FR3135891A1 - METHOD FOR ACQUIRING A MODEL OF A DENTAL ARCH - Google Patents

Abstract

Method for acquiring at least one image of at least one dental arch of a user (U) by means of a mobile telephone (12') and an acquisition tool (31') comprising a head acquisition head (32') provided with a camera (33'), method in which the acquisition head: - acquires said image and transmits it to the mobile phone, or - acquires a signal and transfers it to the mobile phone so that said mobile phone generates the image from said signal, independently or with the help of a computer with which said mobile phone is in communication, the method comprising, after said acquisition, an analysis of said image in order to define the situation dental health of the user and/or to check the proper progress of active or passive orthodontic treatment in progress. Abstract Figure: Figure 12

Description

METHOD FOR ACQUIRING A MODEL OF A DENTAL ARCH

The present invention relates to a method for acquiring a model of a user's dental arch and a computer program for implementing this method.

State of the art

It is advisable for everyone to have their teeth checked regularly, in particular to check that the position and/or shape and/or appearance (or “texture”) of their teeth is not changing unfavorably.

During orthodontic treatment, this unfavorable development may lead to a modification of the treatment. After orthodontic treatment, this unfavorable development, called “recurrence”, can lead to a resumption of treatment. Finally, more generally and independently of any treatment, everyone may wish to monitor possible movements and/or changes in the shape and/or appearance of their teeth.

Classically, checks are carried out by an orthodontist or a dentist who alone has suitable equipment. These checks are therefore expensive. In addition, visits are binding. Finally, the professional scanners available are precise, but require special skill. They are conventionally used on the patient, for intraoral acquisition, or on a cast of the patient's arches, for extraoral acquisition.

Furthermore, US 15/522,520 describes a method which allows, from a simple photograph of the teeth taken by the user at an updated instant, to accurately evaluate the movement and/or deformation of the teeth since an initial instant. . For this purpose, a digital three-dimensional model of a dental arch of the user is produced at the initial moment, preferably with a professional scanner. This initial model is then cut to define a tooth model for each tooth. Finally, the tooth models are moved in order to transform the initial model of the dental arch so that it matches the photograph as closely as possible. This process makes it possible to obtain a model representing the arch at the moment updated with excellent precision, without the user having to travel to scan their teeth. This model can then be compared to the initial model to control the positioning and/or shape of the user's teeth.

This process is convenient for the user, but requires at least one appointment to acquire the initial arch model. It then requires heavy computer processing to cut out the initial model and then deform it.

There is therefore a need for a method allowing monitoring of the dental situation of a user remotely, as described in US 15/522,520, but which is even more practical for the user and quicker to implement.

An objective of the present invention is to respond, at least partially, to this problem.

The invention provides a method for acquiring a model of at least one dental arch of a user, said method comprising the following steps:
a) at an updated instant, acquisition, preferably extraoral, with a portable scanner, by the user, of a digital three-dimensional model of said arch, or "acquired model", and optionally cutting the model of the arch in such a manner to isolate a part of the arch model, preferably a tooth model,
so as to obtain an “updated model”, the updated model thus being able to be the acquired model or the part of the acquired model isolated by cutting, the object represented by the updated model being called “updated object”.

As will be seen in more detail in the remainder of the description, the inventors have discovered that it is possible to use a portable scanner to produce, preferably extraorally and without particular precautions, a model of an arch or 'a tooth of sufficient quality to be used in orthodontics. Such a process seemed incompatible with the acquisition of a sufficiently complete and precise model.

Advantageously, the acquisition can be carried out by the user himself, which opens up a wide field of applications. In particular, the acquisition no longer requires a trip to a dental professional. In addition, a method according to the invention allows an analysis of the dental situation of the user more quickly than according to the methods of the prior art. Notably, no construction of an arcade model from photos is required.

Generally speaking, 3D models of dental arches are classically acquired intra-orally, with a 3D optical scanner, an intra-oral acquisition allowing the sensor to be very close to the arch, and therefore to provide information high precision.

Extraoral (or “extraoral”) acquisition devices, that is to say in which the acquisition sensor, in particular the sensor of a camera or a camera, is not introduced into the mouth of the user, are recent and use photos to distort an initial model obtained with a conventional 3D optical scanner. The computer processing necessary for this deformation is expensive.

It is the merit of the inventors to have tested a portable scanner, preferably extraoral, in particular a laser remote detector, and to have discovered that such a scanner allows the patient to acquire a model of their arches themselves. good quality dental products. Advantageously, no initial model, for example acquired at the start of orthodontic treatment, needs to be acquired and then deformed from the images acquired by the scanner. The processing of the images acquired by the scanner makes it possible, following the techniques conventionally used for 3D optical scanners, to directly obtain a model of the dental arch.

In an advantageous embodiment, the portable scanner has low precision. It is enough to note the spatial position of a few remarkable points of the arcade to constitute an updated model. Advantageously, the acquisition of an imprecise model is possible with limited and portable technical means. An imprecise model also requires little memory to store. It can easily and quickly be transmitted remotely, for example by radio waves.

Preferably the portable scanner
- is integrated into a mobile phone for so-called extraoral acquisition, or
- comprises a mobile telephone and an acquisition tool comprising an acquisition head capable of being introduced into the mouth of the user, which
- acquires the acquired model, preferably by means of a laser remote detector, and transmits it to the mobile phone, or
- acquires a signal and transfers it to the mobile phone so that said mobile phone generates the model acquired from said signal, independently or with the help of a computer with which said mobile phone is in communication.

Preferably, the mobile phone transmits the acquired model and/or the updated model to a dental professional, preferably over the air, preferably at a distance greater than 100 m, or greater than 1 km, or greater than 10 km and/or less than 50,000 km from the user.

