject's teeth with the scan images. Methods and apparatuses are also provided to generate simulated synthetic views of the subject's dentition from various perspectives.

Abstract: In embodiments, a processing device detects a margin line in a model of a preparation from one or more images. The processing device determines, for each segment of a plurality of segments of the margin line, a quality score for the segment. The processing device determines that a segment of the margin line has a quality score that is below a quality threshold, wherein the segment of the margin line was generated based on a first set of images. Responsive to determining that the segment of the margin line has the quality score that is below the quality threshold, the processing devices updates the three-dimensional model of the preparation by replacing a portion of the three-dimensional model associated with the segment of the margin line with image data from at least one of a new image or a second set of images.

Abstract: Methods and apparatuses for taking, using and displaying three-dimensional (3D) volumetric models of a patient's dental arch. A 3D volumetric model may include surface (e.g., color) information as well as information on internal structure, such as near-infrared (near-IR) transparency values for internal structures including enamel and dentin.

Abstract: Methods and apparatuses (including devices and systems, such as intraoral scanners and software) for analyzing images of a subject's teeth. In some examples these methods may include examining the same teeth or tooth regions across different times and/or different imaging modalities, including but not limited to visible light, infrared, florescent, etc. Also described herein are methods and apparatuses for using a single, master, control for automatically or semi-automatically simultaneously adjusting multiple imaging parameters across multiple images of a region taken with different imaging modalities and/or at different times.

Abstract: Methods and apparatuses for generating and displaying a model of a subject's teeth. Described herein are intraoral scanning methods and apparatuses for generating a three-dimensional model of a subject's intraoral region (e.g., teeth). These methods and apparatuses may be used for identifying and evaluating lesions, caries and cracks in the teeth.

Abstract: Calibrating an intraoral scanner includes obtaining reference data of a reference three-dimensional (3D) representation of a calibration object and obtaining, based on the intraoral scanner being used by a user to scan the 3D calibration object, and from one or more device to real-world coordinate transformations of two-dimensional (2D) images of the 3D calibration object, measurement data. Calibrating the intraoral scanner further includes aligning the measurement data to the reference data to obtain alignment data and updating, based on the alignment data, said one or more transformations.

Abstract: Methods and apparatuses for generating and displaying a model of a subject's teeth. Described herein are intraoral scanning methods and apparatuses for generating a three-dimensional model of a subject's intraoral region (e.g., teeth). These methods and apparatuses may be used for identifying and evaluating lesions, caries and cracks in the teeth.

Abstract: A processing device may receive a plurality of intraoral scans of the patient that were generated by an intraoral scanner, determine a three-dimensional surface of at least a portion of one or more dental arch of the patient using the plurality of intraoral scans, automatically determine whether a restorative dental object is represented in at least one of the three-dimensional surface or one or more intraoral scans of the plurality of intraoral scans, and automatically generate a prescription for treating the one or more teeth based at least in part on at least one of a) a presence or absence of a restorative dental object in at least one of the three-dimensional surface or the one or more intraoral scans or b) a location of the restorative dental object in the one or more dental arch of the patient.

Abstract: A method of generating a 3D model includes: determining a 3D surface comprising a preparation tooth using a first plurality of intraoral scans generated by an intraoral scanner at a first time; receiving one or more additional intraoral scans of the preparation tooth that were generated by the intraoral scanner at a second time; determining a change to one or more portions of the preparation tooth between the three-dimensional surface and the one or more additional intraoral scans; determining, based at least in part on the change to the preparation tooth, whether to use a) the 3D surface, b) data from the one or more additional intraoral scans or c) a combination of the 3D surface and the data from the one or more additional intraoral scans to depict one or more portions of the preparation tooth; and generating the 3D model comprising the preparation tooth.

Abstract: A system comprises an intraoral scanner configured to generate scan data comprising a plurality of images of a first and second dental site, wherein each of the plurality of images comprises a time stamp and height information. The system further comprises a computing device configured to: receive the scan data; determine a first subset of the images to use for the first dental site based at least in part on a) time stamps of images in the first subset and b) geometrical data of the images in the first subset; determine a second subset of the images to use for the second dental site based at least in part on a) time stamps of images in the second subset and b) geometrical data of the images in the second subset; and generate a three-dimensional model of at least a portion of a dental arch.

