Classifications

• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T7/00—Image analysis
  • G06T7/0002—Inspection of images, e.g. flaw detection
  • G06T7/0012—Biomedical image inspection
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B1/00—Instruments for performing medical examinations of the interior of cavities or tubes of the body by visual or photographical inspection, e.g. endoscopes; Illuminating arrangements therefor
  • A61B1/00002—Operational features of endoscopes
  • A61B1/00004—Operational features of endoscopes characterised by electronic signal processing
  • A61B1/00009—Operational features of endoscopes characterised by electronic signal processing of image signals during a use of endoscope
  • A61B1/000095—Operational features of endoscopes characterised by electronic signal processing of image signals during a use of endoscope for image enhancement
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B1/00—Instruments for performing medical examinations of the interior of cavities or tubes of the body by visual or photographical inspection, e.g. endoscopes; Illuminating arrangements therefor
  • A61B1/00163—Optical arrangements
  • A61B1/00194—Optical arrangements adapted for three-dimensional imaging
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B1/00—Instruments for performing medical examinations of the interior of cavities or tubes of the body by visual or photographical inspection, e.g. endoscopes; Illuminating arrangements therefor
  • A61B1/24—Instruments for performing medical examinations of the interior of cavities or tubes of the body by visual or photographical inspection, e.g. endoscopes; Illuminating arrangements therefor for the mouth, i.e. stomatoscopes, e.g. with tongue depressors; Instruments for opening or keeping open the mouth
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/0033—Features or image-related aspects of imaging apparatus classified in A61B5/00, e.g. for MRI, optical tomography or impedance tomography apparatus; arrangements of imaging apparatus in a room
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/0059—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
  • A61B5/0082—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence adapted for particular medical purposes
  • A61B5/0088—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence adapted for particular medical purposes for oral or dental tissue
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/45—For evaluating or diagnosing the musculoskeletal system or teeth
  • A61B5/4538—Evaluating a particular part of the muscoloskeletal system or a particular medical condition
  • A61B5/4542—Evaluating the mouth, e.g. the jaw
  • A61B5/4547—Evaluating teeth
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/48—Other medical applications
  • A61B5/4848—Monitoring or testing the effects of treatment, e.g. of medication
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
  • A61B5/6887—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient mounted on external non-worn devices, e.g. non-medical devices
  • A61B5/6898—Portable consumer electronic devices, e.g. music players, telephones, tablet computers
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
  • A61B5/7235—Details of waveform analysis
  • A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
  • A61B5/7267—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems involving training the classification device
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
  • G06T17/20—Finite element generation, e.g. wire-frame surface description, tesselation
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T7/00—Image analysis
  • G06T7/10—Segmentation; Edge detection
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B2576/00—Medical imaging apparatus involving image processing or analysis
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T2207/00—Indexing scheme for image analysis or image enhancement
  • G06T2207/30—Subject of image; Context of image processing
  • G06T2207/30004—Biomedical image processing
  • G06T2207/30036—Dental; Teeth
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T2210/00—Indexing scheme for image generation or computer graphics
  • G06T2210/41—Medical