• à l’étape a), on traite informatiquement le modèle actualisé pour le corriger, la correction pouvant comporter une modification du modèle actualisé ou un remplacement du modèle actualisé par un modèle de correction ;
• à l’étape a), on compare le modèle actualisé avec un modèle de correction de manière à obtenir une mesure d’une différence de forme entre le modèle actualisé et le modèle de correction, puis
  - on modifie le modèle actualisé de manière à réduire ladite différence de forme, de préférence de manière à minimiser ladite différence de forme, de préférence au moyen d’une méthode métaheuristique, en particulier choisie parmi les méthodes listées ci-dessous, de préférence par recuit simulé, ou
  - en fonction de ladite mesure, on laisse le module actualisé inchangé ou remplace le modèle actualisé par le modèle de correction ;
• à l’étape a), on soumet le modèle actualisé à un réseau de neurones entrainé pour rendre plus réaliste un modèle tridimensionnel numérique qu’on lui présente en entrée ;
• l’objet actualisé est ladite arcade de l'utilisateur ou une dent de ladite arcade ;
• le modèle de correction est un modèle
  - obtenu, à un instant différent de l’instant actualisé, par un scan dudit objet actualisé, ou
  - représentant ledit objet actualisé avec une forme théorique, de préférence résultant d’une simulation, ou
  - un modèle d’un objet représentatif d’un ensemble d’individus, ledit objet étant du même type que l’objet actualisé, de préférence une arcade ou une dent, par exemple un typodont ou une dent issue d’un typodont ;
• le modèle de correction est :
  - un modèle de l’objet actualisé obtenu par un scan, de préférence avec le scanner portable ou avec un scanner professionnel, de préférence à un instant antérieur de plus de 2 semaines, 4 semaines, 6 semaines, 2 mois, 3 mois et/ou de moins de 12 mois, ou de moins de 6 mois à l’instant actualisé, ou
  - un modèle de l’objet actualisé, qui simule la forme dudit objet actualisé telle qu’anticipée pour l’instant actualisé et qui, de préférence, a été réalisé à un instant antérieur de plus de 2 semaines, 4 semaines, 6 semaines, 2 mois, 3 mois et/ou de moins de 6 mois à l’instant actualisé, ou
  - un modèle de l’objet actualisé, qui simule la forme dudit objet actualisé telle qu’anticipée pour un instant « de correction », postérieur ou antérieur à l’instant actualisé, l’intervalle temporel entre les instants actualisé et de correction étant de préférence supérieur à une semaine, de préférence supérieur à 2 semaines, à 4 semaines, à 6 semaines, à 2 mois et/ou inférieur à 6 mois,
  ledit modèle ayant de préférence été réalisé plus de 2 semaines, plus de 4 semaines, plus de 6 semaines, plus de 2 mois ou plus de 3 mois avant l’instant actualisé, ou
  - un modèle historique choisi dans une bibliothèque historique comportant plus de 1 000 modèles historiques représentant des objets du même type que le modèle actualisé, ledit choix étant de préférence guidé de manière que le modèle historique choisi soit le modèle historique présentant la plus grande proximité de forme avec le modèle actualisé, ou
  - un modèle obtenu par traitement statistique des modèles historiques de ladite bibliothèque historique, de préférence de manière que le modèle obtenu par traitement statistique soit représentatif d’une population d’individus ;
• la bibliothèque historique ne comporte que des modèles historiques respectant le même critère de classification que le modèle actualisé, par exemple relatifs à des individus présentant au moins une caractéristique commune avec l'utilisateur, par exemple le même âge et/ou le même sexe et/ou la même pathologie et/ou suivant le même traitement orthodontique ou un traitement orthodontique similaire ;
• à l’étape a), on corrige le modèle actualisé en entrant le modèle actualisé à l’entrée d’un réseau de neurones entrainé pour corriger des modèles, de préférence choisi parmi les réseaux de neurones listés dans la description détaillée de l’étape iv) ci-dessous ; et/ou
• à l’étape a), on corrige le modèle actualisé en suivant les étapes suivantes :
  i) création d’une bibliothèque historique comportant plus de 1 000, de préférence plus de 5 000, de préférence plus de 10 000 modèles historiques, chaque modèle historique modélisant un objet du même type que l’objet actualisé, par exemple modélisant une arcade ou une dent si le modèle actualisé modélise une arcade ou une dent, respectivement, et
  attribution à chaque modèle historique, d’une valeur pour un critère de classification ;
  ii) analyse du modèle actualisé, de manière à déterminer la valeur dudit critère de classification pour l’objet actualisé ;
  iii) recherche, dans la bibliothèque historique, d’un modèle historique ayant la même valeur pour ledit critère de classification et présentant une proximité maximale avec ledit modèle actualisé, ou « modèle optimal » ;
  iv) modification du modèle actualisé à partir d’informations relatives au modèle optimal, la modification pouvant comporter un remplacement du modèle actualisé par le modèle optimal ;
• à l’étape a), on procède à un découpage du modèle acquis de manière à définir une pluralité de modèles de dents, puis pour chaque modèle de dent considéré comme modèle actualisé, on réalise un cycle d’étapes i) à iv) dans lequel le modèle optimal déterminé à l’étape iv) est disposé de manière à remplacer, dans le modèle acquis, ledit modèle de dent, ce qui, avantageusement permet de reconstituer un modèle d’arcade de haute précision à partir d’un modèle acquis de faible précision ;
• à l’étape a), on corrige le modèle actualisé en suivant les étapes suivantes :
  i’) définition de :
  - une première zone certaine constituée des points du modèle actualisé représentant un partie du patient, par exemple une dent, avec une précision supérieure à 90%, de préférence supérieure à 95%, de préférence supérieure à 99% ou « premiers points certains », et
  - une première zone incertaine, constituant le complément à 100% du modèle actualisé ;
  ii’) extrapolation de la première zone certaine, à partir de la seule première zone certaine, pour définir, dans la région de la première zone incertaine, une première zone reconstituée, puis
  définition de :
  - une deuxième zone certaine constituée des points de la première zone incertaine écartés de la première zone reconstituée d’une distance inférieure à une distance de seuil, ou « deuxièmes points certains » ; et
  - une deuxième zone incertaine, constituant le complément à 100% de la première zone incertaine ;
  iii’) extrapolation de l’ensemble constituée des première et deuxième zones certaines, à partir du seul ensemble, pour définir, dans la région de la deuxième zone incertaine, une deuxième zone reconstituée, puis
  remplacement de la deuxième zone incertaine par la deuxième zone reconstituée, de manière à obtenir un modèle actualisé nettoyé ;
• à l’étape a), on corrige le modèle actualisé en soumettant le modèle actualisé à un réseau de neurones entrainé en lui fournissant en entrée des modèles bruts d’objets du même type que l’objet actualisé, et en sortie lesdits modèles bruts rendus hyperréalistes ;
• à l’étape a), on traite informatiquement le modèle actualisé pour le simplifier ;
• le scanner portable est intégré dans un téléphone portable ou comporte un téléphone portable et un outil d’acquisition comportant une tête d’acquisition apte à être introduite dans la bouche de l'utilisateur, l’outil d’acquisition étant en communication avec le téléphone portable pour transmettre le modèle acquis ou le modèle actualisé ;
• la tête d’acquisition est connectée au téléphone portable, de préférence en Bluetooth® ou par câble ;
• le téléphone portable est utilisé pour transmettre, par voie hertzienne, le modèle acquis ou le modèle actualisé, de préférence à un professionnel de soins dentaires, et en particulier à un orthodontiste, et/ou à un centre de traitement informatique, de préférence pour la mise en œuvre des étapes b) et/ou c) ;
• le scanner portable est un télédétecteur par laser, en anglais lidar, pour « light detection and ranging » ;
• à l’étape a), le scanner portable projette une lumière structurée directement sur les dents du patient et acquiert des images différentes de photos;
• à l’étape a), l'utilisateur modifie l’angulation du scanner portable, de préférence en déplaçant le scanner portable par rapport aux dents du patient, de préférence horizontalement et/ou verticalement, de préférence bouche ouverte et bouche fermée ;
• à l’étape a), l'utilisateur écarte ses lèvres et/ou ses joues pour rendre ses dents visibles du scanner portable, puis acquiert le modèle acquis, de préférence de manière extra-orale, c'est-à-dire sans faire pénétrer, même partiellement, le scanner portable dans sa bouche ;
• de préférence, l'utilisateur met en œuvre un écarteur et/ou un support de scanner portable pour améliorer la qualité du modèle acquis ;
• à l’étape a), le scanner portable est immobilisé sur un support comportant un rebord, le rebord étant inséré entre les lèvres et les dents de l'utilisateur ;
• le support comporte un espaceur tubulaire qui définit une ouverture orale, ledit rebord s’étendant à la périphérie de l’ouverture orale ;
• à l’étape a), l'utilisateur modifie l’angulation du scanner portable, de préférence en déplaçant le support par rapport aux dents du patient, de préférence horizontalement et/ou verticalement, de préférence bouche ouverte et bouche fermée, en maintenant le rebord du support entre les dents de l'utilisateur et les lèvres de l'utilisateur ;
• à l’étape a), le modèle acquis avec le scanner portable est découpé de manière à définir une pluralité de modèles de dents, puis on corrige et/ou on simplifie successivement chacun desdits modèles de dent, de préférence comme décrit ci-dessus ;
• le procédé comporte, après l’étape a), l’étape suivante :
  b) détermination d’au moins une valeur d’un paramètre dimensionnel du modèle actualisé, ou « valeur dimensionnelle », et/ou d’un paramètre d’aspect du modèle actualisé, ou « valeur d’aspect » ;
• à l’étape b), on définit plus de deux valeurs dimensionnelles, de préférence suffisamment de valeurs dimensionnelles pour définir une position dans l’espace d’au moins un point du modèle actualisé, de préférence de plus de 10, plus de 100, plus de 500 points du modèle actualisé ;
• le paramètre dimensionnel est choisi parmi
  - une dimension du modèle actualisé ;
  - une distance d’un point remarquable du modèle actualisé par rapport à un référentiel, de préférence fixe par rapport au modèle actualisé, de préférence un modèle de référence disposé, comme le modèle actualisé, dans une configuration normalisée, et
  - un paramètre dérivé d’une ou plusieurs dimensions du modèle actualisé et/ou d’une ou plusieurs distances d’un point ou plusieurs points remarquables du modèle actualisé par rapport au dit référentiel ;
• le paramètre d’aspect est choisi parmi une couleur, une réflectance, une transparence, une réflectivité, une teinte, une translucidité, une opalescence, un indice sur la présence de tartre, d’une plaque dentaire ou de nourriture sur la dent ;
• pour déterminer une dite valeur dimensionnelle, on mesure une distance entre un point du modèle actualisé et un modèle de référence disposé, comme le modèle actualisé, dans une configuration normalisée ;
• le modèle de référence est de préférence
  - un modèle de l’objet actualisé obtenu par un scan, de préférence avec le scanner portable ou avec un scanner professionnel, de préférence à un instant antérieur de plus de 2 semaines, 4 semaines, 6 semaines, 2 mois, 3 mois et/ou de moins de 6 mois à l’instant actualisé, ou
  - un modèle de l’objet actualisé, qui simule la forme dudit objet telle qu’anticipée pour l’instant actualisé et qui, de préférence, a été réalisé à un instant antérieur de plus de 2 semaines, 4 semaines, 6 semaines, 2 mois, 3 mois et/ou de moins de 6 mois à l’instant actualisé, ou
  - un modèle de l’objet actualisé, qui simule la forme dudit objet telle qu’anticipée pour un instant de référence, postérieur ou antérieur à l’instant actualisé, l’intervalle temporel entre les instants actualisé et de référence étant de préférence supérieur à une semaine, de préférence supérieur à 2 semaines, à 4 semaines, à 6 semaines, à 2 mois et/ou inférieur à 6 mois,
  ledit modèle ayant de préférence été réalisé plus de 2 semaines, plus de 4 semaines, plus de 6 semaines, plus de 2 mois ou plus de 3 mois avant l’instant actualisé, ou
  - un modèle historique choisi dans une bibliothèque historique comportant plus de 1 000, de préférence plus de 10 000, de préférence plus de 100 000 modèles historiques représentant des objets du même type que l’objet actualisé, ledit choix étant de préférence guidé de manière que le modèle historique choisi soit le modèle historique présentant la plus grande proximité de forme avec le modèle actualisé, ou
  - un modèle obtenu par traitement statistique des modèles historiques de ladite bibliothèque historique, de préférence de manière que le modèle obtenu par traitement statistique soit représentatif d’une population d’individus ;
• le procédé comporte, après l’étape b) l’étape suivante :
  c) utilisation de la valeur dimensionnelle et/ou la valeur d’aspect pour :
  - détecter ou évaluer une position ou d’une forme d’une dent et/ou une évolution d’une position ou d’une forme d’une dent et/ou une vitesse d’évolution d’une position ou d’une forme d’une dent, et/ou
  - détecter ou évaluer une position ou une forme d’un appareil orthodontique et/ou une évolution d’une position ou d’une forme d’un appareil orthodontique et/ou une vitesse d’évolution d’une position ou d’une forme d’un appareil orthodontique, et/ou
  - mesurer une évolution de la forme de la denture du patient entre deux dates, et/ou
  - en dentisterie ;
• à l’étape c), on utilise la valeur dimensionnelle et/ou la valeur d’aspect pour
  - détecter ou évaluer une position ou une forme d’une tâche ou d’une carie :
  - suivre l’éruption d’une dent, et/ou
  - détecter une récidive ou une position anormale d’une dent, et/ou
  - détecter une abrasion d’une dent, et/ou
  - suivre l’ouverture ou la fermeture d’au moins un espace entre deux dents, et/ou
  - contrôler la stabilité ou la modification de l’occlusion,
  - suivre le déplacement d’une dent vers un positionnement prédéterminé, et/ou
  - détecter ou évaluer un décollement d’une bague ou d’une gouttière orthodontique,
  - optimiser la date de prise de rendez-vous chez un professionnel de soins dentaires, et/ou
  - évaluer un indice orthodontique, en particulier choisi parmi les indices orthodontiques listés dans la définition d’un indice orthodontique ci-dessous,
  de préférence un indice orthodontique indiquant si
  - l’utilisateur a atteint une classe d’occlusion n°I pour les canines, et/ou
  - l’utilisateur a atteint une classe d’occlusion n°I pour les molaires, et/ou
  - les espaces antérieurs du patient sont fermés, et/ou
  - tous les espaces résultant de l’extraction d’une dent sont fermés, et/ou
  - l’utilisateur a un surplomb horizontal , ou « overjet » en anglais, normal, de préférence compris entre 1 et 3 mm, et/ou
  - l’utilisateur a un surplomb vertical, ou « overbite » en anglais, normal, de préférence compris entre 1 et 3 mm, et/ou
  - les lignes médianes des arcades inférieure et supérieure sont décalées, et/ou
  - l’utilisateur ne présente pas de décalage latéral de l’arcade supérieure par rapport à l’arcade inférieure, et/ou
  - lors des deux derniers contrôles, aucun mouvement d’une dent n’a été détecté, et/ou
  - toutes les dent temporaires sont tombées,
  ou un indice orthodontique évaluant quantitativement et/ou évaluant l’évolution temporelle de :
  - la classe d’occlusion pour les canines, et/ou
  - la classe d’occlusion pour les molaires, et/ou
  - les espaces antérieurs du patient, et/ou
  - les espaces résultant de l’extraction d’une dent, et/ou
  - le surplomb horizontal, et/ou
  - le surplomb vertical, et/ou
  - le décalage entre les lignes médianes des arcades inférieure et supérieure, et/ou
  - le décalage latéral de l’arcade supérieure par rapport à l’arcade inférieure, et/ou
  - le mouvement d’une dent lors des deux derniers contrôles, et/ou
  - évaluer l’efficacité d’un traitement orthodontique actif, et/ou
  - mesurer l’activité d’un appareil orthodontique actif ; et/ou
  - mesurer une perte d’efficacité d’un appareil orthodontique passif ; et/ou
  - comparer le positionnement de dents de l'utilisateur, à l’instant actualisé, avec celui desdites dents telles que représentées un modèle théorique cible, de préférence un modèle intermédiaire représentant lesdites dents dans une position anticipée, selon un plan de traitement, pour une étape finale ou pour une étape intermédiaire du traitement orthodontique, en anglais « set-up » intermédiaire ; et/ou
  - évaluer la nécessité de corriger ou d’adapter le traitement orthodontique, par exemple en concevant et en fabriquant une nouvelle série de gouttières orthodontiques dans le cadre d’un traitement orthodontique avec des gouttières orthodontiques, ou en changeant de type de traitement orthodontique, par exemple pour passer d’un traitement avec arcs et attache (« brackets » en anglais) à un traitement avec des gouttières orthodontiques, ou inversement) ; et/ou
  - mesurer une évolution de la forme de la denture du patient entre deux dates séparées par l’occurrence d’un choc sur les dents ou par la mise en œuvre d’un dispositif dentaire destiné au traitement de l’apnée du sommeil, ou par l’occurrence d’une greffe dans la bouche du patient ;
• à l’étape a), le modèle acquis avec le téléphone portable est découpé de manière à définir une pluralité de modèles de dents, puis on réalise une dite étape b) pour définir au moins une valeur dimensionnelle pour chaque modèle de dent, défini comme le modèle actualisé pour ladite étape b) ;
• à l’étape a), l'utilisateur acquiert, de préférence avec un même téléphone portable, ledit modèle acquis et une ou plusieurs images actualisées, de préférence des photos en couleurs, de préférence en couleurs réalistes, et
  à l’étape b), on détermine une information relative à une dimension et/ou à l’aspect d’un ou plusieurs objets, de préférence des dents, représentés sur la ou les images actualisées, puis on utilise ladite information pour compléter et/ou corriger ladite valeur dimensionnelle et/ou ladite valeur d’aspect déterminés à partir du modèle actualisé ;
• à l’étape a), le modèle acquis comporte moins de 500 points.

