A computer-implemented method includes receiving a 3D model of upper teeth (U1) of a patient (P) and a 3D model of lower teeth (L1) of the patient (P1), and receiving a plurality of 2D images, each image representative of at least a portion of the upper teeth (U1) and lower teeth (L1) of the patient (P). The method also includes determining, based on the 2D images, a spatial relationship between the upper teeth (U1) and lower teeth (L1) of the patient (P).

An image processing method to provide a final panoramic image of at least a portion of a head of a patient, wherein a plurality of different provisional panoramic images are calculated from captured frame data sets through the variation of a reconstruction parameter; the provisional panoramic images are scanned for recognizable structures; the imaging quality of the recognizable structures is determined; the variation of the at least one reconstruction parameter for the calculation of different provisional panoramic images of those frame data sets which have recognizable structures with the highest imaging quality is determined; and with reference to the determined variation of the reconstruction parameter of step a final panoramic image is calculated. A computer-readable storage medium comprising instructions which cause a computer to perform the method and an imaging system having such a storage medium are also described.

Methods and apparatuses for asynchronously identifying and modeling a gingiva strip from the three-dimensional (3D) dental model of the patient's dentition. These methods may reduce the time required to generate accurate 3D dental models and therefore may reduce and streamline the process of generating dental treatment plans.

The present disclosure provides methods, computing device readable medium, devices, and systems that utilize a cheek retractor and/or a mobile device holder for case assessment and/or dental treatments. One cheek retractor includes a first and a second lip holder, both including imaging markers of a predetermined size to determine a scale of teeth of a user, where each imaging marker is located a predefined distance from the remaining imaging markers, and where the lip holder is to hold a cheek away from a mouth of a user to expose teeth of the user. A mobile device holder can include elements to receive a mobile device to capture images of the patient's teeth.

During an intraoral scan session, a processing device receives a plurality of intraoral images of a dental site. The processing device determines that a historical template of the dental site is existent and registers a first intraoral image of the plurality of intraoral images to the historical template at a first region of the dental site depicted in the historical template. The processing device may register one or more remaining intraoral images of the plurality of intraoral images to the historical template at a second region of the dental site depicted in the historical template. The first region may be separated from the second region.

Described herein are computer-implemented methods for analyzing an input image of a mouth region from a user to provide information regarding a disease or condition of the mouth region, a computing device configured to receive the input images from a user; and a trained machine learning system. In some embodiments, the computing device is configured to transmit an oral health score to the user.

A method for monitoring the positioning of the teeth including production of a three-dimensional digital initial reference model of the arches of the patient and, for each tooth, definition, from the initial reference model, of a three-dimensional digital reference tooth model; acquisition of updated image of at least one two-dimensional image of the arches in actual acquisition conditions; analysis of each updated image and production, for each updated image, of an updated map; optionally, determination, for each updated image, of rough virtual acquisition conditions approximating the actual acquisition conditions; searching, for each updated image, for a final reference model corresponding to the positioning of the teeth during the acquisition of the updated image, for each tooth model, comparison of the positionings of the tooth model in the initial reference model and in the reference model obtained at the end of the preceding steps to determine the movement of the teeth.

A computer-implemented method for automated classification of 3D image data of teeth includes a computer receiving one or more of 3D image data sets where a set defines an image volume of voxels representing 3D tooth structures within the image volume associated with a 3D coordinate system. The computer pre-processes each of the data sets and provides each of the pre-processed data sets to the input of a trained deep neural network. The neural network classifies each of the voxels within a 3D image data set on the basis of a plurality of candidate tooth labels of the dentition. Classifying a 3D image data set includes generating for at least part of the voxels of the data set a candidate tooth label activation value associated with a candidate tooth label defining the likelihood that the labelled data point represents a tooth type as indicated by the candidate tooth label.

A method for automated detection of landmarks from 3D medical image data using deep learning according to the present inventive concept, the method includes receiving a 3D volume medical image, generating a 2D intensity value projection image based on the 3D volume medical image, automatically detecting an initial anatomical landmark using a first convolutional neural network based on the 2D intensity value projection image, generating a 3D volume area of interest based on the initial anatomical landmark and automatically detecting a detailed anatomical landmark using a second convolutional neural network different from the first convolutional neural network based on the 3D volume area of interest.

Systems and methods are provided for scanning a dental impression to obtain a digital model of a patient's dentition as an input to computer aided design (CAD) and computer aided manufacturing (CAM) methods for producing dental prostheses.