Definitions

• 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.
• 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 evaluate with precision the displacement and/or the deformation of the teeth since an initial instant. .
• a digital three-dimensional model of a user's dental arch is produced, at the initial instant, preferably with a professional scanner.
• This initial model is then cut so as to define a tooth model for each tooth.
• the tooth models are moved in such a way as 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 has to come for a scan of his teeth.
• This model can then be compared to the initial model to check the positioning and/or the 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.
• 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 time, 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 so as to isolate a part of the model of the arch, 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”.
• the acquisition can be carried out by the user himself, which opens up a wide field of applications.
• the acquisition no longer requires a trip to a dental care professional.
• 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.
• no construction of an arcade model from photos is required.
• 3D models of dental arches are conventionally acquired intraorally, with a 3D optical scanner, an intraoral acquisition allowing the sensor to be very close to the arch, and therefore to provide information of great precision.
• Extraoral (or “extrabuccal”) 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 deform an initial model obtained with a conventional 3D optical scanner. The computer processing necessary for this deformation is costly.
• the portable scanner is of low precision. It suffices to note the spatial position of a few remarkable points of the arch to constitute an updated model.
• the acquisition of an imprecise model is possible with limited and portable technical means.
• An imprecise model also requires little memory to be stored. It can easily and quickly be transmitted over a distance, for example by radio waves.
• the portable scanner Preferably the portable scanner
• - comprises a mobile phone and an acquisition tool comprising an acquisition head capable of being introduced into the mouth of the user, which
• the mobile telephone 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 of user G.
• the updated model is processed by computer to correct it, the correction possibly comprising a modification of the updated model or a replacement of the updated model by a correction model;
• 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 shape difference, preferably so as to minimize said shape difference, preferably by means of a metaheuristic method, in particular chosen from among the methods listed below, preferably by simulated annealing, or
• the updated module is left unchanged or the updated model is replaced by the correction model
• the updated model is submitted to a trained neural network to make a digital three-dimensional model presented to it as input more realistic;
• the updated object is said user's arch or a tooth of said arch
• the correction model is a model
• - 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 a previous time more than 2 weeks, 4 weeks, 6 weeks, 2 months, 3 months and/ or less than 12 months, or less than 6 months at the updated time, or
• model of the updated object which simulates the shape of said updated object as anticipated for the updated instant and which, preferably, was produced at a previous instant of more than 2 weeks, 4 weeks, 6 weeks, 2 months, 3 months and/or less than 6 months at the updated time, or
• 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 time interval between the updated instant and the correction instant 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 carried out more than 2 weeks, more than 4 weeks, more 6 weeks, more than 2 months or more than 3 months before the updated time, 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
• model obtained by statistical processing of historical models from 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 having at least one common characteristic with the user, for example the same age and/or the same sex and /or the same pathology and/or following the same orthodontic treatment or a similar orthodontic treatment;
• 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), the updated model is corrected 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 model history modeling an object of the same type as the updated object, for example modeling an arch or a tooth if the updated model models an arch or a tooth, respectively, and assigning to each historical model 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) searching, in the historical library, for a historical model having the same value for said classification criterion and presenting maximum proximity with said updated model, or “optimal model”; iv) modification of the updated model based on information relating to the optimal model, the modification
• 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 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 reconstitute a high-precision arch model from a model acquisition of low precision;
• step a the updated model is corrected by following the following steps: i’) definition of:
• first certain zone consisting of the points of the updated model representing a part of the patient, for example a tooth, with an accuracy greater than 90%, preferably greater than 95%, preferably greater than 99% or "first certain points", and
• first uncertain zone constituting the 100% complement of the updated model
• extrapolation of the first certain zone from the first certain zone alone, to define, in the region of the first uncertain zone, a first reconstituted zone, then definition of: a second certain zone consisting of the points of the first uncertain zone separated from the first reconstituted zone by a distance less than a threshold distance, or “second certain points”; and
• the updated model is corrected by submitting the updated model to a trained neural network by supplying it as input with raw models of objects of the same type as the updated object, and as output said raw models hyperrealistic renderings;
• step a) the updated model is processed by computer to simplify it;
• the portable scanner is integrated into a portable telephone or comprises a portable 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 mobile phone 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 radio, 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 sensor, in English lidar, for “light detection and ranging”;
• the portable scanner projects a structured light directly onto the patient's teeth and acquires images different from photos;
• 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 mouth open and mouth closed;
• step a) the user spreads his lips and/or his cheeks to make his teeth visible from the portable scanner, then acquires the acquired model, preferably extraorally, that is to say without doing penetrate, even partially, the portable scanner in his mouth;
• the user implements a retractor and/or a portable scanner support to improve the quality of the acquired model
• the portable scanner is immobilized on a support comprising 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 flange extending to the periphery of the oral opening;
• 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 rim of the bracket between the user's teeth and the user's lips;
• step a) the model acquired with the portable scanner is cut out 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 a parameter of aspect of the updated model, or “aspect value”;
• 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 with respect to a reference, preferably fixed with respect to the updated model, preferably a reference model arranged, like the updated model, in a standardized configuration, and
• the appearance parameter is chosen from a color, reflectance, transparency, reflectivity, tint, translucency, opalescence, an indication of the presence of tartar, dental plaque or food on the tooth;
• 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 a previous time more than 2 weeks, 4 weeks, 6 weeks, 2 months, 3 months and/ or less than 6 months at the updated time, or
• model of the updated object which simulates the shape of said object as anticipated for the updated instant and which, preferably, was produced at a previous instant of more than 2 weeks, 4 weeks, 6 weeks, 2 months, 3 months and/or less than 6 months at the updated time, or
