Manufacture of a retainer

Abstract

The invention relates to a process for manufacturing a retainer, said process comprising the following steps: a) at an update time, after the end of an orthodontic treatment, acquiring at least one two-dimensional image of at least one portion of a dental arch of a user, called the "updated image", by means of an image-acquiring apparatus; b) generating a digital three-dimensional model representing the dental arch of the user, called the "updated model", based on the updated image; c) designing, based on the updated model and preferably by computer, a retainer suitable for keeping teeth in their configuration at the update time; d) manufacturing the retainer.

Description

[0001] Description

[0002] Title: Manufacture of a retention device

[0003] Technical field

[0004] The present invention relates to methods and devices for the design and manufacture of orthodontic retaining appliances.

[0005] State of the art

[0006] After orthodontic treatment, the position of the teeth may change unfavorably. This unfavorable development is generally referred to as "relapse." Typically, the patient visits their orthodontist at regular intervals for checkups. They may also visit their dentist, who can detect any imperfections in the positioning of the teeth.

[0007] However, many patients do not attend these check-ups, which would allow for the detection of possible relapses. The teeth can thus return to a malocclusion position which, to be corrected, requires new orthodontic treatment, which can be as extensive as the initial treatment.

[0008] Visits are burdensome for the patient and a source of stress for the orthodontist. Patent application US 2018 / 0204332 describes a method to partially solve this problem. However, at the end of orthodontic treatment, it is necessary to acquire at least one digital three-dimensional reference model of the patient's arches. The patient is therefore forced to travel to the orthodontist.

[0009] In order to prevent the position of the teeth from changing unfavorably, and therefore limit the number of appointments, the patient may be required to wear a retainer to maintain the position of the teeth obtained at the end of the orthodontic treatment.

[0010] The retainer is typically an orthodontic retaining splint or a retainer arch consisting of a wire forming an arch and fixed against the teeth, generally glued against the lingual surfaces from canine to canine. The shape of the orthodontic appliance is typically determined by the orthodontist by acquiring a 3D scan of the patient's dental arch after the end of orthodontic treatment. Acquiring a 3D scan of the patient's dental arch is restrictive and requires the patient to move around.

[0011] There is a need to facilitate the determination and manufacture of orthodontic retainer appliances following orthodontic treatment.

[0012] One aim of the invention is to meet, at least partially, these needs.

[0013] Statement of the invention

[0014] Summary of the invention

[0015] The invention aims to meet all or part of these needs and achieves this, according to one of its aspects, by means of a method for manufacturing a retention appliance comprising the following steps: a) preferably, at an updated time, at the end or after the end of an orthodontic treatment, acquisition of at least one two-dimensional image of at least part of a dental arch of a user, called an "updated image", by means of an image acquisition device, preferably several updated images are acquired; b) generation of a digital three-dimensional model representing the dental arch of the user, called an "updated model", preferably from the updated image; c) design of a retention appliance, from the updated model the retention appliance being designed so as to maintain the configuration of the teeth at the updated time when it is positioned on said teeth; d) manufacturing of the retention appliance.

[0016] Preferably, in step b) the updated model is obtained by deformation, from the updated image, of a digital three-dimensional model of the user's dental arch, called the "reference model", acquired before step a). The reference model is deformed, from the updated image, until an updated model representing the dental arch in a configuration compatible with the configuration of the dental arch as represented in the updated image is obtained.

[0017] As will be seen in more detail in the remainder of the description, the updated image can be taken outside the orthodontic practice and the reference model can have been generated before or during the orthodontic treatment. In particular, no intraoral scan is necessary, after the orthodontic treatment, in order to manufacture the retainer. The retainer can thus be determined and manufactured without the user having to travel to the dental professional after the end of the orthodontic treatment, or even without having to see the dental professional.

[0018] A method according to the invention thus advantageously makes it possible to limit the number of appointments with the dental care professional.

[0019] A method according to the invention may comprise one or more of the following optional features:

[0020] - the retention device is a retention arch or an orthodontic retaining splint, preferably a retention arch;

[0021] - several updated images are acquired, preferably 3, preferably 4, preferably 5;

[0022] - several updated images are acquired according to different acquisition angles, the updated images comprising in particular preferably at least one image on the right in relation to the user, at least one image on the left in relation to the user, at least one image facing the user;

[0023] - the updated image is acquired by the user or one of his relatives;

[0024] - the acquisition in step a) takes place outside an orthodontic or dental practice, preferably at the user's home;

[0025] - the image acquisition device is a mobile phone;

[0026] - a dental retractor and / or an image acquisition kit, for example as described in EP 3 391 810, is used in step a);