An analysis method according to the invention may also include one or more of the following optional characteristics:

• in step a), the updated model is computer processed to correct it, the correction possibly including a modification of the updated model or a replacement of the updated model by a correction model;
• in step a), the updated model is compared with a correction model so as to obtain a measurement of a difference in shape between the updated model and the correction model, then
  - the updated model is modified so as to reduce said difference in shape, preferably so as to minimize said difference in shape, preferably by means of a metaheuristic method, in particular chosen from the methods listed below, preferably by simulated annealing, or
  - depending on said measurement, we leave the updated module unchanged or replace the updated model with the correction model;
• in step a), the updated model is submitted to a neural network trained to make a digital three-dimensional model presented to it as input more realistic;
• the updated object is said arch of the user or a tooth of said arch;
• the correction model is a model
  - obtained, at a time different from the updated time, by a scan of said updated object, or
  - representing said updated object with a theoretical form, preferably resulting from a simulation, or
  - a model of an object representative of a set of individuals, said object being of the same type as the updated object, preferably an arch or a tooth, for example a typodont or a tooth from a typodont;
• the correction model is:
  - an updated model of the object obtained by a scan, preferably with the portable scanner or with a professional scanner, preferably at an earlier time of more than 2 weeks, 4 weeks, 6 weeks, 2 months, 3 months and/or or less than 12 months, or less than 6 months at the updated time, or
  - a model of the updated object, which simulates the shape of said updated object as anticipated for the updated moment and which, preferably, was produced at an earlier time of more than 2 weeks, 4 weeks, 6 weeks, 2 months, 3 months and/or less than 6 months at the updated moment, or
  - a model of the updated object, which simulates the shape of said updated object as anticipated for a “correction” instant, subsequent to or prior to the updated instant, the temporal interval between the updated and correction instants being preferably greater than one week, preferably greater than 2 weeks, 4 weeks, 6 weeks, 2 months and/or less than 6 months,
  said model having preferably been produced more than 2 weeks, more than 4 weeks, more than 6 weeks, more than 2 months or more than 3 months before the updated moment, or
  - a historical model chosen from a historical library comprising more than 1,000 historical models representing objects of the same type as the updated model, said choice being preferably guided so that the historical model chosen is the historical model presenting the greatest proximity to form with the updated model, or
  - a model obtained by statistical processing of the historical models of said historical library, preferably so that the model obtained by statistical processing is representative of a population of individuals;
• the historical library only includes historical models respecting the same classification criterion as the updated model, for example relating to individuals presenting at least one characteristic in common with the user, for example the same age and/or the same sex and/or or the same pathology and/or following the same orthodontic treatment or similar orthodontic treatment;
• in step a), the updated model is corrected by entering the updated model at the input of a neural network trained to correct models, preferably chosen from the neural networks listed in the detailed description of the step iv) below; and or
• in step a), we correct the updated model by following the following steps:
  i) creation of a historical library comprising more than 1,000, preferably more than 5,000, preferably more than 10,000 historical models, each historical model modeling an object of the same type as the updated object, for example modeling an arcade or a tooth if the updated model models an arch or a tooth, respectively, and
  attribution to each historical model of a value for a classification criterion;
  ii) analysis of the updated model, so as to determine the value of said classification criterion for the updated object;
  iii) search, in the historical library, for a historical model having the same value for said classification criterion and presenting maximum proximity to said updated model, or “optimal model”;
  iv) modification of the updated model based on information relating to the optimal model, the modification possibly including a replacement of the updated model by the optimal model;
• in step a), the acquired model is divided so as to define a plurality of tooth models, then for each tooth model considered as an updated model, a cycle of steps i) to iv) is carried out in in which the optimal model determined in step iv) is arranged so as to replace, in the acquired model, said tooth model, which advantageously makes it possible to reconstruct a high-precision arch model from an acquired model low precision;
• in step a), we correct the updated model by following the following steps:
  i') definition of:
  - a first certain zone made up of points of the updated model representing a part of the patient, for example a tooth, with a precision greater than 90%, preferably greater than 95%, preferably greater than 99% or "first certain points", And
  - a first uncertain zone, constituting the 100% complement of the updated model;
  ii') extrapolation of the first certain zone, from the first certain zone alone, to define, in the region of the first uncertain zone, a first reconstructed zone, then
  definition of :
  - a second certain zone consisting of the points of the first uncertain zone separated from the first reconstructed zone by a distance less than a threshold distance, or “second certain points”; And
  - a second uncertain zone, constituting the 100% complement of the first uncertain zone;
  iii') extrapolation of the set consisting of the first and second certain zones, from the set alone, to define, in the region of the second uncertain zone, a second reconstituted zone, then
  replacement of the second uncertain zone by the second reconstructed zone, so as to obtain a cleaned updated model;
• in step a), the updated model is corrected by submitting the updated model to a trained neural network by providing as input raw models of objects of the same type as the updated object, and as output said rendered raw models hyperrealistic;
• in step a), the updated model is computer processed to simplify it;
• the portable scanner is integrated into a mobile telephone or comprises a mobile telephone and an acquisition tool comprising an acquisition head capable of being introduced into the mouth of the user, the acquisition tool being in communication with the telephone portable to transmit the acquired model or the updated model;
• the acquisition head is connected to the mobile phone, preferably via Bluetooth® or by cable;
• the mobile telephone is used to transmit, by air, the acquired model or the updated model, preferably to a dental care professional, and in particular to an orthodontist, and/or to a computer processing center, preferably for the implementation of steps b) and/or c);
• the portable scanner is a laser remote detector, in English lidar, for “light detection and ranging”;
• in step a), the portable scanner projects structured light directly onto the patient's teeth and acquires different photo images;
• in step a), the user modifies the angulation of the portable scanner, preferably by moving the portable scanner relative to the patient's teeth, preferably horizontally and/or vertically, preferably open mouth and closed mouth;
• in step a), the user spreads his lips and/or his cheeks to make his teeth visible to the portable scanner, then acquires the acquired model, preferably extra-orally, that is to say without doing penetrate, even partially, the portable scanner into his mouth;
• preferably, the user implements a retractor and/or a portable scanner support to improve the quality of the acquired model;
• in step a), the portable scanner is immobilized on a support having a rim, the rim being inserted between the lips and the teeth of the user;
• the support comprises a tubular spacer which defines an oral opening, said rim extending to the periphery of the oral opening;
• in step a), the user modifies the angulation of the portable scanner, preferably by moving the support relative to the patient's teeth, preferably horizontally and/or vertically, preferably with the mouth open and the mouth closed, while maintaining the edge of the support between the user's teeth and the user's lips;
• in step a), the model acquired with the portable scanner is cut so as to define a plurality of tooth models, then each of said tooth models is successively corrected and/or simplified, preferably as described above;
• the method comprises, after step a), the following step:
  b) determination of at least one value of a dimensional parameter of the updated model, or “dimensional value”, and/or of an appearance parameter of the updated model, or “appearance value”;
• in step b), more than two dimensional values are defined, preferably enough dimensional values to define a position in space of at least one point of the updated model, preferably more than 10, more than 100, more than 500 points of the updated model;
• the dimensional parameter is chosen from
  - a dimension of the updated model;
  - a distance of a remarkable point of the updated model in relation to a reference frame, preferably fixed in relation to the updated model, preferably a reference model arranged, like the updated model, in a standardized configuration, and
  - a parameter derived from one or more dimensions of the updated model and/or from one or more distances of a point or several remarkable points of the updated model relative to said reference frame;
• the appearance parameter is chosen from a color, a reflectance, a transparency, a reflectivity, a tint, a translucency, an opalescence, an index of the presence of tartar, dental plaque or food on the tooth;
• to determine a said dimensional value, a distance is measured between a point of the updated model and a reference model arranged, like the updated model, in a standardized configuration;
• the reference model is preferably
  - an updated model of the object obtained by a scan, preferably with the portable scanner or with a professional scanner, preferably at an earlier time of more than 2 weeks, 4 weeks, 6 weeks, 2 months, 3 months and/or or less than 6 months at the updated time, or
  - a model of the updated object, which simulates the shape of said object as anticipated for the updated moment and which, preferably, was produced at an earlier time of more than 2 weeks, 4 weeks, 6 weeks, 2 months, 3 months and/or less than 6 months at the updated moment, or
  - a model of the updated object, which simulates the shape of said object as anticipated for a reference instant, subsequent to or prior to the updated instant, the temporal interval between the updated and reference instants being preferably greater than one week, preferably greater than 2 weeks, 4 weeks, 6 weeks, 2 months and/or less than 6 months,
  said model having preferably been produced more than 2 weeks, more than 4 weeks, more than 6 weeks, more than 2 months or more than 3 months before the updated moment, or
  - a historical model chosen from a historical library comprising more than 1,000, preferably more than 10,000, preferably more than 100,000 historical models representing objects of the same type as the updated object, said choice preferably being guided in a manner that the historical model chosen is the historical model presenting the greatest proximity in form to the updated model, or
  - a model obtained by statistical processing of the historical models of said historical library, preferably so that the model obtained by statistical processing is representative of a population of individuals;
• the process comprises, after step b), the following step:
  c) use of the dimensional value and/or the appearance value for:
  - detect or evaluate a position or a shape of a tooth and/or an evolution of a position or a shape of a tooth and/or a speed of evolution of a position or a shape of a tooth, and/or
  - detect or evaluate a position or a shape of an orthodontic appliance and/or an evolution of a position or a shape of an orthodontic appliance and/or a speed of evolution of a position or a shape orthodontic appliance, and/or
  - measure an evolution of the shape of the patient's teeth between two dates, and/or
  - in dentistry;
• in step c), we use the dimensional value and/or the appearance value to
  - detect or evaluate a position or shape of a stain or decay:
  - follow the eruption of a tooth, and/or
  - detect a recurrence or abnormal position of a tooth, and/or
  - detect an abrasion of a tooth, and/or
  - follow the opening or closing of at least one space between two teeth, and/or
  - check the stability or modification of the occlusion,
  - follow the movement of a tooth towards a predetermined position, and/or
  - detect or evaluate a loosening of a ring or an orthodontic splint,
  - optimize the date of making an appointment with a dental care professional, and/or
  - evaluate an orthodontic index, in particular chosen from the orthodontic indices listed in the definition of an orthodontic index below,
  preferably an orthodontic index indicating whether
  - the user has reached occlusion class No. I for canines, and/or
  - the user has reached occlusion class No. I for the molars, and/or
  - the patient's anterior spaces are closed, and/or
  - all spaces resulting from the extraction of a tooth are closed, and/or
  - the user has a normal horizontal overjet, preferably between 1 and 3 mm, and/or
  - the user has a normal vertical overbite, preferably between 1 and 3 mm, and/or
  - the midlines of the lower and upper arches are offset, and/or
  - the user does not have a lateral shift of the upper arch in relation to the lower arch, and/or
  - during the last two checks, no movement of a tooth was detected, and/or
  - all the primary teeth have fallen out,
  or an orthodontic index quantitatively evaluating and/or evaluating the temporal evolution of:
  - the occlusion class for canines, and/or
  - the occlusion class for the molars, and/or
  - the patient's anterior spaces, and/or
  - spaces resulting from the extraction of a tooth, and/or
  - the horizontal overhang, and/or
  - the vertical overhang, and/or
  - the offset between the midlines of the lower and upper arches, and/or
  - the lateral offset of the upper arch relative to the lower arch, and/or
  - the movement of a tooth during the last two checks, and/or
  - evaluate the effectiveness of active orthodontic treatment, and/or
  - measure the activity of an active orthodontic appliance; and or
  - measure a loss of effectiveness of a passive orthodontic appliance; and or
  - compare the positioning of the user's teeth, at the updated instant, with that of said teeth as represented in a target theoretical model, preferably an intermediate model representing said teeth in an anticipated position, according to a treatment plan, for a final stage or for an intermediate stage of orthodontic treatment, in English “intermediate set-up”; and or
  - assess the need to correct or adapt orthodontic treatment, for example by designing and manufacturing a new series of orthodontic aligners as part of orthodontic treatment with orthodontic aligners, or by changing the type of orthodontic treatment, for example example to move from treatment with archwires and brackets to treatment with orthodontic aligners, or vice versa); and or
  - measure an evolution of the shape of the patient's teeth between two dates separated by the occurrence of an impact on the teeth or by the implementation of a dental device intended for the treatment of sleep apnea, or by the occurrence of a graft in the patient's mouth;
• in step a), the model acquired with the mobile phone is cut so as to define a plurality of tooth models, then said step b) is carried out to define at least one dimensional value for each tooth model, defined as the updated model for said step b);
• in step a), the user acquires, preferably with the same mobile phone, said acquired model and one or more updated images, preferably color photos, preferably in realistic colors, and
  in step b), information relating to a dimension and/or the appearance of one or more objects, preferably teeth, represented on the updated image(s) is determined, then said information is used to complete and /or correct said dimensional value and/or said aspect value determined from the updated model;
• in step a), the acquired model has less than 500 points.