• 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 time interval between the updated and reference instants preferably being 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 made for more than 2 weeks, more than 4 weeks, more than 6 weeks , more than 2 months or more than 3 months before the updated time, 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 being preferably guided so that the historical model chosen either the model history showing the closest shape proximity to the updated model, or
• model obtained by statistical processing of historical models from said historical library preferably so that the model obtained by statistical processing is representative of a population of individuals
• the method comprises, after step b), the following step: c) use of the dimensional value and/or the aspect value for:
• step c) the dimensional value and/or the aspect value are used to
• an orthodontic index in particular chosen from the orthodontic indexes listed in the definition of an orthodontic index below, preferably an orthodontic index indicating whether
• the user has a horizontal overhang, or “overjet” in English, normal, of preferably between 1 and 3 mm, and/or
• - G user has a normal vertical overhang, preferably between 1 and 3 mm, and/or
• step a) the model acquired with the mobile phone is cut out so as to define a plurality of tooth models, then a so-called 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);
• 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 to the appearance of one or more objects, preferably teeth, represented on the updated image or images is determined, then said information is used to supplement and/or correct said value dimension and/or said aspect value determined from the updated model;
• the acquired model has less than 500 points.
• the invention also relates to:
• step a a computer program, and in particular a specialized application for mobile telephone, comprising program code instructions for the execution of step a), and preferably of step b), and preferably of the 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
• the invention thus relates to a portable scanner, preferably integrated into a portable telephone, able to implement 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).
• user is meant any person for whom a method according to the invention is implemented, whether this person is ill or not, undergoes orthodontic treatment or not.
• Dental care professional means any person qualified to provide dental care, which includes in particular an orthodontist and a dentist.
• An "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 an active orthodontic treatment (passive orthodontic treatment).
• Orthodontic indices are indices which make it possible, in a synthetic way, 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). By way of examples, we can cite: the vertical overjet, the horizontal overjet, the crowding, in particular the Nance index, the deviation of the inter-incisor midpoints, the classes of canine and/or molar occlusions, a irregularity index, in particular Little's index, anterior open bite, lateral open bite, inverted posterior lingual bite, inverted posterior buccal bite, ideal arc length, presence or not of inter-dental space, an index of leveling of the curve of Spee, the presence of a significant rotation, for example greater than 10°, on certain teeth, as well as the combinations of these indices and their evolutions. Examples of orthodontic indices are those used to define the orthodontic index of the American Board of Orthodontics “AB O 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.
• arch or “dental arch”, is meant all or part of a dental arch.
• image is meant a two-dimensional digital representation, such as a photograph or an image taken from a film. An image is made up of pixels.
• Model means a digital three-dimensional model.
• a model is made up of a set of voxels. It conventionally comprises a mesh made up of points connected by straight 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 part of the teeth, preferably for all the teeth represented in the model of the arch, tooth models. Tooth models are therefore models within the arch model.
• a “model of an arch” 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 observer has the impression of observing the modeled object itself.
• the colors of the model are those of the modeled object.
• 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 hyper-realistic.
• the "type" of a modeled 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 with one or more tooth numbers, or an arch subgroup, for example the upper arch.
• a "classification criterion" is an attribute of a modeled object, in particular an arch or a tooth, which makes it possible to classify it.
• the classification criterion can 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.
• a dimension e.g. height, width, concavity, inter-canine distance, inter-premolar width, inter-molar width, arch length or deflection , arch perimeter
• an orthodontic index in particular chosen from the orthodontic indices listed below above, or a combination of these criteria.
• a classification criterion makes it possible in particular to select modeled objects which have similar or identical characteristics.
• she makes it possible to constitute a learning base well adapted 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 having the number 14, it is preferable to train it with a learning base comprising only records relating to teeth number 14. The tooth number is then a classification criterion.
• a "standard configuration” is a positioning of a model, in space, according to a predetermined orientation, with a predetermined scale.
• the two models can be arranged according to the standardized configuration. Normalization methods for laying out and sizing a model in a normalized configuration are well known.
• To compare the shape of two models one can in particular use an iterative search algorithm for the closest point (ICP, or "Iterative Closest Point” in English, described in https://fr.wikipedia.org/wiki/Iterative_Closest_Point ).
• the "splitting" of a model of an arch into “tooth models” is an operation that makes it possible to delimit and make autonomous the representations of the teeth (tooth models) in the model of the arch.
• 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-l0.
• 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 a mean, a standard deviation, or a median value.
• Statistical processing tools are well known to those skilled in the art.
• Methods are well-known optimization methods. In the context of the present invention, they are preferably chosen from the group formed by:
• 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 leaming”, from a learning base.
• a “learning base” is a base of computer records suitable for training a neural network. The quality of the analysis performed by the neural network directly depends on the number of records in the learning base. Conventionally, the learning base comprises 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.
• the training of a neural network consists in confronting it with a learning base containing information on first objects and second objects that the neural network must learn to "match", that is to say to connect to each other.
• the training can be done from a "paired” or “with pairs” learning base, made up of “paired” recordings, that is to say each comprising a first object for the input of the neural network, and a corresponding second object, for the output of the neural network.
• paired the input and the 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 (B AIR) Laboratory, UC Berkeley illustrates the use of a database. paired learning.
• a “reference” has the function of serving 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 is preferably fixed with respect to the model considered. If the model represents an arch, it can for example have its origin at the center of the user's oral cavity.
• 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 conventionally measured 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 transverse direction for the user, which extends from the right to the left of the user.
• 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 conventionally measured 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 direction of the longest dimension of the tooth when viewed from the front, perpendicular to the height direction.
• the direction of the length Z' is the direction perpendicular to the directions Y' and X'.
• each tooth in a dental arch has a predetermined number.
• the tooth numbers defined by this convention are recalled in figure 6.
• a "remarkable point” is a point on an arch or tooth model that can be identified, for example the top of the tooth or at the tip of a cusp, a point of interdental contact, that is ie of a tooth with an adjacent tooth, for example a mesial or distal point of the incisal edge of a tooth, or a point at the center of the crown of the tooth, or “barycentre”.