[0027] - the image acquisition kit has the form of a box on which the image acquisition device is fixed;

[0028] - the housing has the shape of a tube comprising a first opening intended to be positioned in the user's mouth and a second opening intended to be fixed to the image acquisition apparatus so that the image acquisition apparatus acquires at least one image of the user's teeth through said openings;

[0029] - in step b), the updated model is obtained by deformation, from the updated image, of a digital three-dimensional model of the user's dental arch, called the “reference model”, acquired before step a);

[0030] - the reference model is made from a digital three-dimensional model, preferably from a digital three-dimensional model acquired before the start of orthodontic treatment or during orthodontic treatment, for example by means of a 3D scanner;

[0031] - the reference model is an updated model, called a “historical updated model”, resulting from the implementation of a method according to the invention, the historical updated model having preferably been recorded in a database after step b);

[0032] - the reference model is a digital three-dimensional model of the user's dental arch generated at the start of orthodontic treatment, in particular for modeling the dental arch at a stage of orthodontic treatment, or during orthodontic treatment, for example more than 2 weeks or more than one month before stage b);

[0033] - preferably, the reference model represents the user's dental arch in a desired theoretical configuration at an intermediate moment of the orthodontic treatment or at a final moment of the orthodontic treatment;

[0034] - preferably, the reference model represents the dental arch in a final configuration corresponding to the theoretical configuration desired at the end of the orthodontic treatment;

[0035] - the deformation of the reference model is carried out by means of a metaheuristic method or by means of a neural network;

[0036] - in step b), preferably before step b), preferably in step a), more preferably before step a), the reference model is cut into tooth models, the deformation comprising a displacement of the tooth models equal to the difference in positioning of the teeth between the configuration of the teeth in the reference model and the configuration of the teeth in the updated image;

[0037] - in step b) or preferably before step b), preferably in step a), more preferably before step a), at least one neural network is trained, from a learning base, to determine an updated model at the output of the neural network, from a reference model and an updated image submitted as input to the neural network, the learning base consisting of historical images and first historical models, similar respectively to the updated image and to the reference model, and second historical models, similar to the updated model as expected at the output of the neural network;

[0038] - in step b), the updated model is obtained without resorting to a reference model, in particular by assembling tooth models chosen according to the updated images;

[0039] - in step c), the design of the orthodontic appliance involves determining the curvature of a retention arch;

[0040] - preferably, the retention arch is determined so as to adapt to the shape of the teeth on which the retention arch is intended to be applied, the retention arch being conventionally intended to be fixed on an intrados surface of the user's teeth;

[0041] - steps b) to c) are implemented by computer, preferably automatically, i.e. without operator intervention, or under the supervision of an operator, for example a technician or a dental care professional;

[0042] - step d) is carried out using a 3D printer;

[0043] - the method according to the invention comprises, after step d), the following step e): e) sending the retention device to the user or dental care professional.

[0044] In one embodiment, the updated model is obtained by implementing a method for modeling a dental arch, preferably by a mobile phone of the user, said modeling method comprising the following steps:

[0045] 1) analyzing the updated image so as to determine at least one tooth area and at least one tooth attribute value associated with said tooth area, preferably a type or number of the tooth to which the tooth area belongs;

[0046] 2) for each tooth area determined in step 1), search, in a historical library comprising more than 1000 tooth models associated with said tooth attribute value, called “historical tooth models”, for a historical tooth model having maximum proximity to the tooth area, called “optimal tooth model”;

[0047] 3) arrangement of all optimal tooth models in such a way as to create a model that has maximum concordance with the updated image, i.e. the updated model.

[0048] The modeling method preferably comprises one or more of the following characteristics:

[0049] - steps 1) and 2) of the modeling method are implemented for several updated images, and, preferably, in steps 2) and 3), optimal tooth models are sought and a model assembled so as to obtain maximum concordance with respect to all the updated images; - the attribute of a tooth is chosen from the type of the tooth, the number of the tooth, the thickness of the tooth, the height of the crown of the tooth, the mesio-palatal width of the tooth, the index of deflection in mesial and distal of the incisal edge of the tooth, a tooth color, a tooth shape, a tooth contour, a clinical state of the tooth, for example "decayed tooth", "broken tooth", a relative position of the tooth with respect to another tooth, or with respect to a reference frame fixed with respect to the arch, and the combinations of these attributes;

[0050] - several tooth attributes are associated with the tooth area and historical tooth models;

[0051] - in step 2), the proximity is a shape proximity assessed by the difference between the shape of the tooth represented on the tooth area and the shape of the historical tooth model, preferably by the shape difference between the tooth area and a view of the historical tooth model which has the shape closest to that of the tooth area;

[0052] - the view of the historical tooth model that has the shape closest to that of the tooth zone is sought using a metaheuristic method, preferably evolutionary, preferably by simulated annealing, or by a neural network.