• un programme d’ordinateur, et en particulier un applicatif spécialisé pour téléphone portable, comprenant des instructions de code de programme pour l'exécution de l’étape a), et de préférence de l’étape b), et de préférence de l’étape c), lorsque ledit programme est exécuté par un ordinateur,
• un support informatique sur lequel est enregistré un tel programme, par exemple une mémoire ou un CD-ROM, et
• un scanner portable, en particulier incorporé dans un téléphone portable, dans lequel est chargé un tel programme.

The invention also relates to:

• a computer program, and in particular a specialized application for a mobile telephone, comprising program code instructions for the execution of step a), and preferably step b), and preferably of step c), when said program is executed by a computer,
• a computer medium on which such a program is recorded, for example a memory or a CD-ROM, and
• a portable scanner, in particular incorporated into a mobile telephone, into which such a program is loaded.

The invention thus relates to a portable scanner, preferably integrated into a mobile telephone, capable of implementing the acquisition in step a), and preferably one or more of the correction and/or simplification methods described in the present description, and preferably step b), and more preferably step c).

Definitions

By “user” is meant any person for whom a method according to the invention is implemented, whether this person is sick or not, is undergoing orthodontic treatment or not.

“Dental care professional” means any person qualified to provide dental care, which includes in particular an orthodontist and a dentist.

“Orthodontic treatment” is all or part of a treatment intended to modify the shape of a dental arch (active orthodontic treatment) or to maintain the shape of a dental arch, in particular after the end of active orthodontic treatment (passive orthodontic treatment).

Orthodontic indices are indices which allow, in a synthetic manner, to evaluate the shape and/or the evolution of the shape of the dental arches. They can be specific to one arch or to both arches (“inter-arch” indices). As examples, we can cite:
vertical overjet, horizontal overjet, crowding, in particular the Nance index, deviation of the inter-incisal media, classes of canine and/or molar occlusions, an index of irregularity, in particular the index of Little, the anterior open bite, the lateral open bite, the posterior lingual inverted bite, the posterior buccal inverted bite, an ideal arch length, the presence or absence of inter-dental space, an index of leveling of the Spee curve, the presence of a significant rotation, for example greater than 10°, on certain teeth,
as well as the combinations of these indices and their evolution. Examples of orthodontic indices are those used to define the American Board of Orthodontics' ABO Discrepancy Index.

An “orthodontic appliance” is an appliance worn or intended to be worn by a user. An orthodontic appliance can be intended for therapeutic or prophylactic treatment, but also for aesthetic treatment. An orthodontic appliance may in particular be an arch and bracket appliance, or an orthodontic splint, or an auxiliary appliance of the Carrière Motion type.

By “arch” or “dental arch”, we mean all or part of a dental arch.

By "image" we mean a two-dimensional digital representation, such as a photograph or an image taken from a film. An image is made up of pixels.

By “model” we mean a digital three-dimensional model. A model is made up of a set of voxels. It classically comprises a mesh made up of points connected by line segments, that is to say an assembly of triangles.

A “tooth model” is a three-dimensional digital model of a tooth. A model of a dental arch can be cut so as to define, for at least a portion of the teeth, preferably for all the teeth represented in the model of the arch, tooth models. The tooth models are therefore models within the arch model.

An “arch model” is a model representing at least part of a dental arch, preferably at least 2, preferably at least 3, preferably at least 4 teeth.

A model, in particular a model of an arch or a tooth, is “hyperrealistic” when the person observing it has the impression of observing the modeled object itself. In particular, the colors of the model are those of the modeled object.

By “raw” model we mean a model resulting from a scan and possibly corrected according to the invention, but whose color has not been modified to make it hyperrealistic.

The “type” of a modeled object, and in particular of the updated object, defines the nature of this object. The object may in particular be of the “tooth” or “arch” or “gum” type. The object can also be a subgroup of teeth, for example the group of incisors or the group of teeth bearing one or more tooth numbers, or a subgroup of arch, for example the upper arch.

A “classification criterion” is an attribute of a modeled object, in particular an arch or a tooth, which allows it to be classified. For example, the classification criterion may be an occlusion class, a range for a dimension (e.g. height, width, concavity, inter-canine distance, inter-premolar width, inter-molar width, arch length or deflection , arch perimeter) of the modeled object, the age, sex, pathology, or orthodontic treatment of the person who owns the modeled object, an orthodontic index, in particular chosen from the orthodontic indices listed below above, or a combination of these criteria.

The use of a classification criterion makes it possible in particular to select modeled objects which have similar or identical characteristics. Advantageously, it makes it possible to constitute a learning base well suited to the object that a neural network is intended to process. For example, if a neural network is intended to correct tooth models representing teeth number 14, it is preferable to train it with a learning base that only includes recordings relating to teeth number 14. The tooth number is then a classification criterion.

A “standardized configuration” is a positioning of a model, in space, following a predetermined orientation, with a predetermined scale. To compare the shape of two models representing an object, for example an arch or a tooth, the two models can be arranged according to the standardized configuration. Standardization methods for arranging and sizing a model according to a standardized configuration are well known. To compare the shape of two models, we can in particular use an iterative closest point search algorithm (ICP, or “Iterative Closest Point” in English, described in https://fr.wikipedia.org/wiki/Iterative_Closest_Point ).

The “cutting” of an arch model into “tooth models” is an operation making it possible to delimit and make autonomous the representations of the teeth (tooth models) in the arch model. There are computer tools for manipulating the tooth models of an arch model. An example of software for manipulating tooth models and creating a treatment scenario is the Treat program, described at https://en.wikipedia.org/wiki/Clear_aligners#cite_note-invisalignsystem-10 .

A “statistical processing” is a processing which, applied to a set of data, makes it possible to determine characteristics specific to this set, for example an average, a standard deviation, or a median value. Statistical processing tools are well known to those skilled in the art.

“Metaheuristic” methods are known optimization methods. In the context of the present invention, they are preferably chosen from the group formed by:
- evolutionary algorithms, preferably chosen from evolution strategies, genetic algorithms, differential evolution algorithms, distribution estimation algorithms, artificial immune systems, Shuffled Complex Evolution path recomposition, simulated annealing, ant colony algorithms, particle swarm optimization algorithms, taboo search, and the GRASP method;
- the kangaroo algorithm,
- the Fletcher and Powell method,
- the sound method,
- stochastic tunneling,
- climbing hills with random starts,
- the cross-entropy method, and
- hybrid methods between the metaheuristic methods cited above.

We call “concordance” or “proximity” (“match” or “fit” in English) between two objects a measure of the difference, or “distance”, between these two objects. A match is maximal (“best fit”) when this difference is minimal.

A “neural network” or “artificial neural network” is a set of algorithms well known to those skilled in the art. To be operational, a neural network must be trained by a learning process called “deep learning”, from a learning base.

A “learning base” is a base of computer records suitable for training a neural network. The quality of the analysis carried out by the neural network depends directly on the number of recordings in the learning base. Conventionally, the learning base contains more than 1,000, preferably more than 10,000 records.

The training of a neural network is adapted to the aim pursued and does not pose any particular difficulty to those skilled in the art. Training a neural network consists of confronting it with a learning base containing information on first objects and second objects that the neural network must learn to “correspond”, that is to say to connect one to the other.

Training can be done from a “paired” or “with pairs” learning base, made up of “pair” recordings, that is to say each comprising a first object for the input of the neural network, and a second corresponding object, for the output of the neural network. We also say that the input and output of the neural network are “paired”. Training the neural network with all these pairs teaches it to provide, from an object similar to the first objects, a corresponding object similar to the second objects.

The article “Image-to-Image Translation with Conditional Adversarial Networks ” by Phillip Isola Jun-Yan Zhu, Tinghui Zhou, Alexei A. Efros, Berkeley AI Research (BAIR) Laboratory, UC Berkeley, illustrates the use of a database paired learning.

The function of a “reference frame” is to serve as a basis for measuring one or more distances. A reference frame can for example be a three-dimensional reference frame, for example orthonormal. The three-dimensional reference frame is preferably fixed relative to the model considered. If the model represents an arch, it can for example have its origin in the center of the user's oral cavity. In particular, the three-dimensional marker is preferably independent of the position and orientation of the portable scanner.

The dimensions (length, width, height) of an arch are classically measured by considering that the arch is in a horizontal plane. The direction of height Y is then the vertical direction. The width direction X is the cross direction for the user, which extends from the user's right to left. The Z length direction is the depth direction for the user, which extends from the front to the back of the user.

The dimensions (length, width, height) of a tooth are classically measured considering that the arch is in a horizontal plane. The direction of height Y’ is then the vertical direction. The direction of width X’ is the direction of the largest dimension of the tooth when observed from the front, perpendicular to the direction of height. The direction of the length Z’ is the direction perpendicular to the directions Y’ and X’.

According to the international convention of the International Dental Federation, each tooth in a dental arch has a predetermined number. The tooth numbers defined by this convention are recalled on the .

A “remarkable point” is a point on an arch or tooth model that can be identified, for example the apex of the tooth or at the tip of a cusp, an interdental contact point, it is that is, a tooth with an adjacent tooth, for example a point mesial or distal to the incisal edge of a tooth, or a point at the center of the crown of the tooth, or "barycenter".

An “angulation” is an orientation of the optical axis of the portable scanner relative to the user, during acquisition of the model in step a).

A 3D scanner, or “scanner”, is a device used to obtain a model of a tooth or dental arch. It classically uses structured light and, from different images and, preferably by matching particular points on these images, manages to constitute a 3D model.

More precisely, the portable scanner projects structured light onto the patient's teeth while acquiring said images. The scanner can project a light pattern onto the teeth. The deformation of this pattern allows the spatial interpretation of the scene.

Among the techniques conventionally used, we can cite the projection of a 1-dimensional or 2-dimensional pattern, multi-band laser triangulation, in English " Multistripe laser Triangulation (MLT)", and digital fringes and the modulated phase technique. .

Alternatively or in addition to the structured light projection, the portable scanner projects modulated light onto the patient's teeth while acquiring said images. The projected light then changes and the scanner camera measures the variation of the reflected light over time in order to deduce the distance it travels. Among the techniques conventionally used, we can cite in particular the modulated phase technique.

The analysis of the images allows the construction of the model.

The images can be of the same type as images acquired by conventional intraoral 3D optical scanners.

The images are representations of the observed scene, in this case of the patient's teeth, but their nature is specific to the nature of the light source illuminating the scene. The images are preferably not photos depicting the scene realistically, as a person would directly observe it.

The maximum difference in shape between the model acquired with the scanner and the scanned object, at real scale, is inversely proportional to the performance of the scanner. It is called “acquisition resolution” or “accuracy” of the scanner. The lower the resolution, the more realistic the model is.

A laser remote detector is particularly well suited to the invention because it allows extraoral acquisition of a precise model of the arch, by the patient himself, the laser light being projected directly onto the patient's teeth.

A professional scanner preferably has a precision of less than 5/10 mm (i.e. the maximum difference in shape between the model acquired with the scanner and the real object scanned, at real scale, is less to 5/10 mm), preferably less than 3/10 mm, preferably less than 1/10 mm, preferably less than 1/50 mm, preferably less than 1/100 mm and/or greater than 1/500 mm.

An iPhone® type device is called a “mobile phone” or “mobile phone”. Such a device typically weighs less than 500 g, or less than 200 g, is equipped with a camera comprising a lens allowing it to take films or photos, or even a scanner allowing it to acquire three-dimensional digital models. . A mobile phone is also capable of exchanging data with another device more than 500 km away from the mobile phone, and is capable of displaying on a screen the films, photos or models that it has acquired.