• An “angulation” is an orientation of the optical axis of the portable scanner relative to the user, during the acquisition of the model in step a).
• a 3D scanner, or “scanner”, is a device that makes it possible to obtain a model of a tooth or a dental arch. He conventionally uses structured light and, starting from different images and, preferably by matching particular points on these images, manages to constitute a 3D model.
• the portable scanner projects the 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.
• the portable scanner projects modulated light onto the patient's teeth while acquiring said images.
• the projected light is then changing and the scanner camera measures the variation of the reflected light over time in order to deduce the distance it travels.
• the phase-modulated technique mention may be made in particular of the phase-modulated technique.
• the images can be of the same type as the images acquired by conventional intraoral 3D optical scanners.
• the images are representations of the observed scene, in this case 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.
• 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 the “acquisition resolution” or “accuracy” of the scanner. The lower the resolution, the more the model is faithful to reality.
• a laser remote sensor 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 an accuracy of less than 5/10 mm (i.e. the maximum difference in shape between the model acquired with the scanner and the real scanned object, at real scale, is less than 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.
• a “mobile phone” or “mobile phone” is a device of the iPhone® type. 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 made it possible to acquire.
• a “retractor” (“retractor” in English), 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 retractor opening and intended to be introduced between the teeth and the lips. In the service position, the lips of the user rest on these edges, so that the teeth are visible through the retractor opening. A retractor thus makes it possible to observe the teeth without being bothered by the lips.
• the teeth do not rest on the retractor, so that the user can, by turning the head relative to the retractor, change the teeth which are visible through the retractor opening. He can also change the distance between his dental arches.
• a retractor does not press on the teeth in such a way as to spread the two jaws apart, but on the lips.
• a retractor is configured to resiliently push the upper and lower lips apart to expose teeth visible through the retractor opening.
• a spacer is configured such that the distance between the upper rim and the lower rim, and/or between the right rim and the left rim is constant.
• the “service position” is the position in which the user acquires the model acquired in step a).
• the bracket is partially inserted into the user's mouth, as shown in Figures 2 and
• 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 where the mouth is open, in which the teeth of the patient's upper and lower arches are not in contact.
• the method (apart from the acquisition operation with the portable scanner) according to the invention is implemented by computer, preferably exclusively by computer.
• Computer means a computer processing unit, which includes a set of several machines, having computer processing capabilities. This unit may in particular be integrated into the portable scanner, or into a mobile telephone 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 located at a dental professional.
• the mobile telephone and the computer then comprise means of communication for exchanging between them, in particular for transmitting the updated model, optionally corrected and/or simplified, and/or one or more dimensional values determined according to the invention.
• a computer comprises in particular a processor, a memory, a man-machine interface, conventionally comprising a screen, a communication module by internet, by WIFI, by Bluetooth® or by the telephone network.
• Software configured to implement a method of the invention is loaded into the memory of the computer.
• the computer can also be connected to a printer.
• reference refers to a model used in step b) to evaluate a dimensional value or an aspect value, or at a time when the object modeled by the reference model is expected to have the shape or the appearance of this model;
• - “correction” refers to a model or an instant used in a preferred correction method; - “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 time, in particular modeling an arch or a tooth of a "historical" person different from the user;
• optical refers to a model which, among a set of models, presents the form closest to the updated model.
• Figure 1 schematically shows an example of a kit according to the invention
• Figure 2 schematically shows the kit according to the invention in a service position, the user being seen from the front;
• Figure 3 shows, schematically, the kit according to the invention in a service position, the user being seen from the side;
• figure 4 represents an acquired model, with three different acquisition resolutions
• Figure 5 is an example of a model acquired, after treatment to cut out tooth models; an example of a tooth model is colored dark gray;
• Figure 6 illustrates the numbering of teeth used in the dental field
• Figure 7 illustrates an acquisition method according to the invention
• Figure 8 illustrates a first correction method according to the invention
• Figure 9 illustrates a second correction method according to the invention
• Figure 10 schematically represents an example of a portable scanner in one embodiment of the invention.
• Figure 11 shows different shots providing additional data.
• identical references are used to designate similar or identical objects.
• the objective of a method according to the invention, illustrated in FIG. 7, is to quickly provide a digital three-dimensional model of an arch of the user, or of a part of this arch, that is to say an "updated model”.
• step a at an updated instant, the user generates, with a portable scanner 6, the “acquired model”.
• the acquired model represents at least 2, preferably at least 3, preferably at least 4 teeth, preferably all the teeth of the arch.
• a portable scanner is an autonomous scanner, in particular in that it incorporates its own energy source, typically a battery, and in that its weight allows it to be handled by hand.
• the portable scanner weighs less than 1 kg, preferably less than 500 g, preferably less than 200 g, and/or more than 50 g.
• 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 of 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 model acquired comprises more than 5,000 and/or less than 200,000, or less than 150,000 points.
• Figure 4 shows examples of Arcade 8 models acquired with a handheld scanner with 5000, 11500, and 154000 points, respectively.
• the portable scanner 6 can be integrated into a portable telephone 12, as in FIG. 1, or be in communication with a portable telephone. 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 actualized instant can be during an orthodontic treatment undergone by the user or apart from any orthodontic treatment.
• the portable scanner is preferably carried by hand by the user.
• it is not immobilized, for example by means of a structure resting on the ground, for example a tripod.
• the user's head is not immobilized.
• the user scans the dental arch without using any device other than the portable scanner.
• he uses a tool to free his lips, and better expose the dental arch to the portable scanner.
• the tool can for example be a spoon introduced into his mouth.
• he uses a retractor and/or a mouth support that he introduces partially into his mouth.
• step a) the user uses a kit 10 comprising the portable scanner 6 and a support 14 (FIG. 1) allowing simultaneously
• the support 14 preferably has the general shape of a tubular body, one opening of which, 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.
• the acquisition aperture also faces a flash of the handheld scanner, allowing it to 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 with respect to the oral opening.
• the data acquired by the portable scanner 6 through its lens, 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.
• the support is configured so that this spacing and this orientation are constant.
• the support 14 comprises:
• tubular spacer 16 which defines the oral opening Oo and preferably comprises a flange 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 241 and 24 2 , as illustrated in FIG. 1, the adapter 18 being rigidly fixed on the spacer 16, preferably in a removable manner, for example by means of a clip 20, or made in one piece with the spacer, so that the lens of the portable scanner can “see” the oral opening.