[0053] In one embodiment, the reference model that is deformed to obtain the updated model is a model generated by the user, preferably with their mobile phone.

[0054] The user can in particular implement, at a time prior to the updated time, for example at a stage of the orthodontic treatment, the modeling method described above, to define, from “prior” updated images, an “prior” updated model and use this prior updated model as a reference model.

[0055] To produce the updated model, or a so-called reference model, the user can also perform a scan of said dental arch using a portable scanner, for example of the LIDAR type, preferably a LIDAR from his mobile phone, or by analyzing a series of images representing a light mark. In particular, he can implement, preferably with his mobile phone, a method for generating a digital three-dimensional model of a dental arch comprising the following steps:

[0056] I) projection of at least one light beam onto the user's dental arch, so as to draw at least one light mark on the arch;

[0057] II) simultaneously with step I), movement of the dental arch through the beam and acquisition, during said movement, of a series of “marked” images of said arch each showing a representation of the projected mark, or “projection”;

[0058] III) identification of said projection on each marked image, then production of a digital three-dimensional model presenting maximum concordance with the set of projections.

[0059] In one embodiment, the generation method is performed before the updated time to generate a reference model and the updated images are used to update the reference model.

[0060] In one embodiment, the generation method is performed at the updated time to generate a reference model and the updated images are used to correct possible errors in the reference model.

[0061] Preferably, steps b) to e) are implemented by computer, preferably automatically, i.e. without operator intervention, or under the supervision of an operator, for example a technician or a dental care professional.

[0062] Preferably, when the retainer is a retainer arch, the retainer is sent to the dental professional.

[0063] When the retention device is a retention arch, the method preferably comprises,

[0064] - in design step c), designing, from the updated model, an orthodontic transfer splint intended to contain the retention appliance and an adhesive substance so that when the orthodontic transfer splint is positioned on the user's teeth, the retention appliance is positioned and fixed on the user's teeth, in a position allowing the configuration of the user's teeth to be maintained at the updated time; and

[0065] - at step d) of manufacturing the retention arch, the manufacturing of the orthodontic transfer splint.

[0066] The adhesive substance may be made of a composite material. Preferably, the adhesive substance comprises a combination of inorganic particles coated with silane and dimethacrylic resin, for example of the type "ENAMEL plus HRI Flow HF". The adhesive substance may comprise composites comprising "Bis GMA" and / or "Bis EMA", for example "Braceplaste". In step e), the retention arch may be sent into the orthodontic transfer tray, preferably to the dental professional or to the user, preferably to the dental professional.

[0067] The invention also relates to a computer program product comprising instructions which, when the program is executed by a computer, cause the latter to implement the following steps: a') reception of at least one two-dimensional image, representing a dental arch of a user after the end of an orthodontic treatment, called "updated image"; b) generation of a digital three-dimensional model representing the dental arch of the user, called "updated model", from the updated image, preferably the generation of the updated model is carried out by deformation, from the updated image, of a digital three-dimensional model of the dental arch of the user, acquired before step a'), called "reference model"; c) design of a retention appliance from the updated model; the updated image received in step a') being acquired by means of the image acquisition apparatus.

[0068] Preferably, the computer program product comprises, after step c), a step d) comprising sending manufacturing instructions, preferably via digital communications, to a manufacturer of orthodontic appliances or directly to a manufacturing device, for example a 3D printer.

[0069] The invention also relates to:

[0070] - a computer program product according to the invention,

[0071] - a computer medium on which such a product is recorded, for example a memory or a CD-ROM, and

[0072] - a computer in which such a product is loaded.

[0073] The medium may include computer memory, a hard drive or a CD-ROM.

[0074] The invention also relates to a kit for designing a restraint device comprising:

[0075] - an image acquisition device, preferably a mobile phone,

[0076] - a computer program product according to the invention, preferably recorded on a medium and loaded into a computer, optionally comprising a code for the step of sending manufacturing instructions; the image acquisition device being in communication with the computer so as to transmit to it the updated image that it has acquired.

[0077] The computer program product may be a specialized application installed on the image acquisition device, the image acquisition device preferably being a mobile phone.

[0078] The kit may also include a device for manufacturing an orthodontic appliance, for example a 3D printer, configured to receive instructions for manufacturing the retention appliance transmitted by the computer executing the computer program product.

[0079] The kit may also include a transport vehicle, intended to transport the retention device from a manufacturing site of said retention device to a delivery site of said retention device, the delivery site preferably being the user's home and / or the office of the user's dental care professional.