A “retractor” or “dental retractor” is a device intended to roll up the lips. It comprises an upper rim and a lower rim, and/or a right rim and a left rim, extending around a spacer opening and intended to be introduced between the teeth and the lips. In the service position, the user's lips rest on these edges, so that the teeth are visible through the spacer opening. A retractor allows you to observe the teeth without being bothered by the lips.

The teeth, however, do not rest on the spacer, so the user can, by turning their head relative to the spacer, change which teeth are visible through the spacer opening. He can also modify the spacing between his dental arches. In particular, a spacer does not press on the teeth so as to separate the two jaws from each other, but on the lips.

In one embodiment, a retractor is configured to elastically spread the upper and lower lips apart so as to expose teeth visible through the retractor opening.

In one embodiment, a spacer is configured so that the distance between the upper edge and the lower edge, and/or between the right edge and the left edge is constant.

Spacers are for example described in PCT/EP2015/074896, US 6,923,761, or US 2004/0209225.

The “service position” is the position in which the user acquires the model acquired in step a). When using a bracket to rigidly fix the portable scanner, the bracket is partially inserted into the user's mouth, as shown in Figures 2 and 3.

The “closed mouth” position is the occlusion position in which the teeth of the patient's upper and lower arches are in contact. An “open mouth” position is a position of opening the mouth, in which the teeth of the patient's upper and lower arches are not in contact.

The method (excluding the acquisition operation with the portable scanner) according to the invention is implemented by computer, preferably exclusively by computer.

By “computer”, we mean a computer processing unit, which includes a set of several machines, having computer processing capabilities. This unit can in particular be integrated into the portable scanner, or into a mobile phone integrating the portable scanner, or be a PC type computer or a server, for example a server remote from the user, for example be the "cloud" or a computer available from a dental professional. The mobile phone and the computer then include means of communication for exchanging with each other, in particular for transmitting the updated model, optionally corrected and/or simplified, and/or one or more dimensional values determined according to the invention.

Conventionally, a computer comprises in particular a processor, a memory, a man-machine interface, conventionally comprising a screen, a communication module via the Internet, by WIFI, by Bluetooth® or by the telephone network. Software configured to implement a method of the invention is loaded into the computer's memory. The computer can also be connected to a printer.

“First”, “second” are used for clarity.

Also, for the sake of clarity:
- “basic” refers to a model used in the preferred simplification process;
- “reference” refers to a model used in step b) to evaluate a dimensional value or an aspect value, or to a time at which it is expected that the object modeled by the reference model will have the shape or the appearance of this model;
- “correction” refers to a model or instant used in a preferred correction process;
- “updated” refers to step a), and in particular to the model resulting from step a);
- “historical” refers to one or more models acquired prior to the updated moment, in particular modeling an arch or a tooth of a “historical” person different from the user;
- “optimal” refers to a model which, among a set of models, presents the form closest to the updated model.

“Vertical”, “horizontal”, “right”, “left”, “front” or “front”, “behind”, “above”, “below” refer to a user who is standing, vertically.

“Comprising” or “comprising” or “presenting” should be interpreted non-restrictively, unless otherwise indicated.

Brief description of the figures

• la représente, schématiquement, un exemple de kit selon l’invention ;
• la représente, schématiquement, le kit selon l’invention dans une position de service, l'utilisateur étant vu de face ;
• la représente, schématiquement, le kit selon l’invention dans une position de service, l'utilisateur étant vu de côté ;
• la représente un modèle acquis, avec trois résolutions d’acquisition différentes ;
• la est un exemple de modèle acquis, après un traitement pour découper des modèles de dent ; un exemple de modèle de dent est coloré en gris foncé ;
• la illustre la numérotation des dents utilisée dans le domaine dentaire ;
• la illustre un procédé d’acquisition selon l’invention ;
• la illustre un premier procédé de correction selon l’invention ;
• la illustre un deuxième procédé de correction selon l’invention ;
• la représente schématiquement un exemple de scanner portable dans un mode de réalisation de l’invention ;
• la présente différents clichés apportant des données complémentaires ;
  - la représente schématiquement un exemple de dispositif pour la mise en œuvre d’un procédé d’acquisition d’images selon l’invention.

Other characteristics and advantages of the invention will appear further on reading the detailed description which follows and on examining the appended drawing in which:

• there represents, schematically, an example of a kit according to the invention;
• there represents, schematically, the kit according to the invention in a service position, the user being seen from the front;
• there represents, schematically, the kit according to the invention in a service position, the user being seen from the side;
• there represents an acquired model, with three different acquisition resolutions;
• there is an example of a model acquired, after processing to cut out tooth models; an example tooth model is colored dark gray;
• there illustrates the numbering of teeth used in the dental field;
• there illustrates an acquisition method according to the invention;
• there illustrates a first correction method according to the invention;
• there illustrates a second correction method according to the invention;
• there schematically represents an example of a portable scanner in one embodiment of the invention;
• there presents different photos providing additional data;
  - there schematically represents an example of a device for implementing an image acquisition method according to the invention.

In the different figures, identical references are used to designate similar or identical objects.

detailed description

The objective of a process according to the invention, illustrated in the , is to quickly provide a digital three-dimensional model of an arch of the user, or part of this arch, that is to say an “updated model”.

In step a) , at an updated time, the user generates, with a portable scanner 6, the “acquired model”.

Preferably, the acquired model represents at least 2, preferably at least 3, preferably at least 4 teeth, preferably all the teeth in the arch.

A portable scanner is an autonomous scanner, in particular in that it integrates its own energy source, typically a battery, and in that its weight allows it to be handled by hand.

Preferably, the portable scanner weighs less than 1 kg, preferably less than 500 g, preferably less than 200 g, and/or more than 50 g.

Preferably, the largest dimension of the portable scanner is less than 30 cm, 20 cm or 15 cm and/or greater than 5 cm.

The portable scanner preferably has an acquisition resolution less than 10 mm, preferably less than 5 mm, preferably less than 3 mm, preferably less than 2 mm, preferably less than 1 mm, preferably less than 1/ 2 mm, preferably less than 1/5 mm, preferably less than 1/10 mm.

The portable scanner is preferably configured so that the acquired model has more than 5,000 and/or less than 200,000, or less than 150,000 points.

There shows examples of arcade models 8 acquired with a handheld scanner featuring 5000, 11,500 and 154,000 dots, respectively.

The portable scanner 6 can be integrated into a mobile phone 12, as in the , or be in communication with a cell phone. Step a) is thus easy to implement by the user. The mobile phone also allows the updated model to be transferred to a remote computer.

The updated moment may be during orthodontic treatment undergone by the user or outside of any orthodontic treatment.

In step a), the portable scanner is preferably carried by the user's hand. Preferably, it is not immobilized, for example by means of a structure resting on the ground, for example a tripod. Preferably, the user's head is not immobilized.

In one embodiment, the user scans the dental arch without using any device other than the portable scanner.

In a preferred embodiment, he uses a tool to clear his lips, and better expose the dental arch to the portable scanner. The tool can be, for example, a spoon inserted into his mouth.

In one embodiment, he uses a retractor and/or a mouth support which he inserts partially into his mouth.

Portable Scanner Stand

In a particularly advantageous embodiment, in step a), the user uses a kit 10 comprising the portable scanner 6 and a support 14 ( ) allowing simultaneously
- to spread the user's lips to release the teeth, and
- to facilitate the positioning and orientation of the portable scanner 6 in relation to the teeth.

The support 14 preferably has the general shape of a tubular body of which one opening, called the “oral opening” Oo, is intended to be introduced into the patient's mouth, and the opposite opening of which, called the “acquisition opening” , faces the objective of the portable scanner, rigidly fixed, preferably in a removable manner, on the support 14.

Preferably, the acquisition aperture also faces a flash of the portable scanner, which can be used to illuminate the user's teeth during acquisition.

The support 14 makes it possible to define a spacing between the portable scanner and the oral opening Oo as well as an orientation of the portable scanner relative to the oral opening. Advantageously, in the service position, the data acquired by the portable scanner 6 through its objective, the acquisition aperture and the oral aperture are thus acquired at a predetermined distance from the user's teeth and according to a predefined orientation . Preferably, the support is configured so that this spacing and this orientation are constant.

Preferably, the support 14 comprises:
- a tubular spacer 16 which defines the oral opening Oo and preferably comprises a rim 22 extending radially outwards, at the periphery of the oral opening Oo, intended to be introduced between the lips and the teeth of the user, and
- an adapter 18 on which the portable scanner 6 is fixed, for example clamped between two jaws 24 ₁ and 24 ₂ , as illustrated in the , the adapter 18 being rigidly fixed on the spacer 16, preferably in a removable manner, for example by means of a clip 20, or integral with the spacer, so that the objective of the portable scanner can " see » the oral opening.

The maximum height h ₂₂ of the rim 22 is preferably greater than 3 mm and less than 10 mm.

To acquire the acquired model, the user assembles the tubular spacer 16 to the adapter 18 by means of the clips 20, then the portable scanner on the adapter 18 so that the portable scanner then performs a scan through the spacer tubular 16 and the adapter 18. He then introduces the end of the tubular spacer opposite the portable scanner into his mouth, inserting the rim 22 between his lips and the teeth. The lips thus rest on the tubular spacer 16, outside the latter, which allows a clear view of the teeth through the oral opening Oo.

In the service position obtained, as illustrated in Figures 2 and 3, the teeth do not rest on the support, so that the user U can, by turning his head relative to the support, modify the teeth which are visible by the portable scanner through the oral opening. He can also modify the spacing between his dental arches. In particular, the support spreads the lips, but does not press on the teeth so as to separate the two jaws from each other.

The acquired model can totally or partially represent a dental arch or both dental arches.

Cutting the acquired model

In one embodiment, the arch model acquired with the portable scanner is cut, preferably to define at least one tooth model 30. In one embodiment, the updated model is thus reduced to part of the acquired model , preferably reduced to a tooth model.

Preferably, steps b) and c) are then implemented successively for each tooth model.

The cutting of a model can implement any known cutting process .

Correction of the updated model, possibly resulting from a division of the acquired model, consists of modifying it so that it is more consistent with the object it models. To this end, it is possible in particular to improve the resolution of the model and/or complete it and/or give it more realistic colors, for example to make it hyper realistic, and/or clean it. Model cleaning consists of removing parts of the model that do not model the target object, for example removing the representation of an orthodontic bracket when the target object is a tooth or removing defects resulting from the cleaning operation. acquisition, particularly for cleaning artifacts caused by saliva during acquisition.

Correction

The updated model is preferably processed electronically to be corrected. Correction of the updated model can be carried out after or before a simplification.

In a preferred embodiment, illustrated in the , the updated model is compared to a “correction model”, then corrected according to the results of this comparison.

Preferably, we proceed according to the following steps when the model to be corrected is a tooth model:
i) creation of a historical library comprising more than 1,000 tooth models, called “historical tooth models”, and allocation of a tooth number to each historical tooth model;
ii) analysis of the tooth model to be corrected, so as to determine the number of the tooth modeled by said tooth model to be corrected;
iii) search, in the historical library, for a historical tooth model having the same number and having maximum proximity to said tooth model to be corrected, or “optimal tooth model”;
iv) modification of the tooth model to be corrected based on information relating to the optimal tooth model, the modification possibly including a replacement of the tooth model to be corrected by the optimal tooth model.

In step i) , a historical library is created comprising preferably more than 2,000, preferably more than 5,000, preferably more than 10,000 and/or less than 1,000,0000 historical tooth models.

A historical tooth model can in particular be obtained from a model of a dental arch of a “historical” patient obtained with a scanner. This arch model can be cut in order to isolate the representations of the teeth, that is to say the tooth models, as on the .

The historical library therefore contains historical tooth models and the numbers of the teeth modeled by these historical tooth models.

In step ii) , the tooth model to be corrected is analyzed to determine its number.

Tooth numbers are conventionally assigned according to a standard rule. It is therefore enough to know this rule and the number of a tooth modeled to determine the numbers of the other tooth models.

In a preferred embodiment, the shape of the tooth model to be corrected is analyzed so as to define its number. This shape recognition is preferably carried out using a neural network.