Abstract: Calibrating an intraoral scanner includes obtaining reference data of a reference three-dimensional (3D) representation of a calibration object and obtaining, based on the intraoral scanner being used by a user to scan the 3D calibration object, and from one or more device to real-world coordinate transformations of two-dimensional (2D) images of the 3D calibration object, measurement data. Calibrating the intraoral scanner further includes aligning the measurement data to the reference data to obtain alignment data and updating, based on the alignment data, said one or more transformations.

Abstract: Systems and methods for tracking orthodontic treatment using camera images. One or more input two-dimensional (2D) images of a patient's current teeth taken by a camera device can be received. The input 2D image(s) can correspond to occlusal view(s) of the patient's current teeth of the patient's upper and/or lower jaw in a current configuration. One or more rendered 2D images representing target positions of the patient's teeth at a planned treatment stage can be assessed. The rendered 2D image(s) can be based on virtual camera parameters that correspond to the input 2D image(s). One or more rotational differences between the patient's current teeth and the planned treatment stage can be determined by comparing silhouettes of corresponding teeth of the input 2D image(s) to the rendered 2D image(s). A difference indicator indicating the rotational difference(s) can be output.

Abstract: Systems and computer-readable media for preparing a dental restoration having optical properties matching optical properties of a patient's tooth may be configured to generate a volumetric model of at least a portion of the patient's tooth from a three-dimensional (3D) intraoral scan including both near-IR wavelength data and visible light wavelength data providing both an accurate outer surface of the patient's tooth and an internal structure of a region of enamel extending from the outer surface of the patient's tooth to the patient's dentine.

Abstract: Methods and apparatuses for assessing oral health and automatically providing diagnosis of one or more oral diseases. Described herein are intraoral scanning methods and apparatuses for collecting and analyzing image data and to detect and visualize features within image data that are indicative of oral diseases or conditions, such as gingival inflammation or oral cancer. These methods and apparatuses may be used for identifying and evaluating lesions, redness and inflammation in soft tissue and caries and cracks in the teeth. The methods an include training a machine learning model and using the trained machine learning model to provide a diagnosis of an oral disease or condition based on image data collected using multiple scanning modes of an intraoral scanner.

Abstract: A processing device receives a plurality of intraoral scans of a dental arch. The processing device determines, from the plurality of intraoral scans, a first set of intraoral scans that depict a restorative object and a second set of intraoral scans that fail to depict any restorative object. The processing device generates a multi-resolution three-dimensional model of the dental arch, wherein a first portion of the multi-resolution three-dimensional model is generated from the first set of intraoral scans, has a first resolution and represents the restorative object, and wherein a second portion of the multi-resolution three-dimensional model is generated from the second set of intraoral scans, has a second resolution and represents a remainder of the dental arch, wherein the first resolution is greater than the second resolution.

Abstract: In embodiments, a processing device generates a three-dimensional model of a dental site from scan data, the three-dimensional model comprising a representation of a tooth, wherein a portion of the three-dimensional model comprises an interfering surface that obscures a portion of the tooth. The processing device receives or generates an image of the tooth, wherein the image depicts the interfering surface. The processing device processes the image to generate a modified image, wherein the portion of the tooth that was obscured by the interfering surface in the image is shown in the modified image. The processing device updates the three-dimensional model of the dental site by replacing, using the modified image, the portion of the three-dimensional model that comprises the interfering surface that obscures the portion of the tooth, wherein the portion of the tooth that was obscured in the three-dimensional model is shown in an updated three-dimensional model.

Abstract: Systems and methods for monitoring a subject's teeth during orthodontic treatment. An input 2D image of the subject's current teeth including a wide angle occlusal view of the subject's upper and/or lower jaw at a current treatment stage can be received. Virtual camera parameters corresponding to the input 2D image can be determined. A rendered 2D image of the subject's teeth can be generated from a 3D model of the subject's upper and/or lower jaw at a planned treatment stage with the virtual camera parameters. Differences between the subject's teeth from the input 2D image and the rendered 2D image using tooth centers can be determined. An indicator indicating the differences can be output.

Abstract: Methods and apparatuses for assessing oral health and automatically providing diagnosis of one or more oral diseases. Described herein are intraoral scanning methods and apparatuses for collecting and analyzing image data and to detect and visualize features within image data that are indicative of oral diseases or conditions, such as gingival inflammation or oral cancer. These methods and apparatuses may be used for identifying and evaluating lesions, redness and inflammation in soft tissue and caries and cracks in the teeth. The methods can include training a machine learning model and using the trained machine learning model to provide a diagnosis of an oral disease or condition based on image data collected using multiple scanning modes of an intraoral scanner.