[0080] Definitions

[0081] By "user" is meant any person for whom a method according to the invention is implemented, whether this person is ill or not.

[0082] A “dental care professional” means any person qualified to provide dental care, which includes in particular an orthodontist and a dentist.

[0083] An "orthodontic treatment" is all or part of a treatment intended to modify a patient's dental configuration. A treatment intended to maintain the dental configuration (retention treatment) is not considered an orthodontic treatment.

[0084] A 3D scanner, or "scanner," is a device that produces a 3D model of a dental arch.

[0085] An "updated instant" is an instant during which the updated image(s) are acquired. The duration of this instant is short enough that the configuration of the teeth does not change significantly during this time.

[0086] A "model" means a digital three-dimensional model. A model consists of a set of voxels. A "model of an arch" is a model representing at least a portion of a dental arch, preferably at least 2, preferably at least 3, preferably at least 4 teeth. Figure 3 is an example of an arch model.

[0087] A "tooth model" is a three-dimensional digital model of a tooth in a user's arch. A model of an arch can be sliced ​​so as to define tooth models for at least some of the teeth, preferably for all the teeth represented in the model of the arch. The tooth models are therefore models within the model of the arch. Figure 4 illustrates an example of an arch model sliced ​​into tooth models.

[0088] A "scenario" is a sequence of models of an arch that represent successive arch configurations. In particular, a "treatment scenario," or "treatment plan," includes models that represent configurations of an arch at different times during its treatment. These times are typically the initial time, before the start of treatment, intermediate times during treatment, and the final time, at the end of treatment. Each model of a scenario representing the arch in its planned configuration at an intermediate time is called an "intermediate model." Figure 2 illustrates an example of a treatment scenario.

[0089] A "match" or "fit" between two objects is a measure of the difference between these two objects. A match is maximal ("best fit") when it results from an optimization that minimizes the said difference.

[0090] In particular, an updated image is maximally consistent with a model when a view of that model provides an image that is maximally consistent with the updated image.

[0091] A "tooth area" is an area of ​​an image that represents, at least partially, a tooth.

[0092] A "historical tooth model" is a tooth model enriched with its description.

[0093] 'Proximity' is a measure of one or more differences between the historical tooth model and the tooth zone. These differences may include a difference in shape, but also other differences such as a difference in translucency or color. Maximum proximity can be sought by minimizing several differences in succession, or by minimizing a combination of these differences, for example a weighted sum of these differences. 'Proximity' is therefore a broader concept than 'concordance', with concordance only measuring relative proximity in shape.

[0094] The configurations of the arch at the intermediate and final instants are theoretical because they result from a simulation for a future instant. They are therefore anticipated, or "predicted," and may therefore differ from reality at the intermediate or final instant. Visualizing the models of a scenario, chronologically, allows the effect of the arch treatment to be simulated.

[0095] An arch configuration is said to be "real" when it is that of the user's arch in reality. An arch configuration is said to be "theoretical" when it is that of the user's arch as "simulated", "planned" or "desired" for a future instant.

[0096] 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 treatment scenario.

[0097] An "image" means a two-dimensional image, such as a photograph or a frame from a film. An image is made up of pixels.

[0098] The "acquisition conditions" specify the position in space, the orientation in space and the calibration, for example the values ​​of the diaphragm opening and / or the exposure time and / or the focal length and / or the sensitivity,

[0099] - of a real image acquisition device, relative to a dental arch of the user (real acquisition conditions) or

[0100] - a virtual image acquisition device, relative to a model of the user's dental arch (virtual acquisition conditions).

[0101] The "calibration" of an acquisition device consists of all the values ​​of the calibration parameters. A calibration parameter is a parameter intrinsic to the acquisition device (unlike its position and orientation) whose value influences the acquired image. For example, the aperture is a calibration parameter that modifies the depth of field. The exposure time is a calibration parameter that modifies the brightness (or "exposure") of the image. The focal length is a calibration parameter that modifies the angle of view, that is, the degree of "zoom". "Sensitivity" is a calibration parameter that modifies the reaction of the sensor of a digital acquisition device to incident light.

[0102] Preferably, the calibration parameters are chosen from the group formed by diaphragm aperture, exposure time, focal length and sensitivity.

[0103] An observation of a model, under specific virtual acquisition conditions, in particular with a virtual acquisition device calibration, at a specific angle and distance, is called a "view".

[0104] By "image of an arch", "view of an arch", "representation of an arch", "scan of an arch", or "model of an arch" is meant an image, a view, a representation, a scan or a model of all or part of said dental arch.