• the maximum height hn of the flange 22 is preferably greater than 3 mm and less than 10 mm.
• 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 tube 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, on the outside of the latter, which makes it possible to clear the view of the teeth through the oral opening Oo.
• 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 change the distance between his dental arches.
• the support spreads the lips apart, but does not press on the teeth in such a way as to spread the two jaws apart.
• the acquired model can totally or partially represent one dental arch or both dental arches.
• the model of the arch acquired with the portable scanner is cut, preferably to define at least one tooth model 30.
• the updated model is thus reduced to a part of the acquired model. , preferably reduced to a tooth model.
• steps b) and c) are then implemented successively for each tooth model.
• Slicing a model can implement any known slicing process.
• the correction of the updated model consists in modifying it so that it is more in conformity with the object which 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 up.
• Cleaning the model 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 operation of acquisition, in particular to clean saliva artifacts during acquisition.
• the updated model is preferably processed by computer to be corrected.
• the correction of the updated model can be carried out after or before a simplification.
• the updated model is compared to a “correction model”, then corrected according to the results of this comparison.
• 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 attribution to each model historical tooth, tooth number; 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 presenting a maximum proximity with said tooth model to be corrected, or “optimal tooth model”; iv) modification of the tooth model to be corrected on the basis of information relating to the optimal tooth model, the modification possibly comprising a replacement of the tooth model to be corrected by the optimal tooth model.
• a historical library is created comprising preferably more than 2000, preferably more than 5000, preferably more than 10,000 and/or less than 1,0000000 historical tooth models.
• a historical tooth model can be obtained in particular 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, i.e. the tooth models, as in figure 5.
• the historical library therefore contains historical tooth models and the numbers of the teeth modeled by these historical tooth models.
• 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 sufficient to know this rule and the number of a modeled tooth to determine the numbers of the other tooth models.
• the shape of the tooth model to be corrected is analyzed so as to define its number. This shape recognition is preferably carried out by means of a neural network.
• a neural network is used, preferably chosen from the “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 (Red
• the neural network is trained by supplying 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.
• step iii) a search is made in the historical library, among the historical tooth models having the same number as the tooth model to be corrected, for the historical tooth model presenting a maximum proximity with the tooth model to be corrected.
• This historical tooth model is referred to as the “optimal tooth model”.
• Proximity 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.
• the maximum proximity 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 minimum.
• step iv) the tooth model to be corrected is modified based on information relating to the optimal tooth model, which serves as the correction model.
• 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 which face them, and/or the "white" areas of the tooth model to be corrected, that is to say the undefined areas, which face areas of the optimal tooth model which are not white can be replaced by these areas of the optimal tooth model.
• a first distance threshold for example by more than 1 mm
• the modification of the tooth model to be corrected can also consist of replacing the tooth model to be corrected by the optimal tooth model.
• steps i) to iv) are performed for each tooth model cut from the acquired model.
• the above method can be applied to an updated model representing a dental arch.
• the classification criterion of the updated model is adapted accordingly.
• the classification criterion may 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 may in particular be chosen from those which are listed above, in the definition of a classification criterion.
• the updated model can be subjected to a neural network trained for this purpose by means of a learning base.
• the neural network can in particular be chosen from the following networks: Shape Inpainting using 3D Generative Adversarial Network and Recurrent Convolutional Networks (2017), Déformable Shape Completion with Graph Convolutional Autoencoders (2016), Learning 3D Shape Completion Under Weak Supervision (2016) , 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 R
• each record in the learning base can include:
• an incomplete model of an object for example a dental arch, or a tooth model
• the objects modeled in the recordings belong to the same class defined by means of a classification criterion.
• the tooth number of the tooth models is preferably identical for all the records of the learning base.
• a neural network specialized in image generation is used, for example:
• the neural network After having been trained with this learning base, by supplying it, successively for each record, with the incomplete model and at output the corresponding complete model, the neural network can transform an incomplete model into a complete model.
• the complete model serves as the “correction model”.
• the correction model can be used to carry out a quality control during the acquisition of the acquired model, i.e. to check 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(es).
• the model may have roughness or recesses which, in reality, i.e. on the dental arch(es), do not exist.
• the correction of the acquired model can also be used to remove such defects resulting from the acquisition operation.
• a cleaning of the updated model is preferably carried out, independently of the above modification method (steps i) to iv)).
• the objective is to process the updated model to remove the representation of an external object, but also to replace it with a surface representing as faithfully as possible the surface of the arch covered by this object.
• the updated model is cleaned to remove from it the representation of an object external to the user, for example an orthodontic bracket, at least partially masking the object to be modeled, by a tooth, for example, following these steps: i') definition of:
• first certain zone made up of the points of the updated model representing the object to be modeled, for example a tooth, with an accuracy greater than 90%, or “first certain points”, and
• 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 food, a drop of saliva, all or part of a tool.
• the representation of the external object is isolated. More precisely, we identify the points of the updated model which are, in a quasi-certain way, representations of points of the arch.
• a neural network is used, preferably chosen from the “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 the “first certain zone”, constitute a fraction of the updated model. The points of the updated model which are not in the first certain zone together form the “first uncertain zone”.
• 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, it can be provided as input with arcade models 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 that appears if we remove the first uncertain zone.
• step ii′ the first certain area is used to define a surface filling in said first white area. This surface is called “first reconstituted zone”.
• second certain points are also, with great precision, points representing points of the arch. All of these points are called the “second certain zone”. These points are therefore points of the updated model that the analysis of step i') had discarded, but that we retain because they are close to a surface extrapolated from the points that the analysis of step i') had retained.
• the proximity of a point of the first uncertain zone with the first reconstituted zone can be evaluated by measuring the Euclidean distance between this point and this first reconstituted zone. It is considered that a point of the first uncertain zone must enter the second certain zone if this distance is less than a threshold distance.
• 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 reconstituted zone, for example as a function of the mean and the standard deviation of these distances.
