Abstract: A method includes the following steps of (i) production with a 3D scanner, of a three-dimensional digital reference model of at least part of a dental arch of the patient, or “initial reference model”; (ii) acquisition, in actual acquisition conditions, by the patient or one of his or her close relatives, with a mobile phone, of at least three two-dimensional images of the dental arches of the patient corresponding to a front view, a right-side view and a left side view of the teeth of the patient, respectively, called “updated images”; and (iii) searching, through modification of the initial reference model, for a final reference model corresponding to the positioning and/or the shape of the teeth on the updated images.

Abstract: A method for generating a 3D digital, updated, model of a dental arch, including: Acquiring at least one updated image. Each updated image representing an active aligner attached, in an operating position, to a dental arch, or ‘image with aligner’, or representing the dental arch without an aligner, or ‘image of uncovered teeth’. Searching in an updated image, referred to as the ‘updated analysis image’, for representations of teeth that are non-compliant with the treatment scenario. If one or more non-compliant teeth are identified, determining, depending on the updated time, one of an intermediate models, or ‘active intermediate model’, then identifying one or more models of teeth representing the noncompliant tooth or teeth, respectively, in the active intermediate model. Deforming the active intermediate model until an updated model is obtained that is compatible with at least one of the updated images.

Abstract: A method for analyzing an image, called “analysis image”, of a dental arch of a patient. The method in which the analysis image is submitted to a neural network, in order to determine at least one value of an image attribute relating to the analysis image. The analysis image is a photograph or an image taken from a film. The image attribute relates to a position or an orientation or a calibration of an acquisition apparatus used to acquire the analysis image or a combination thereof, or a quality of the analysis image, and in particular relating to the brightness, to the contrast or to the sharpness of the analysis image, or a combination thereof.

Abstract: A method for determining a contour of the representation, on a photo of an object made up of one or several elements, referred to as an “actual contour.” The method includes the following steps: 1) application of a first treatment to the photo so as to obtain a first image representing a first contour of the object; 2) application of a second treatment to the photo so as to obtain a second image representing a second contour of the object; 3) association, according to a predetermined association algorithm, of each point of the second contour with a point of the first respective contour, then removal of the points of the first contour that have not been associated with a point of the second contour, the first image then representing a corrected contour of the object.

Abstract: An acquisition kit, including: a mouthpiece intended for being placed into the mouth of a patient and including a reference mark; and an image-acquisition apparatus including a screen for viewing an image that can be acquired, computer memory containing information on target acquisition conditions, and a computer program comprising program code instructions for displaying on said screen a reference in a position such that, when the reference mark matches the reference on the screen, the acquisition apparatus complies with the target acquisition conditions.

Abstract: A method for transforming an “original” view of an “original” digital three-dimensional model into a hyper-realistic view. The method includes creating a “transformation” learning base of more than 1000 “transformation” records. Each transformation record includes a “transformation” photo representing a scene, and a view of a “transformation” digital three-dimensional model modeling the scene, or “transformation view”, the transformation view representing the scene in the same way as the transformation photo. The method includes training at least one “transformation” neural network, by way of the transformation learning base. The method includes submitting the original view to the at least one transformation neural network, such that it transforms it into a hyper-realistic view.

Abstract: A method for analyzing an image, called analysis image, of a dental arch of a patient. The analysis image is submitted to a deep learning device in order to determine at least one value of a tooth attribute relating to a tooth represented on the analysis image, and/or at least one value of an image attribute relating to the analysis image.

Abstract: A method for monitoring the shape of teeth including: producing a three-dimensional digital model of at least one portion of an arch of the patient or “initial reference model”; acquiring at least one two-dimensional image of the arches, referred to as “updated image”, under actual acquisition conditions; analysing each updated image and producing an updated map relating to a piece of discriminating information; optionally determining rough virtual acquisition conditions that approximate the actual acquisition conditions; searching each updated image for a final reference model corresponding to the shape of the teeth, and optionally to the positioning of the teeth, during the acquisition of the updated image; and comparing the shapes of the initial reference model and of the reference model obtained at the end of the preceding steps, referred to as “final reference model”, in order to determine the deformation and/or the movement of teeth between steps a) and b).

Abstract: A dental photography kit that includes a support, taking the form of a housing. The support includes a support attachment part. The kit includes a dental retractor that defines a retractor opening and that includes a retractor attachment part that is removably attached to the support attachment part when the retractor is in the mounted position on the support. The kit includes a camera that is removably attached to the support in an operating position in which the camera is oriented to receive an at least partial image of the retractor opening. The retractor attachment part is articulated on the support attachment part.

Abstract: A method for enriching a historical learning base. Training of a first neural network to transform first photos of first dental scenes into first hyper-realistic images to simulate the effect of a dental event on the first dental scenes. Submission, to the trained first neural network, of a source photo representing a source dental scene in a dental context, so as to obtain a final image representing, hyper-realistically, the source dental scene after simulation of the dental event. Creation of a descriptor of the final image, or “final descriptor.” Creation of a historical record consisting of the final image and the final descriptor, and addition of the historical record in the historical learning base.

Abstract: A method for evaluating an orthodontic appliance. Acquisition of a two-dimensional “appliance image” of teeth at least partially representing the orthodontic appliance in a service position. Acquisition of a two-dimensional “dentition image” of the teeth. If a determination of comparable dental and appliance attributes is not possible from the appliance image and from the dentition image, respectively, conversion of the appliance image and/or of the dentition image so that the appliance image be compatible with the dentition image. Determination of dental and appliance attributes relative to the shape of the tooth represented on the dentition image and relative to the shape of the orthodontic appliance on the appliance image. Comparison of the dental and appliance attributes, followed by determination of at least one score. At least one image is acquired with a mobile phone.