[0105] A model of a user's dental arch is "compatible" with an image when there is a view of this model which corresponds to said image, that is to say such that the representations of the teeth on the view are positioned, relative to each other, like the representations of the teeth on the image. The contours of the models of teeth represented on the view are therefore substantially superimposable in register with the contours of the representations of said teeth on the image.

[0106] This view of the model can also be described as “compatible”, or “superimposable in register”, with the said image.

[0107] A "light mark" is the result of the interaction between a light beam and a dental arch. A light mark can be a point, a line, a band, or a set of points and / or lines and / or bands. A line can therefore be continuous or locally interrupted and made up of pieces of lines. It can have a constant or variable width. The representation of a light mark, particularly on an updated image, varies depending on the direction of observation of this mark.

[0108] The term "light" includes all electromagnetic waves from infrared to ultraviolet.

[0109] Metaheuristic methods are known optimization methods. They are preferably chosen from the group formed by

[0110] - evolutionary algorithms, preferably chosen from: evolutionary 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;

[0111] - the kangaroo algorithm, the Fletcher and Powell method, the noise method, stochastic tunneling, random restart hill climbing, the cross-entropy method, and

[0112] - hybrid methods between the metaheuristic methods cited above.

[0113] Deep learning devices, known as "deep learning" algorithms, are well known to those skilled in the art. They include "neural networks" or "artificial neural networks."

[0114] A person skilled in the art knows how to choose a neural network, depending on the task to be performed. In particular, a neural network can be chosen from:

[0115] - networks specialized in image classification, called “CNN” (“Convolutional neural network”), for example AlexNet (2012), ZF Net (2013), VGG Net (2014), GoogleNet (2015), Microsoft ResNet (2015), Caffe: BAIR Reference Caff eNet, BAIR AlexNet, Torch VGG CNN S, VGG CNN M, VGG_CNN_M_2048, VGG_CNN_M_1024, VGG CNN M 128, VGG CNN F, VGG ILSVRC-2014 16-layer, VGG ILSVRC-2014 19-layer, Network-in-Network (Imagenet & CIFAR-10), Google: Inception (V3, V4);

[0116] - networks specialized in localization and detection of objects in an image, Object Detection Networks, for example 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.), 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, YOL09000 (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, ComerNet (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 and al.), 2012;.

[0117] - networks specialized in image generation, 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).

[0118] The above list is not exhaustive.

[0119] Training a neural network involves confronting it with a learning base containing information on the two types of object that the neural network must learn to "match", that is, to connect one to the other.

[0120] Training can be done from a learning base made up of recordings each comprising a first object of a first type and a corresponding second object of a second type.

[0121] Alternatively, training can be done from a learning base consisting of records each containing either a first object of a first type, or a second object of a second type, each record however containing information relating to the type of object it contains. Such training techniques are for example described in the article by Zhu, Jun-Yan, et al. "Unpaired image-to-image translation using cycle-consistent adversarial networks.", 2017 IEEE International Conference on Computer Vision (ICCV).

[0122] Training the neural network with these recordings teaches it to provide, from any object of the first type, a corresponding object of the second type.

[0123] The quality of the analysis performed by the neural network directly depends on the number of records in the training base. Preferably, the training base has more than 10,000 records.

[0124] The term "computer" refers to a computer processing unit, which includes a set of several machines with computer processing capabilities. This unit may be integrated into a mobile phone, or be a PC-type computer or a server, for example a server remote from the user, for example being the "cloud" or a computer located at a dental professional's premises. The image acquisition device and the computer then include means of communication to exchange information between them, in particular to transmit the updated image(s).

[0125] Conventionally, a computer comprises in particular a processor, a memory, a human-machine interface, conventionally comprising a screen, a communication module via the internet, WIFI, Bluetooth® or 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, for example a 3D printer.

[0126] “Understand,” “comprise,” or “present” shall be interpreted broadly, without limitation, unless otherwise indicated.

[0127] Brief description of the drawings

[0128] Other characteristics and advantages of the invention will become apparent upon reading the detailed description which follows and upon examining the attached drawing, provided for illustrative and non-limiting purposes. In the attached drawing:

[0129] [Fig 1] schematically illustrates a manufacturing method according to the invention;

[0130] [Fig 2] represents a treatment scenario;

[0131] [Fig 3] illustrates an example of a dental arch model;

[0132] [Fig 4] illustrates an example of an arch model cut into tooth models;

[0133] [Fig 5] shows a diagram of a kit according to the invention;

[0134] [Fig 6] shows a diagram of a deformation step of a reference model according to the invention.

[0135] Detailed description

[0136] Figure 1 illustrates an example of a manufacturing method according to the invention. This manufacturing method comprises steps a) to d), preferably steps a) to e).