• a dynamic calculation with a method of the “3 sigma rule” type can for example be implemented.
• step iii' the objective is to replace the second uncertain zone with a second reconstructed zone that better corresponds to the surface of the arch.
• the first and second certain zones are extrapolated in the region of the second uncertain zone.
• the extrapolation is not based on the first certain zone alone, but on all the first and second certain zones. Tests have shown that this extrapolation thus makes it possible to obtain a second reconstructed zone representing, with high reliability, the surface of the arch.
• 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 up-to-date model, on which the representation of the exterior objects has been removed.
• the updated model is rendered hyper-realistic, preferably by means of a neural network.
• the updated model can be subjected to a neural network trained for this purpose by means of a learning base, as described for example in http://cs230.stanford.edu/projects_winter_2020/reports/32639841.pdf.
• each record in the learning base can include:
• a rough model of an object for example a dental arch, or a tooth model
• the raw models preferably look similar to the refreshed model. They can be scans, preferably made with a scanner identical or similar to the portable scanner used in step a).
• the rough models can for example have been made hyper-realistic by projection of photos.
• the objects modeled in the recordings belong to the same class defined by means of a classification criterion.
• the tooth number of the tooth models is preferably identical for all the records of the learning base.
• a neural network specialized in image generation is used, for example:
• the neural network After having been trained with the learning base, by providing it, successively for each record, 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.
• the updated model 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 any correction, or between two correction treatments.
• the updated model is preferably displayed on a screen, preferably on the screen of the mobile telephone when the latter incorporates the portable scanner and/or on a screen in the cabinet of a dental care professional.
• the portable scanner preferably in the mobile phone incorporating the portable scanner or in communication with an acquisition tool, or
• 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 aspect parameter of the updated model, or "value of aspect ".
• 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 i.e. the raw model as the portable scanner generated it, or
• 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 among
• a dimension of the updated model for example the width, length or height of the dental arch or of a tooth
• a parameter derived from these dimensions and distances for example an orthodontic index, a canine/molar occlusion class, a measurement of a vertical overbite (in English
• overbite or an 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.
• 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, it is possible to compare the shapes and/or the positions of teeth in the updated model and in a reference model.
• An “aspect value” is a value that depends on the surface appearance 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 of the presence of tartar, dental plaque or food on the tooth.
• the aspect value can also be a measure of an aspect difference between the updated model and a reference model. In particular, the aspects of teeth in the updated model and in a reference model can be compared.
• the reference model is chosen according to the intended application.
• 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 as normal at the updated instant.
• the reference model can be representative of a set of individuals, preferably comprising more than 100 individuals, preferably more than 1000 individuals and/or less than 1,0000000 individuals, for example
• 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 aspect which is /that of the anticipated updated object for a reference instant, prior to or after the updated instant or simultaneous to the updated instant.
• the reference instant may in particular be a stage of an orthodontic treatment undergone by the user (for example at the start or at the 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 instants can 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 from a library of historic teeth, as described in EP18184486, equivalent to US16/031,172.
• the reference model is preferably obtained obtained by computer simulation, so that it represents the dental arch in the configuration provided for at the reference time, in particular at the end of an orthodontic treatment or at the updated time.
• an initial model for example generated by means of a scan of a user's arch, preferably generated more than a week before the updated instant, for example at the start of orthodontic treatment.
• the initial model is conventionally cut so as to define tooth models. The movement of the tooth models then makes it possible to simulate the progress of the orthodontic treatment.
• step c) the dimensional value and/or the aspect 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 dimension value and/or the aspect value, and preferably the updated model can be presented to the user, for example by being displayed on the screen of his mobile phone.
• the dimension value and/or the aspect value is/are interpreted, preferably by computer, preferably by a mobile telephone integrating the portable scanner, and a recommendation is presented to the user, preferably on the cell phone screen.
• step a) the user acquires, in addition to the updated model, one or more "updated” images, preferably extra-oral.
• the user uses the mobile telephone implemented to acquire the acquired model.
• the updated images are photographs or images taken from a film. They are preferably in color, preferably in real colors. 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 complements that provided by the acquired model.
• the information may in particular relate to a dimension and/or to the appearance of one or more objects, preferably teeth, represented on the updated image or images.
• 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.
• 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 the updated images thus makes it possible to detect, and to follow 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 on the updated model, they thus make it possible to color the surface of the updated model in a very realistic way.
• the set of updated images can include 6 images representing the dental arches “front views”, “front-right views “, “right views”, “front-left views”, “left views” and “bottom views”, respectively.
• At least one updated image is acquired facing the user (front view).
• at least one updated image is acquired from the right of the user, and at least one updated image is acquired from the left of the user.
• 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.
• the updated images are processed to generate a said correction model and/or a said reference model.
• all conventional techniques can be implemented.
• the method can be implemented independently of any orthodontic treatment, in particular to monitor that the position and/or the shape of the teeth are not "abnormal", that is to say when they do not respect a therapeutic standard or aesthetic. Preferably, an appointment with a dental professional should then be made.
• the method can be implemented before orthodontic treatment.
• the method can be implemented in particular to acquire the position and the anatomy of the teeth of the future patient and to launch the manufacture of an interceptive orthodontic appliance or a custom-made orthodontic appliance, by example of transparent orthodontic splints, or design an individualized treatment with arches and brackets.
• the method can be implemented during an 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 the treatment, that is to say after the installation of a device intended to correct the positioning of the user's teeth, known as an “active retention device”.
• the method can be implemented to acquire an updated model of the teeth and allow the fabrication of a new orthodontic appliance, for example an implant, an orthodontic splint, or a vestibular orthodontic appliance .
• 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 him establish a diagnosis.
• 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 a device intended to maintain the teeth in position, called "passive retainer".
• the dimensional value is preferably used for
• the aspect value is preferably used to detect or evaluate a position or a shape of a stain or a cavity.