Preferably, a neural network is used, preferably chosen from “Object Detection Networks”, for example from the following neural networks: R-CNN (2013), SSD (Single Shot MultiBox Detector: Object Detection network), Faster R-CNN (Faster Region-based Convolutional Network method: Object Detection network), Faster R-CNN (2015), SSD (2015), RCF (Richer Convolutional Features for Edge Detection) (2017), SPP-Net, 2014, OverFeat (Sermanet et al.), 2013, GoogleNet (Szegedy et al.), 2015, VGGNet (Simonyan and Zisserman), 2014, R-CNN (Girshick et al.), 2014, Fast R-CNN (Girshick et al.) , 2015, ResNet (He et al.), 2016, Faster R-CNN (Ren et al.), 2016, FPN (Lin et al.), 2016, YOLO (Redmon et al.), 2016, SSD (Liu et al.), al.), 2016, ResNet v2 (He et al.), 2016, R-FCN (Dai et al.), 2016, ResNeXt (Lin et al.), 2017, DenseNet (Huang et al.), 2017, DPN (Chen et al.), 2017, YOLO9000 (Redmon and Farhadi), 2017, Hourglass (Newell et al.), 2016, MobileNet (Howard et al.), 2017, DCN (Dai et al.), 2017, RetinaNet ( Lin et al.), 2017, Mask R-CNN (He et al.), 2017, RefineDet (Zhang et al.), 2018, Cascade RCNN (Cai et al.), 2018, NASNet (Zoph et al.), 2019, CornerNet (Law and Deng), 2018, FSAF (Zhu et al.), 2019, SENet (Hu et al.), 2018, ExtremeNet (Zhou et al.), 2019, NAS-FPN (Ghiasi et al.) , 2019, Detnas (Chen et al.), 2019, FCOS (Tian et al.), 2019, CenterNet (Duan et al.), 2019, EfficientNet (Tan and Le), 2019, AlexNet (Krizhevsky et al.), 2012, Cbnet (2020), Point-gnn (2020), MDFN (2020), CADN (2021).

Preferably, the neural network is trained by providing it with tooth models as input and the associated tooth number as output. The neural network thus learns to provide a tooth number for a tooth model presented to it as input.

We can then modify the tooth model to be corrected from a historical tooth model with the same number.

In step iii) , we search in the historical library, among the historical tooth models having the same number as the tooth model to be corrected, the historical tooth model having maximum proximity with the tooth model to be corrected. This historical tooth model is referred to as the “optimal tooth model”.

“Closeness” is a measure of the difference in shape between the historical tooth model and the tooth model to be corrected. The difference in shape can be, for example, an average distance between the historical tooth model and the tooth model to be corrected after they have been arranged in a standardized configuration.

Preferably, it is considered that the maximum proximity, or “maximum agreement”, is achieved when the cumulative Euclidean distance between the points of the historical tooth model and those of the tooth model to be corrected is minimal.

In step iv) , the tooth model to be corrected is modified based on information relating to the optimal tooth model, which serves as a correction model.

For example, the areas of the tooth model to be corrected which, in the standardized configuration, are separated from the optimal tooth model by a distance greater than a first distance threshold, for example by more than 1 mm, can be replaced by the areas of the optimal tooth model facing them, and/or
“white” areas of the tooth model to be corrected, i.e. undefined areas, which face areas of the optimal tooth model that are not white can be replaced by these areas of the tooth model optimal.

Changing the tooth model to be corrected may also consist of replacing the tooth model to be corrected with the optimal tooth model.

Preferably, steps i) to iv) are executed for each tooth model cut out in the acquired model.

The above method can be applied to an updated model representing a dental arch. In steps ii) and iii), the classification criterion of the updated model is adapted accordingly. Instead of being the tooth number, the classification criterion can for example be one or more attributes relating to an arch, for example the width of the arch, or to both arches. The classification criterion can in particular be chosen from those listed above, in the definition of a classification criterion.

The updated model can be submitted to a neural network trained for this purpose using a learning database. The neural network can be chosen in particular from the following networks: Shape Inpainting using 3D Generative Adversarial Network and Recurrent Convolutional Networks (2017), Deformable Shape Completion with Graph Convolutional Autoencoders (2018), Learning 3D Shape Completion Under Weak Supervision (2018) , PCN: Point Completion Network (2019), TopNet: Structural Point Cloud Decoder (2019), RL-GAN-Net: A Reinforcement Learning Agent Controlled GAN Network for Real-Time Point Cloud Shape Completion (2019), Cascaded Refinement Network for Point Cloud Completion (2020), PF-Net: Point Fractal Network for 3D Point Cloud Completion (2020), Point Cloud Completion by Skip-attention Network with Hierarchical Folding (2020), GRNet: Gridding Residual Network for Dense Point Cloud Completion (2020) , and Style-based Point Generator with Adversarial Rendering for Point Cloud Completion (2021).

For example, each record of the learning database can include:
- an incomplete model of an object, for example
a dental arch, or
a tooth model, and
- the same model, but complete.

Preferably, the objects modeled in the recordings belong to the same class defined using a classification criterion. For example, if these objects are teeth, the tooth number of the tooth models is preferably identical for all the records in the learning base.

Preferably, a neural network specialized in image generation is used, for example:
- Cycle-Consistent Adversarial Networks (2017),
- Augmented CycleGAN (2018),
- Deep Photo Style Transfer (2017),
- FastPhotoStyle (2018),
- pix2pix (2017),
- Style-Based Generator Architecture for GANs (2018),
- SRGAN (2018),
- WaveGAN 2020
- GAN-LSTM 2019,
- CSGAN 2021,
- DivCo 2021.

After having been trained with this learning base, by providing it, successively for each recording, the incomplete model and outputting the corresponding complete model, the neural network can transform an incomplete model into a complete model.

The full model serves as a “correction model”.

The correction model can be used to carry out quality control during the acquisition of the acquired model, that is to say to verify that this acquisition has not generated any defects. A defect is a part of the acquired model that does not correctly represent the dental arch(s). For example, the model may present roughness or recesses which, in reality, that is to say on the dental arch(s), do not exist.

Correction of the acquired model can also be used to remove such defects resulting from the acquisition operation.

Cleaning

A cleaning of the updated model is preferably carried out, independently of the modification process above (steps i) to iv)). The objective is to process the updated model to make the representation of an external object disappear, but also to replace it with a surface representing as faithfully as possible the surface of the arcade covered by this object.

In a preferred embodiment, illustrated in the , the updated model is cleaned to remove the representation of an object external to the user, for example an orthodontic bracket, partially masking at least the object to be modeled, for example a tooth, by proceeding according to the following steps:
i') definition of:
- a first certain zone made up of the points of the updated model representing the object to be modeled, for example a tooth, with a precision greater than 90%, or “first certain points”, and
- a first uncertain zone, constituting the 100% complement of the updated model;
ii') extrapolation of the first certain zone, from the first certain zone alone, to define, in the region of the first uncertain zone, a first reconstructed zone, then
definition of :
- a second certain zone consisting of the points of the first uncertain zone separated from the first reconstructed zone by a distance less than a threshold distance, or “second certain points”; And
- a second uncertain zone, constituting the 100% complement of the first uncertain zone;
iii') extrapolation of the set consisting of the first and second certain zones, from the set alone, to define, in the region of the second uncertain zone, a second reconstituted zone, then
replacement of the second uncertain zone by the second reconstructed zone, so as to obtain a cleaned updated model.

These operations advantageously make it possible to remove the representation of the external object from the updated model and to obtain a cleaned updated model representing the object to be modeled with good precision.

The external object may in particular be all or part of an orthodontic appliance, a crown, an implant, a bridge, an elastic or a veneer. It can also be a food, a drop of saliva, all or part of a tool.

In step i') , we isolate the representation of the external object. More precisely, we identify the points of the updated model which are, almost certainly, representations of points of the arch.

Algorithms for detecting objects in images are well known to those skilled in the art. Preferably, a neural network is used, preferably chosen from “Object Detection Networks”, for example from those listed above.

These neural networks are capable, after training, of detecting the points of the updated model which, with a precision greater than a precision threshold greater than or equal to 90%, represent points of the arch, or “first certain points”. All of these points, called “first certain zone”, constitute a fraction of the updated model. The points in the updated model that are not in the first certain zone together form the “first uncertain zone”.

Preferably, the precision threshold is greater than 95%, preferably greater than 98%, preferably greater than 99% and/or less than 99.99%.

Training a neural network to detect an object in an image poses no difficulty to those skilled in the art. For example, we can provide it with arcade models as input and as output the same arcade models on which the zones representing the arcade and the zones representing an external object have been identified. He thus learns to define these zones on an arcade model.

The following steps aim to fill the “first white zone” of the updated model which appears if we delete the first uncertain zone.

In step ii') , the first certain zone is used to define a surface filling said first white zone. This surface is called “first reconstructed zone”.

The techniques for carrying out this extrapolation are well known. We can cite for example WENDLAND, Holger. Piecewise polynomial, positive definite and compactly supported radial functions of minimal degree. Advances in computational mathematics , 1995, vol. 4, no. 1, p. 389-396.

To refine the reconstruction of the surface of the arch masked by the external object, we then identify the points of the first uncertain zone which are close to the first reconstructed zone. These points are therefore points of the updated model which are close to a surface extrapolated from points representing, with near certainty, points of the arcade.

We consider that these points of the updated model, or “second certain points”, are also, with great precision, points representing points of the arcade. We call all of these points “second certain zone”. These points are therefore points of the updated model that the analysis of step i') had discarded, but which we retain because they are close to a surface extrapolated from the points that the analysis of step i') 'step i') had retained.

The points of the updated model which do not belong to the first certain zone, nor to the second certain zone together form the “second uncertain zone”.

The proximity of a point in the first uncertain zone to the first reconstructed zone can be evaluated by measuring the Euclidean distance between this point and this first reconstructed zone. We consider that a point in the first uncertain zone must enter the second certain zone if this distance is less than a threshold distance.

If the model is at scale 1, that is to say represents the modeled object with the real dimensions of this object, the threshold distance is preferably greater than 0.1 mm and/or less than 1 mm .

The threshold distance can also be determined by an analysis of the distribution of said Euclidean distances between the points of the first uncertain zone and the first reconstructed zone, for example as a function of the mean and the standard deviation of these distances. A dynamic calculation with a “3 sigma rule” type method can for example be implemented.

In step iii') , the objective is to replace the second uncertain zone with a second reconstructed zone which better corresponds to the surface of the arch. For this purpose, the first and second certain zones are extrapolated into the region of the second uncertain zone.

Particularly remarkably, the extrapolation is not based on the first certain zone alone, but on all of the first and second certain zones. Tests have shown that this extrapolation makes it possible to obtain a second reconstructed zone representing, with high reliability, the surface of the arch.

The extrapolation in step iii’) can use the same methods as those implemented in step ii’). It can also use different methods.

The first and second certain zones and the second reconstituted zone constitute the cleaned updated model, on which the representation of external objects has been removed.

Appearance correction

Preferably, the updated model is made hyperrealistic, preferably by means of a neural network.

The updated model can be submitted to a neural network trained for this purpose using a learning base, as described for example in http://cs230.stanford.edu/projects_winter_2020/reports/32639841.pdf.

For example, each record of the learning database can include:
- a rough model of an object, for example
a dental arch, or
a tooth model, and
- the same model, but hyperrealistic.

Raw models preferably look similar to the updated model. They can be scans, preferably carried out with a scanner identical or similar to the portable scanner used in step a).

The raw models may, for example, have been made hyperrealistic by photo projection.

Preferably, the objects modeled in the recordings belong to the same class defined using a classification criterion. For example, if these objects are teeth, the tooth number of the tooth models is preferably identical for all the records in the learning base.

Preferably, a neural network specialized in image generation is used, for example:
- Cycle-Consistent Adversarial Networks (2017)
- Augmented CycleGAN (2018)
- Deep Photo Style Transfer (2017)
- FastPhotoStyle (2018)
- pix2pix (2017)
- Style-Based Generator Architecture for GANs (2018)
- SRGAN (2018).

After having been trained with the learning base, by providing it, successively for each recording, with the raw model as input and the hyperrealistic model as output, the neural network can transform a raw model into a hyperrealistic model.