Abstract: Method of enrichment of a reference model to be enriched representing a dental arch. Acquisition, under first real conditions, of a current image of the arch displaying one region. Exploration of the reference model in such a manner as to determine a first view of the reference model, in a first direction of observation the reference image exhibiting a maximum match with the current image. Determination, by comparison of the images, of a first orphan point represented on the current image and not represented on the reference image when the current image is in a first register position in which it is superposed, in the space of the reference model, with the reference image. Addition, in the reference model, of a point on a first straight line parallel to the first direction of observation and passing through the first orphan point in the first register position.

Abstract: A method for modeling a dental arch of a patient. Creation of a historical library including more than 1000 historical tooth models, and assignment, to each historical tooth model, of a value for at least one tooth attribute value. Analysis of at least one analysis image of the dental arch by means of a deep learning device so as to determine at least one analysis tooth zone and at least one tooth attribute value. For each analysis tooth zone determined in the preceding step, search, in the historical library, for a historical tooth model exhibiting a maximal proximity with the analysis image. Arrangement of all of the optimal tooth models so as to create an assembled model which exhibits a maximal proximity Some optionally steps are possible.

Abstract: A method for assessing the shape of an orthodontic aligner, said method comprising the following steps: a?) acquisition of at least one image at least partially representing the aligner in a service position in which it is worn by a patient, called “analysis image”; b?) analysis of the analysis image by means of a deep learning device, preferably a neural network, trained by means of a learning base, so as to determine a value for at least one tooth attribute of an “analysis tooth zone” representing, at least partially, a tooth on said analysis image, the tooth attribute relating to a separation between the tooth represented by the analysis tooth zone, and the aligner represented on the analysis image, and/or for an image attribute of the analysis image, the image attribute relating to a separation between at least one tooth represented on the analysis image, and the aligner represented on said analysis image.

Abstract: A method for evaluating the shape of an orthodontic aligner worn by a patient. Acquisition of at least one two-dimensional image of teeth of the patient as “updated image.” At least one updated image as “aligner image,” at least partially representing the aligner in a service position. At least one updated image as “dentition image,” representing the teeth. If the dentition image is different from the aligner image, conversion of the dentition image so that it represents the teeth as seen under the acquisition conditions used during the acquisition of the aligner image. Determination, for each of a plurality of teeth represented on the dentition and aligner images, of interior and exterior tooth outlines representing the outline of the free end of the tooth on the dentition and aligner images. Comparison of the interior and exterior tooth outlines, followed by determination of at least one score according to the comparison.

Abstract: A simulating method. The method includes acquiring an image of a dental arch of a patient, called the “original image.” The method includes subjecting the original image to a neural network, called the “modification neural network”, trained to locally modify the original image in order to obtain a “modified image.” The method includes presenting the modified image to the patient.

Abstract: A method for modeling a dental arch of a patient. Creation of a historical library including more than 1000 historical tooth models, and assignment, to each historical tooth model, of a value for at least one tooth attribute value. Analysis of at least one analysis image of the dental arch by means of a deep learning device so as to determine at least one analysis tooth zone and at least one tooth attribute value. For each analysis tooth zone determined in the preceding step, search, in the historical library, for a historical tooth model exhibiting a maximal proximity with the analysis image. Arrangement of all of the optimal tooth models so as to create an assembled model which exhibits a maximal proximity. Some optionally steps are possible.

Abstract: Method for preparing a composed response from a value for at least one dental attribute relating to the dental situation of a patient. The method includes: (d) selection by a composition computer of at least one relevant standard response from a base or standard responses and as a function of the value of the at least one dental attribute; (e) composition of a composed response by the composition computer on the basis of the at least one relevant standard response; (f) optionally, validation and/or modification of the composed response by a controller; (g) presentation of the optionally validated and/or modified composed response. The selection in (d) and the composition in (e) are determined according to composition rules of a composition protocol. Before (e), the composition protocol is selected in a protocol models base and/or is created by selecting a protocol model in a protocol models base and then modifying.

Abstract: A method for assessing the shape of an orthodontic aligner. Acquisition of at least one analysis image at least partially representing the aligner in a service position in which it is worn by a patient. Analysis of the analysis image by means of a deep learning device, trained by means of a learning base, so as to determine a value. For at least one tooth attribute of an analysis tooth zone representing, at least partially, a tooth on the analysis image, the tooth attribute relating to a separation between the tooth represented by the analysis tooth zone, and the aligner represented on the analysis image. For an image attribute of the analysis image, the image attribute relating to a separation between at least one tooth represented on the analysis image, and the aligner represented on the analysis image.

Abstract: A method for analyzing a real dental situation of a patient. The method includes steps, as follows, in succession. At an updated instant, acquisition of an updated image representing a real dental scene as observed by an operator. Simulation, for a simulation instant, of the real dental scene represented on the updated image, then determination of a virtual dental scene as a function of the simulation. Presentation of the virtual dental scene in transparent mode and overlaid on the real dental scene, or display of the updated image on a screen and presentation of the virtual dental scene overlaid with the representation of the real dental scene on the updated image displayed on the screen, in transparent mode or not on the representation.