• both the dimensional value and the aspect value are used.
• the method can thus be used for precise and localized monitoring of the evolution of certain pathologies, in particular stains, demineralizations, or caries.
• 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, except 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, ie extra-orally.
• the processing of 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.
• the acquired model in step a), is coarse. It may in particular represent a "3D skeleton" of the dental arch(es) of the user, 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.
• the processing of 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(es).
• the portable scanner is partially inserted into the user's mouth.
• the intrados of the teeth can be scanned.
• the portable scanner 6 preferably comprises a portable telephone 12 and an acquisition tool 31 in communication with the portable telephone, preferably over the air, preferably via Bluetooth®. Cable communication is also possible.
• the acquisition tool is provided with an acquisition head 32 which can be introduced into the mouth of the user.
• 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 model acquired from said signal.
• the acquisition tool does not include a physical link with the mobile phone or is connected to the mobile phone by a flexible link, for example a cable.
• the acquisition tool comprises a handle 34 facilitating its manipulation, by the user himself or one of his relatives, for example in the manner of a toothbrush.
• the acquisition tool is attached to the mobile telephone, 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.
• the acquisition tool can be attached to a phone case.
• the method further implements a measuring head in communication with the mobile telephone and which is introduced into the mouth of the user 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 palatal median suture the soft tissues (aphtha, benign or malignant lesions, recessions, etc.) the color of the teeth the presence of cavities or stains the condition and/or shape of the implants , crowns and/or bridges the condition of the vestibular or lingual treatment devices (e.g.: lingual, vestibular brackets, maxillary expander or any other treatment aid) or restraint (palatine arch) the distances between the different parts of the same vestibular, lingual or any other auxiliary appliances condition of the anchoring devices (mini-screw type) distance between the anchoring devices and the appliances present in the mouth of the soft tissue stitches post-surgery soft tissue healing the curve of spee the wilson curve the intercanine distance the intermolar distance
• Figure 11 shows different images providing additional data, in particular on the palate, including a median palatal suture (image 1), soft tissue sutures (image 2), distances between the different parts of the same vestibular appliance , lingual or any other auxiliary (images 3 and 4), the condition and/or the 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 appliances present in the mouth (image 6), the condition of the vestibular or lingual treatment appliances (for example lingual, vestibular brackets, maxillary disjunctor or any other treatment aid) or contention (palatine arch) (image 7), interdental space and post-surgery soft tissue healing (image 9), lingual surfaces of teeth (image 10), intercanine distance and intermolar distance (image 10), the shade of the teeth (image 11), the curve of Spee (image 12), the curve of Wilson (image 13), and the presence of cavities or stains (image 14).
• image 1 a median pala
• 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 up and/or rendered 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.
• the invention also relates to a method for acquiring at least one image of at least one dental arch of a user by means of a mobile phone. and an acquisition tool comprising an acquisition head provided with a camera, preferably able to be introduced into the mouth of the user, a process in which the acquisition head:
• Said at least one image is preferably a photo, preferably a photo representing the dental arch realistically, as a person would observe it directly.
• the image can be used to generate a model as in step a), but the image acquisition method according to the invention is no longer limited to this particular embodiment, the image being able to be used for other purposes. This method is therefore referred to below as a “generalized method”.
• step a Insofar as a characteristic described above for step a) is technically compatible with the generalized method, it can however be applied to this method.
• the mobile phone and the acquisition tool are preferably handled exclusively by the user.
• the acquisition can be performed extraorally, the camera of the acquisition tool not entering the mouth of the user. Acquisition can be performed intraorally, with the camera of the acquisition tool entering the user's mouth.
• the acquisition tool is attached to the mobile telephone, 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.
• the acquisition tool can be attached to a phone case.
• the mobile phone and the acquisition tool communicate with each other, but are movable independently of each other.
• no rigid device preferably no mechanism connects the mobile phone and the acquisition tool together so that the mobile phone can be moved in space, preferably in all dimensions of space, without necessarily bringing the acquisition tool with it.
• the screen displays the scene observed by the camera of the acquisition head.
• 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 viewing being hindered by manipulation of the acquisition head.
• the user observes the screen of the mobile phone, the mobile phone preferably being immobile 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.
• this embodiment advantageously allows the user to use the camera of the mobile telephone arranged on the side opposite the screen, without having to use a mirror.
• the user acquires at least one image seen from the front, preferably at least one image from the right of the user, and, more preferably, at least one image from the left of the user.
• the user acquires at least one open mouth image and at least one closed mouth image.
• the set of images acquired 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.
• the user uses a tool to release his lips, and better expose the dental arch to the camera of the acquisition tool.
• the tool can for example be a spoon introduced into his mouth.
• he uses a retractor that he introduces partially into his mouth.
• the generalized method comprises, after said acquisition, an analysis of said image in order to define the dental situation of the user, and preferably to design an active or passive orthodontic treatment plan, and/or to check the proper progress of active or passive orthodontic treatment in progress.
• the acquisition method comprises, after said analysis of said image, the manufacture of an orthodontic device, for example an orthodontic gutter, and preferably the sending of said orthodontic device to the user.
• an orthodontic device for example an orthodontic gutter
• the acquisition method comprises, after said analysis of said image, the manufacture of an orthodontic device, for example an orthodontic gutter, and preferably the sending of said orthodontic device to the user.
• the uses mentioned above for the updated images can also be applied to the image or images acquired according to the generalized method.
• Said at least one image is preferably used to
• Figure 12 illustrates a device 6' for the implementation of such an image acquisition process.
• This kit includes a 12' mobile phone and a 31' acquisition tool in communication with the mobile phone, preferably over the air, preferably via Bluetooth® or WiFi. Cable communication is also possible.
• the acquisition tool 31' is provided with an acquisition head 32' which can be introduced into the mouth of the user.
• the acquisition head comprises a camera 33' which acquires the image and transmits it to the mobile telephone 12', or acquires a signal and transfers it to the mobile telephone 12' so that the latter generates the image from said signal.
• the acquisition tool does not include a physical link with the mobile telephone or is linked to the mobile telephone by a flexible link, for example a cable.
• the acquisition tool comprises a handle 34' facilitating its manipulation, by the user himself or one of his relatives, for example in the manner of a toothbrush.
• the mobile phone 12 may include one or more of the characteristics of the mobile phone 12. Preferably, it is not fixed to any support, and in particular to any support fixed to the user like the support 10 described above, and the user can manipulate it freely.