Thanks to the correction methods described above, an updated model can be advantageously transformed into an updated model representing the modeled object, for example the real arch, with great realism.

Simplification

Before being used, for example during a step b), the updated model, possibly corrected, can be simplified, in particular to facilitate the processing in step b). The simplification can also be carried out before or after the possible correction, or between two correction treatments.

The updated model, preferably corrected, is preferably displayed on a screen, preferably on the screen of the mobile phone when the latter integrates the portable scanner and/or on a screen in the office of a dental care professional.

One or more of the cutting and/or correction and/or cleaning and/or appearance correction and/or simplification operations described above can be implemented
- in the portable scanner, preferably in the mobile telephone incorporating the portable scanner or in communication with an acquisition tool, or
- in a computer processing center in communication with said mobile phone, to which said mobile phone has transmitted the acquired model or the updated model.

In step b), at least one value of a dimensional parameter of the updated model, or “dimensional value” and/or at least one value of an appearance parameter of the updated model, or “value of appearance ".

Step b) can be implemented in the mobile phone or in a processing center, remote from the mobile phone and to which the mobile phone transmits the updated model.

The updated model used in step b) can be
- the acquired model, that is to say the raw model as the portable scanner generated it, or
- part of the acquired model, for example resulting from a computer division of the acquired model, or
- said model acquired after correction and/or simplification, or
- said part of the model acquired after correction and/or simplification.

A “dimensional value” is a value that depends on the shape of the updated model. This value is that of a “dimensional parameter”, which can be chosen in particular from
- a dimension of the updated model, for example the width, length or height of the dental arch or a tooth;
- a distance of a point of the updated model relative to a reference frame, or
- a parameter derived from these dimensions and distances, for example an orthodontic index, a canine/molar occlusion class, a measurement of a vertical overbite or a horizontal overjet "), a tooth number, or an indication of the presence or absence of a tooth.

The dimensional value can be measured on the updated model or be obtained from one or more measurements made on the updated model.

For example, we can measure a gap between two teeth, the position of a remarkable point in relation to a reference, for example orthonormal, fixed in relation to the updated object (arch or tooth in particular) or in relation to another tooth, for example to evaluate the alignment of a tooth in relation to the other teeth, the misalignment of a tooth in relation to the others or in relation to a predetermined position in the mark, the positioning of one or more teeth in relation to to a fixed or removable orthodontic appliance positioned on the teeth or soft tissues, the index of crowding and/or irregularity of the arch, the misalignment of a tooth in relation to the other teeth or in relation to the gum, a deformation of a tooth, for example the depth of a cavity, a deformation of the gum, the width of the arch or the relative position of one arch in relation to the other.

The dimensional value can also be a measure of a difference in shape between the updated model and a reference model. In particular, we can compare the shapes and/or positions of teeth in the updated model and in a reference model.

An “appearance value” is a value that depends on the appearance of the surface of the updated model. This value is that of an “appearance parameter”, which can be chosen in particular from a color, a reflectance, a transparency, a reflectivity, a tint, a translucency, an opalescence, an index on the presence of tartar, d plaque or food on the tooth.

The appearance value can also be a measure of a difference in appearance between the updated model and a reference model. In particular, we can compare the appearances of teeth in the updated model and in a reference model.

The reference model is chosen according to the intended application.

For example, if the objective is to check whether the dental situation is normal at the current moment, that is to say to check that it does not require intervention by a dental care professional, in particular for therapeutic or aesthetic reasons, the reference model can be a model which represents an object of the same type as the updated object, or even the updated object, in a dental situation considered normal at the updated moment.

The reference model may be representative of a set of individuals, preferably comprising more than 100 individuals, preferably more than 1000 individuals and/or less than 1,000,0000 individuals, for example
- a tooth from a typodont if the updated object is a tooth, or
- an arch corresponding to an average form of arch for all individuals if the updated object is an arch.

The reference model may be a model which represents an object of the same type as the updated object, preferably the updated object, but in a position and/or with a shape and/or with an appearance which is that(s) /that of the anticipated updated object(s) for a reference instant, before or after the updated instant or simultaneous with the updated instant.

The reference moment may in particular be a stage of an orthodontic treatment undergone by the user (for example at the beginning or end of the orthodontic treatment or at an intermediate stage of the orthodontic treatment, in English "intermediate set-up", or “staging”).

The time interval between the updated and reference times may be greater than one week, preferably greater than 2 weeks, 4 weeks, 6 weeks, 2 months and/or less than 6 months.

The reference model can be obtained by means of a scanner, for example with the portable scanner by the user, preferably by means of a professional scanner, or be obtained by construction from photos of the arch and 'a library of historic teeth, as described in EP18184486, equivalent to US16/031,172.

The reference model is preferably obtained by computer simulation, so that it represents the dental arch in the configuration planned at the reference time, in particular at the end of orthodontic treatment or at the updated time.

For example, it may result from a modification of an initial model, for example generated by means of a scan of an arch of the user, preferably generated more than a week before the updated moment, for example at the start of orthodontic treatment. The initial model is conventionally cut to define tooth models. Moving the tooth models then makes it possible to simulate the course of orthodontic treatment.

An example of software for manipulating tooth models and creating a treatment scenario is the Treat program, described at https://en.wikipedia.org/wiki/Clear_aligners#cite_note-invisalignsystem-10 . US5975893A also describes the creation of a processing scenario.

In one embodiment, we proceed to:
- a division of the reference model produced prior to the updated instant or of the updated model, so as to generate tooth models,
- a movement of one or more said tooth models, without deformation of the tooth models, until obtaining a modified model presenting a maximum shape concordance with the updated or reference model, respectively,
- an evaluation of the difference in positioning (determination of at least one dimensional value) of at least one tooth model between its position in the reference or updated model, respectively, and its position in the modified model.

In step c), the dimensional value and/or the appearance value determined in step b) is/are used, in particular to decide whether an action for therapeutic or aesthetic purposes is necessary and/ or to contribute to the determination of this action.

The dimensional value and/or the appearance value, and preferably the updated model can be presented to the user, for example by being displayed on the screen of his mobile phone.

In addition or alternatively, they can also be transmitted, preferably by radio, preferably by a mobile phone integrating the portable scanner or in communication with the acquisition tool, to a dental care professional, in particular an orthodontist or to a remote computer in communication with the mobile phone.

Preferably, the dimensional value and/or the appearance value is/are interpreted, preferably by computer, preferably by a mobile phone integrating the portable scanner, and a recommendation is presented to the user, preferably on the screen of his cell phone.

Using refreshed images

In a particularly advantageous embodiment, in step a), the user acquires, in addition to the updated model, one or more “updated” images, preferably extra-oral. Preferably, it uses the mobile phone used to acquire the acquired model.

Preferably, the updated images are photographs or images taken from a film. They are preferably in color, preferably in real color. Preferably, they represent the dental arches substantially as seen by the operator of the device for acquiring these images.

The information provided by the updated images makes it possible to supplement that provided by the acquired model. The information may in particular relate to a dimension and/or the appearance of one or more objects, preferably teeth, represented on the updated image(s). In particular, the analysis of an updated image, preferably by computer, makes it possible to confirm and/or correct a dimensional value and/or an aspect value determined from the updated model, and/or to complete the teaching taken from the updated model.

For example, the updated model may allow the detection of a cavity on the surface of a tooth and an updated image may show a darker area at the location of this cavity. The updated image thus confirms the presence of the cavity. It also allows you to confirm your position. The analysis of the model and updated images thus makes it possible to detect, and monitor the evolution of, caries.

The updated images can also very reliably provide information on the appearance of the teeth, for example on their colors. Projected onto the updated model, they allow the surface of the updated model to be colored in a very realistic manner.

More preferably, several updated images taken at different angulations are acquired, that is to say with different orientations of the acquisition device relative to the oral cavity of the user. For example, the set of updated images may include 6 images representing the dental arches "front views", "front-right views", "right views", "front-left views", "left views". » and “bottom views”, respectively.

Preferably, at least one updated image is acquired facing the user (front view). Preferably, at least one updated image is acquired from the user's right, and at least one updated image is acquired from the user's left.

The set of updated images preferably comprises more than two, preferably more than three, preferably more than 5, preferably more than 6 and/or less than 30, preferably less than 20, preferably less than 15, preferably less than 10 updated images.

In one embodiment, the updated images are processed to generate a said correction model and/or a said reference model. For this purpose, all conventional techniques can be used.

The acquisition of two models at the updated moment, namely the updated model and a model obtained from updated images, then the comparison of these models advantageously makes it possible to make the best use of the 3D and 2D representations provided by the scanner. portable and the image acquisition device, respectively.

The method can be implemented independently of any orthodontic treatment, in particular to monitor that the position and/or shape of the teeth are not “abnormal”, that is to say when they do not comply with a therapeutic standard or aesthetic. Preferably, an appointment with a dental professional should then be made. The process can be implemented before orthodontic treatment.

Prior to orthodontic treatment, the method can be implemented in particular to acquire the positioning and anatomy of the teeth of the future patient and launch the manufacture of an interceptive orthodontic appliance or a tailor-made orthodontic appliance, for example. example transparent orthodontic aligners, or design individualized treatment using archwires and brackets.

The method can be implemented during orthodontic treatment, in particular to control its progress, step a) being implemented less than 3 months, less than 2 months, less than 1 month, less than a week, less than 2 days after the start of treatment, that is to say after the installation of an appliance intended to correct the positioning of the user's teeth, called an "active retainer".

During orthodontic treatment, the method can be implemented to acquire an updated model of the teeth and allow the manufacture of a new orthodontic appliance, for example an implant, an orthodontic splint, or a vestibular orthodontic appliance .

Preferably, the updated model generated in step a) and/or the value(s) determined in step b) is/are transmitted to a dental professional to help them establish a diagnosis.

The process can also be implemented after orthodontic treatment, to check that the positioning of the teeth does not change unfavorably (“recurrence”). Step a) is then preferably implemented less than 3 months, less than 2 months, less than 1 month, less than a week, less than 2 days after the end of the treatment, that is to say after the installation of an appliance intended to hold the teeth in position, called a “passive retainer”.

The dimensional value is preferably used to
- detect a recurrence, and/or
- determine a speed of evolution of a change in positioning of the teeth, and/or
- optimize the date of making an appointment with a dental care professional, and/or
- evaluate the effectiveness of orthodontic treatment, and/or
- evaluate the evolution of the positioning of teeth towards a reference model corresponding to a determined positioning of the teeth, in particular an improved positioning of the teeth, and/or
- modify ongoing orthodontic treatment, for example by manufacturing a new series of orthodontic aligners, and/or
- in dentistry, and/or
- visualize and/or measure and/or detect dental plaque, and/or caries, and/or a microcrack, and/or wear, for example resulting from bruxism or the use of an active orthodontic appliance or passive, particularly in the event of breakage or detachment of an orthodontic arch;
- visualize and/or measure and/or detect a change in volume, in particular during tooth growth or following intervention by a dental professional, for example a deposit of glue on the surface of the teeth;
- assess the advisability of interceptive treatment, before any orthodontic treatment, in particular to assess the benefit of orthodontic treatment.

The appearance value is preferably used to detect or evaluate a position or shape of a stain or decay.

In a particularly advantageous embodiment, both the dimensional value and the appearance value are used. Advantageously, the method can thus be used for precise and localized monitoring of the evolution of certain pathologies, in particular stains, demineralization, or caries.

As is now clear, the invention provides a method allowing a particular user, for example a patient, to generate a model of one or more of his arches, or of one or more of his teeth. He does not need any specific hardware, other than the portable scanner, which is preferably integrated into his mobile phone.

The acquired model can be acquired without introducing the portable scanner into the user's mouth, i.e. extra-orally. Processing the updated model to correct it makes it possible in particular to correct it to model regions of the mouth to which the portable scanner has not had access, for example in an interproximal space.

In one embodiment, in step a), the acquired model is coarse. It may in particular represent a “3D skeleton” of the user's dental arch(s), and only include less than 500 points, less than 200 points, less than 100 points or less than 50 points and/or more than 10 points. Processing the updated model to correct it, in particular with a neural network or from a historical library, advantageously makes it possible to reconstruct a much more precise model of the user's dental arch(s).