[0137] In step a), an updated image 22, preferably a photo, representing a dental arch of a user, is acquired by means of an image acquisition device 20, in order to update a reference model 32 representing said dental arch of the user. Alternatively, the acquisition of the updated image is carried out by acquiring a video, the dental arch of the user being filmed by means of the image acquisition device. The updated image can be extracted from this video.

[0138] Step a) is carried out at an updated time, the updated time being after orthodontic treatment. Preferably, the acquisition is carried out less than six months, preferably less than three months, preferably less than one month, and more preferably immediately after the end of the orthodontic treatment.

[0139] The acquisition in step a) can be carried out by the user, a relative or a dental professional. Preferably, the acquisition is carried out by the user himself.

[0140] The image acquisition device 20 may be a mobile phone, a tablet, a camera or a computer, the image acquisition device preferably being a mobile phone.

[0141] Preferably, several updated images 22 are acquired. The updated images may include a front view image, a left view image, and a right view image. The updated images may be taken for the upper arch, the lower arch, or both. The updated images may be taken with the user's mouth open or closed. Preferably, the updated images are in color, preferably in realistic color.

[0142] In step b), an updated model 42 is generated from the updated image acquired in step a), the model being generated without the user needing to be physically present in the dental office, preferably the user is not physically present in the dental office.

[0143] Several methods can be implemented.

[0144] In one embodiment, the updated model is generated directly from the updated image(s), preferably with at least one neural network.

[0145] The at least one neural network is pre-trained so that the neural network learns to provide an updated model as output, from one or more updated images provided as input. The training is carried out using a training base comprising historical images and historical models, the historical images being comparable to updated images, and the historical models being comparable to updated models. A historical model can be acquired using a 3D scanner substantially at the time at which the corresponding historical image was acquired, or can be generated manually. A recording of the training base can comprise a historical image as a first object and a historical model as a second object. The neural network can be told that for a first object comprising a historical image, it must match a second object comprising a historical model.In particular, to train the neural network, it will be provided with a set of first objects and a set of second objects so that it learns to match a first object with a second object. Once trained, the neural network is then able to determine an updated model as output, when it is provided with an updated image as input.

[0146] Preferably, the first object comprises a plurality of updated images, the at least one neural network being trained to generate, as output, an updated model from a plurality of updated images provided to it as input.

[0147] The at least one neural network can be a reconstruction neural network, that is to say an “occupancy network” type neural network.

[0148] The occupancy network is trained to output a 3D model of at least a portion of a dental arch constructed from a plurality of updated images representing the at least a portion of the dental arch. Preferably, an occupancy network only takes as input updated images representing at least a portion of the user's dental arch.

[0149] In another embodiment, a reference model 32 is determined. The reference model can be selected manually, for example from a set of 3D models stored in a database 30, representing the user's dental arch. Preferably the reference model is determined automatically, i.e. without human intervention, preferably by computer.

[0150] The selected reference model 32 is preferably an intermediate model or a final model, created when determining the orthodontic treatment scenario. An orthodontic treatment scenario is illustrated in Figure 2. The reference model 32 preferably corresponds to a 3D model acquired before the start of the orthodontic treatment by means of a 3D scanner, also called an “initial model”, which has been modified to represent the theoretical configuration of the teeth at an intermediate time of the orthodontic treatment, also called an intermediate model, or at the final time of the orthodontic treatment, also called a final model. Preferably, the reference model corresponds to the final model.

[0151] The reference model can be selected from a database. Alternatively, the reference model can be sent, for example, by the dental professional or technician, via digital communication, preferably via a specialized application.

[0152] The reference model 32 is then deformed to obtain an updated model 42 representing the configuration of the user's teeth at the updated time.

[0153] Figure 6 illustrates the deformation of a reference model via a transformation algorithm. The transformation algorithm receives as input the reference model 32 and the updated image 22, then deforms the reference model based on the updated image to determine an updated model 42 compatible with the updated image.

[0154] The transformation algorithm may be a metaheuristic method, preferably comprising the following steps:

[0155] - search for a position, orientation and calibration of a virtual acquisition device, collectively called “virtual acquisition conditions”, which best correspond to the real acquisition conditions of the updated image;

[0156] - comparison of the view of the reference model in virtual acquisition conditions and the updated image;

[0157] - deformation of the reference model so that the positioning of the teeth observed on said view under virtual acquisition conditions corresponds to the positioning of the teeth observed on the acquisition image.

[0158] The deformation is therefore carried out to update the reference model at the time at which the acquisition image was acquired.