Landscapes

• Health & Medical Sciences (AREA)
• Life Sciences & Earth Sciences (AREA)
• Engineering & Computer Science (AREA)
• Physics & Mathematics (AREA)
• Surgery (AREA)
• General Health & Medical Sciences (AREA)
• Medical Informatics (AREA)
• Animal Behavior & Ethology (AREA)
• Biomedical Technology (AREA)
• Public Health (AREA)
• Molecular Biology (AREA)
• Veterinary Medicine (AREA)
• Biophysics (AREA)
• Heart & Thoracic Surgery (AREA)
• Pathology (AREA)
• Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
• Radiology & Medical Imaging (AREA)
• Artificial Intelligence (AREA)
• Optics & Photonics (AREA)
• Dentistry (AREA)
• Oral & Maxillofacial Surgery (AREA)
• Theoretical Computer Science (AREA)
• General Physics & Mathematics (AREA)
• Computer Vision & Pattern Recognition (AREA)
• Signal Processing (AREA)
• Rheumatology (AREA)
• Fuzzy Systems (AREA)
• Orthopedic Medicine & Surgery (AREA)
• Audiology, Speech & Language Pathology (AREA)
• Multimedia (AREA)
• Quality & Reliability (AREA)
• Evolutionary Computation (AREA)
• Physical Education & Sports Medicine (AREA)
• Mathematical Physics (AREA)
• Physiology (AREA)
• Psychiatry (AREA)
• Computer Graphics (AREA)
• Geometry (AREA)
• Software Systems (AREA)
• Dental Tools And Instruments Or Auxiliary Dental Instruments (AREA)

Applications Claiming Priority (2)

Publications (1)

Family

ID=89076571

Family Applications (1)

Country Status (5)

• 2022
  • 2022-05-24 EP EP22732920.8A patent/EP4348572A1/de active Pending
  • 2022-05-24 KR KR1020237044714A patent/KR20240013207A/ko unknown
  • 2022-05-24 CN CN202280052170.7A patent/CN117769721A/zh active Pending
  • 2022-05-24 BR BR112023024686A patent/BR112023024686A2/pt unknown
  • 2022-05-24 AU AU2022281999A patent/AU2022281999A1/en active Pending

Also Published As

Similar Documents

Legal Events