In one embodiment, the portable scanner is partially inserted into the user's mouth. Advantageously, the intradoses of the teeth can be scanned.

As shown on the , preferably, the portable scanner 6 comprises a mobile telephone 12 and an acquisition tool 31 in communication with the mobile telephone, preferably by radio, preferably by Bluetooth®. Cable communication is also possible.

The acquisition tool is provided with an acquisition head 32 which can be inserted into the user's mouth. The acquisition head acquires the acquired model and transmits it to the mobile phone 12, or acquires a signal, for example a set of images, and transfers it to the mobile phone 12 so that the latter generates the acquired model from said signal.

Preferably, the acquisition tool does not have a physical link with the mobile phone or is connected to the mobile phone by a flexible link, for example a cable.

Preferably, the acquisition tool includes a handle 34 facilitating its handling, by the user himself or one of his relatives, for example like a toothbrush.

In one embodiment, the acquisition tool is fixed to the mobile phone, for example by means of a clip, a hook-and-loop strip, clamping jaws, a screw, a magnet , a cover or a flexible band, preferably elastic. The fixation can also result from a complementarity of form with the mobile phone. For example, the acquisition tool can be attached to a phone case.

• l’espace interdentaires des dents
• les faces linguales des dents
• le palais incluant par exemple la suture médiane palatine
• les tissus mous (aphte, lésions bénignes ou malignes, récessions, )
• la teinte des dents
• la présence de caries ou tâches
• l’état et/ou la forme des implants, couronnes et/ou bridges
• l’état des appareils de traitement vestibulaires ou linguaux (ex : brackets linguaux, vestibulaires, disjoncteur maxillaire ou tout autre auxiliaire de traitement) ou de contention (arc palatin)
• les distances entre les différentes parties d’un même appareillage vestibulaires, linguaux ou tout autre auxiliaire
• état des dispositifs d’ancrage (type mini-vis)
• distance entre les dispositifs d’ancrage et les appareils en présence dans la bouche
• des points de suture de tissus mous
• la cicatrisation de tissus mous post-chirurgie
• la courbe de spee
• la courbe de wilson
• la distance intercanine
• la distance intermolaire

In one embodiment, the method also uses a measuring head in communication with the mobile phone and which is introduced into the user's mouth in order to acquire additional data, for example data on

• the interdental space of the teeth
• the lingual surfaces of the teeth
• the palate including for example the median palatal suture
• soft tissues (canker sores, benign or malignant lesions, recessions, etc.)
• the color of the teeth
• the presence of cavities or stains
• the condition and/or shape of implants, crowns and/or bridges
• the condition of vestibular or lingual treatment devices (e.g.: lingual, vestibular brackets, maxillary breaker or any other treatment aid) or restraint (palatal arch)
• the distances between the different parts of the same vestibular, lingual or any other auxiliary appliance
• condition of anchoring devices (mini-screw type)
• distance between anchoring devices and devices in the mouth
• soft tissue stitches
• healing of soft tissues post-surgery
• the spee curve
• Wilson's curve
• the intercanine distance
• the intermolar distance

There presents different images providing additional data, in particular on the palate including a median palatal suture (image 1), soft tissue stitches (image 2), distances between the different parts of the same vestibular, lingual or any other auxiliary (images 3 and 4), the condition and/or shape of the implants, crowns and/or bridges (images 5 and 8), the condition of the anchoring devices (mini-screw type) and the distance between the anchoring devices and the devices present in the mouth (image 6), the condition of the vestibular or lingual treatment devices (for example lingual brackets, vestibular brackets, maxillary breaker or any other treatment aid) or restraint ( palatal arch) (image 7), the interdental space and the healing of soft tissues post-surgery (image 9), the lingual surfaces of the teeth (image 10), the intercanine distance and the intermolar distance (image 10), the shade teeth (image 11), the Spee curve (image 12), the Wilson curve (image 13), and the presence of cavities or stains (image 14).

The measuring head can be integrated into a measuring tool having one or more of the characteristics of the acquisition tool. Unlike the latter, however, the measurement tool is not used to acquire the acquired model.

The acquired model can then be corrected in particular to be completed and/or cleaned and/or made hyperrealistic. The user can transmit to a dental professional, possibly to a dental professional whom he has never met, a model which the dental professional can analyze, in particular to establish a diagnosis and/or to address advice to the user and/or to set an appointment date.

Of course, the invention is not limited to the embodiments described and represented.

The methods of correction and simplification of the updated model described above are inventions, independently of the method of description.

Improvements

Beyond the method described above and more generally, the invention also relates to a method of acquiring at least one image of at least one dental arch of a user by means of a mobile telephone and an acquisition tool comprising an acquisition head provided with a camera, preferably capable of being introduced into the mouth of the user, method in which the acquisition head:
- acquires said image and transmits it to the mobile phone, or
- acquires a signal and transfers it to the mobile phone so that said mobile phone generates the image from said signal, independently or with the help of a computer with which said mobile phone is in communication.

Said at least one image is preferably a photo, preferably a photo representing the dental arch in a realistic manner, as a person would directly observe it.

The image can be used to generate a model as following step a), but the image acquisition method according to the invention is no longer limited to this particular embodiment, the image can be used for other purposes. This process is therefore described below as a “generalized process”.

To the extent that a characteristic described above for step a) is technically compatible with the generalized process, it can nevertheless be applied to this process.

The mobile phone and the acquisition tool are preferably exclusively manipulated by the user.

The acquisition can be carried out extraorally, the camera of the acquisition tool not entering the user's mouth. The acquisition can be carried out intraorally, with the camera of the acquisition tool entering the user's mouth.

In one embodiment, the acquisition tool is fixed to the mobile phone, for example by means of a clip, a hook-and-loop strip, clamping jaws, a screw, a magnet , a cover or a flexible band, preferably elastic. The fixation can also result from a complementarity of form with the mobile phone. For example, the acquisition tool can be attached to a phone case.

Preferably, however, the mobile phone and the acquisition tool communicate with each other, but can be moved independently of each other. Preferably, no rigid device, preferably no mechanism, interconnects the mobile phone and the acquisition tool so that the mobile phone can be moved in space, preferably in all dimensions of space, without necessarily taking the acquisition tool with it.

Preferably, the screen displays the scene observed by the acquisition head camera.

The independence of movement between the mobile phone and the acquisition tool makes it possible in particular to use the screen of the mobile phone to view the scene observed by the camera of the acquisition head, without this visualization being hampered by manipulation of the acquisition head.

In one embodiment, during acquisition, the user observes the screen of the mobile phone, the mobile phone preferably being stationary relative to the ground, for example placed on a table, and manipulates the acquisition tool. He can thus easily position the acquisition tool in a desired position, preferably for extraoral acquisition. In addition, this embodiment advantageously allows the user to use the mobile phone camera located on the side opposite the screen, without having to use a mirror.

Preferably, the user acquires at least one front view image, preferably at least one image from the user's right, and, more preferably, at least one image from the user's left.

Preferably, the user acquires at least one open mouth image and at least one closed mouth image.

The set of acquired images preferably comprises more than two, preferably more than three, preferably more than 5, preferably more than 6 and/or less than 30, preferably less than 20, preferably less than 15, preferably less than 10 images.

Preferably, the user uses a tool to free their lips, and better expose the dental arch to the camera of the acquisition tool. The tool can be, for example, a spoon inserted into his mouth.

In one embodiment, he uses a retractor which he inserts partially into his mouth.

Preferably, the generalized method comprises, after said acquisition, an analysis of said image in order to define the dental situation of the user, and preferably design an active or passive orthodontic treatment plan, and/or to check the smooth progress of the active or passive orthodontic treatment in progress.

Preferably, the acquisition method comprises, after said analysis of said image, the manufacture of an orthodontic appliance, for example an orthodontic splint, and preferably sending said orthodontic appliance to the user.

The uses mentioned above for updated images can also be applied to the image or images acquired following the generalized process.

Said at least one image is preferably used to
- detect a recurrence, and/or
- determine a speed of evolution of a change in positioning of the teeth, and/or
- optimize the date of making an appointment with a dental care professional, and/or
- evaluate the effectiveness of orthodontic treatment, and/or
- evaluate the evolution of the positioning of teeth towards a reference model corresponding to a determined positioning of the teeth, in particular an improved positioning of the teeth, and/or
- modify ongoing orthodontic treatment, for example by manufacturing a new series of orthodontic aligners, and/or
- in dentistry, and/or
- visualize and/or measure and/or detect dental plaque, and/or caries, and/or a microcrack, and/or wear, for example resulting from bruxism or the use of an active orthodontic appliance or passive, particularly in the event of breakage or detachment of an orthodontic arch;
- visualize and/or measure and/or detect a change in volume, in particular during tooth growth or following intervention by a dental professional, for example a deposit of glue on the surface of the teeth;
- assess the advisability of interceptive treatment, before any orthodontic treatment, in particular to assess the benefit of orthodontic treatment.

There illustrates a device 6' for implementing such an image acquisition method. This kit includes a 12' mobile phone and a 31' acquisition tool in communication with the mobile phone, preferably over the air, preferably by Bluetooth® or WiFi. Cable communication is also possible.

The acquisition tool 31' is provided with an acquisition head 32' which can be inserted into the user's mouth. The acquisition head includes a camera 33' which acquires the image and transmits it to the mobile phone 12', or acquires a signal and transfers it to the mobile phone 12' so that the latter generates the image from said signal.

Preferably, the acquisition tool does not have a physical link with the mobile phone or is connected to the mobile phone by a flexible link, for example a cable.

Preferably, the acquisition tool includes a handle 34' facilitating its handling, by the user himself or one of his relatives, for example like a toothbrush.

The mobile phone 12' may include one or more of the characteristics of the mobile phone 12. Preferably, it is not fixed on any support, and in particular on any support fixed on the user such as the support 10 described above, and the The user can manipulate it freely.

Claims (13)

Method for acquiring at least one image of at least one dental arch of a user (U) by means of a mobile telephone (12') and an acquisition tool (31') comprising a head acquisition head (32') provided with a camera (33'), method in which the acquisition head:
- acquires said image and transmits it to the mobile phone, or
- acquires a signal and transfers it to the mobile phone so that said mobile phone generates the image from said signal, independently or with the help of a computer with which said mobile phone is in communication,
said at least one image being a photo or an image extracted from a film. Method according to the preceding claim, in which the mobile telephone (12') and the acquisition tool (31') are exclusively manipulated by the user. Method according to any one of the preceding claims, in which the acquisition is carried out extraorally, the camera of the acquisition tool not entering the mouth of the user. Method according to any one of claims 1 to 2, in which the acquisition is carried out intraorally, the camera of the acquisition tool penetrating into the mouth of the user. Method according to any one of the preceding claims, in which the mobile telephone and the acquisition tool are movable independently of each other. Method according to any one of the preceding claims, in which, during acquisition, the user observes the screen of the mobile phone to view the scene observed by the camera of the acquisition head. Method according to the immediately preceding claim, in which during the acquisition, the mobile telephone is stationary relative to the ground and the user manipulates the acquisition tool. Method according to any one of the preceding claims, in which the user acquires at least one front view image, at least one image from the user's right, at least one image from the user's left, at least an open mouth image and at least one closed mouth image. Method according to any one of the preceding claims, in which the user uses a tool to clear his lips and better expose the dental arch to the camera of the acquisition tool. Method according to the immediately preceding claim, wherein said tool is a spreader. Method according to any one of the preceding claims, in which the acquisition tool is in communication with the mobile telephone via radio. Method according to any one of the preceding claims, in which said at least one image is used to
- determine a speed of evolution of a change in positioning of the teeth, and/or
- optimize the date of making an appointment with a dental care professional, and/or
- evaluate the evolution of the positioning of teeth towards a reference model corresponding to a determined positioning of the teeth, and/or
- visualize and/or measure and/or detect a microcrack, and/or wear, and/or
- visualize and/or measure and/or detect a change in volume during tooth growth or following intervention by a dental professional. Method according to any one of the preceding claims, wherein the image is used to generate a digital three-dimensional model.