[0159] Preferably, the reference model is previously divided into tooth models, as illustrated in Figure 4, the deformation comprising the displacement of said tooth models. In one embodiment, the deformation consists of moving tooth models whose shape remains constant. The search for said virtual acquisition conditions and said comparison can in particular be carried out according to the teaching of PCT / EP2015 / 074896.

[0160] Alternatively, the transformation algorithm includes at least one neural network.

[0161] The at least one neural network is pre-trained so that the neural network learns to provide an updated model as output, from an updated image and a reference model provided as input.

[0162] The training is carried out using a training base comprising historical images, first historical models, and second historical models, the historical images being comparable to updated images, the first historical models being comparable to reference models and the second historical models being comparable to updated models. Preferably, each second historical model is determined from a historical image and a corresponding first historical model, for example manually, or is acquired using a 3D scanner substantially at the time at which the corresponding historical image was acquired. A recording of the training base may comprise as a first object, a historical image and a first historical model and as a second object a second historical model.The neural network can be told that for a first object with a historical image and a first historical model, it must match a second object with a second historical model. In particular, to train the neural network, it will be provided with a set of first objects and a set of second objects so that it learns to match a first object with a second object. Once trained, the neural network is then able to determine an updated model as output, when it is provided with an updated image and a reference model as input.

[0163] In particular, if you have several updated images, it is possible to use PPO-type reinforcement networks, as described on the following site: https: / / openai.com / blog / openai-baselines-ppo / .

[0164] The PPO-type neural network may be configured to iteratively modify the position of the teeth of a 3D model representing at least a portion of a dental arch of the user from at least two updated images provided as input to the neural network so that the 3D model, once modified, has maximum concordance with the images provided as input, the at least two updated images being images representing at least a portion of the dental arch of the user acquired with different acquisition angles. The provision of several updated images acquired at different acquisition angles makes it possible to calculate the movements of the teeth in three dimensions according to the principle of triangulation.

[0165] Advantageously, such neural networks do not require any data other than the updated images as input to perform the modification of the 3D model available to the neural network.

[0166] To train the neural network, the neural network is given the expected final position of the teeth as output. The neural network can then learn to correct the result it provides as output (3D "output" model) by comparing the position of the teeth in this "output" model to the expected final position for said teeth. The difference between the expected tooth position and the position of said teeth in the output model provided by the neural network can be calculated, for example, in millimeters, or in degrees, or can be a surface tolerance, or a Euclidean distance LL

[0167] Compared to a PPO-type neural network, an occupancy network-type neural network may be less accurate, particularly when certain portions of the at least one part of the dental arch are not represented on the plurality of updated images provided as input to the neural network. Advantageously, a previously acquired 3D model of the user's dental arch makes it possible to reconstruct the missing portions. The previously acquired 3D model of the user's dental arch may also provide dimensional information, in millimeters for example, which cannot be deduced from the plurality of updated images provided as input alone.

[0168] In another embodiment of step b), the updated model is generated from the updated image, preferably from a set of several updated images, and from a library of tooth models according to a modeling method comprising, for each updated image, the following steps:

[0169] 1) analyzing the updated image so as to determine at least one tooth area and at least one tooth attribute value associated with said tooth area, preferably a type or number of the tooth to which the tooth area belongs;

[0170] 2) for each tooth area determined in step 1), search, in a historical library comprising more than 1000 tooth models associated with said tooth attribute value, called “historical tooth models”, for a historical tooth model having maximum proximity to the tooth area, called “optimal tooth model”;

[0171] 3) arrangement of all optimal tooth models in such a way as to create a model that has maximum concordance with the updated image.

[0172] The tooth model library is preferably created before step a) of the manufacturing method according to the invention. Preferably, the tooth model library comprises more than 2,000, preferably more than 5,000, preferably more than 10,000 historical tooth models. The higher the number of historical tooth models, the more accurate the assembled model.

[0173] The tooth attribute is used to filter historical tooth models to limit the search to teeth that have the same tooth attribute value as the tooth represented by the tooth area on the updated image.

[0174] One or more tooth attributes, in particular selected from a tooth number, a tooth type, a tooth shape parameter, for example a tooth width, in particular a mesio-palatal width, a thickness, a crown height, a deflection index mesially and distally of the incisal edge, or an abrasion level, a tooth appearance parameter, in particular a translucency index or a color parameter, a parameter relating to the condition of the tooth, for example "abraded", "broken", "decayed" or "braced" (i.e. in contact with an orthodontic appliance), an age for the user, or a combination of these attributes, may be associated with the tooth models.

[0175] Preferably, the modeling method comprises the following optional steps:

[0176] 4) optionally, replacement of at least one optimal tooth model with another historical tooth model and return to step 3) so as to maximize the agreement between the assembled model and the updated image;

[0177] 5) optionally, repeat step 1) with another updated image and in step 3) and / or 4), search for maximum concordance with all the updated images used.

[0178] The accuracy of the assembled model can be increased if multiple updated images are processed. In step 1), the updated image is analyzed, preferably by being subjected to a trained neural network to determine at least one tooth area and at least one tooth attribute value associated with said tooth area.

[0179] At the end of step 1), we obtain an updated image enriched with a description providing, for each tooth zone, a tooth attribute value for at least one tooth attribute, for example a tooth number.

[0180] In step 2), the historical library is searched for a historical tooth model with maximum proximity to the tooth zone for each tooth zone determined in the previous step. This tooth model is referred to as the "optimal tooth model".

[0181] Preferably, a historical tooth model is sought that has, for at least one tooth attribute, the same value as said tooth area. The tooth attribute may in particular be related to the tooth type or the tooth number. In other words, the historical tooth models are filtered to examine in more detail only those that are related to the same tooth type as the tooth represented on the tooth area.

[0182] Alternatively or, preferably, in addition to this comparison of the attribute values, the shape of the tooth represented on the tooth area may be compared to the shape of a historical tooth model to be evaluated, preferably by means of a metaheuristic method, preferably evolutionary, preferably by simulated annealing.

[0183] For this purpose, the historical tooth model to be evaluated is observed from different angles. Each view thus obtained is compared with the updated image, preferably with the tooth area, so as to establish a "distance" between this view and the said updated image or, preferably, the said tooth area. The distance thus measures the difference between the view and the tooth area.

[0184] For each historical tooth model tested, a view is determined that provides a minimum distance to the updated image or to the tooth area. Each historical tooth model examined is thus associated with a particular minimum distance, which measures its shape proximity to the tooth area.

[0185] The optimal historical tooth model is the one that, based on the comparison(s) made, is considered to be closest to the tooth zone. The minimum distances obtained for the different tooth models tested are then compared and the one with the smallest minimum distance is used to define the optimal tooth model. The optimal tooth model therefore has maximum concordance with the updated image.

[0186] The search for maximum concordance is preferably carried out using a metaheuristic method, preferably evolutionary, preferably by simulated annealing.

[0187] In a preferred embodiment, a first evaluation of the historical tooth models is successively carried out by comparing the values ​​of at least one tooth attribute, for example the tooth number, with the corresponding values ​​of the analysis tooth zone, then a second evaluation by comparison of shape. The first, rapid evaluation advantageously makes it possible to filter the historical tooth models in order to submit to the second, slower evaluation only the historical tooth models retained by the first evaluation.

[0188] Preferably, several initial assessments are conducted before the second assessment is conducted.

[0189] At the end of step 2), an optimal tooth model was thus associated with each of the tooth zones.

[0190] In step 3), an assembled model is created by arranging the optimal tooth models.

[0191] A first rough arrangement can be established by considering the tooth attribute values ​​of the optimal tooth models. For example, if the tooth numbers of optimal tooth models are those of canines and incisors, these tooth models can be arranged along an arc that classically corresponds to the region of the arch that bears these types of teeth.

[0192] The shape of this arc can be refined based on other tooth attribute values.

[0193] The order of optimal tooth models is that of the corresponding tooth areas.

[0194] Furthermore, the maximum proximity, or "minimum distance," associated with an optimal tooth model results from an observation of the tooth model from an observation point. In other words, it is likely that the tooth that this model models is also observed in the updated image from approximately this point. Optimal tooth models are thus preferably oriented so that their surfaces, which correspond to their respective tooth areas on the updated image, are observed from the same observation point.

[0195] It is thus possible to define an initial arrangement of optimal tooth models.

[0196] Preferably, the first arrangement of optimal tooth models is then iteratively modified, so as to exhibit maximum agreement with the updated image.

[0197] In another embodiment of step b), the updated model (or a reference model intended to be deformed to generate the updated model) is generated by implementing a method for generating a digital three-dimensional model of a dental arch comprising the following steps:

[0198] I) projection of at least one light beam onto the user's dental arch, so as to draw at least one light mark on the arch;

[0199] II) simultaneously with step I), moving the dental arch through the beam and acquiring, during said movement, a series of marked images of said arch each showing a representation of the projected mark, or “updated projection”;

[0200] III) identification of said projection on each marked image, then production of a digital three-dimensional model presenting maximum concordance with all of said updated projections.

[0201] Preferably, in step I), a structured beam of light is projected.

[0202] In step III), the updated model can be searched using an optimization method and / or one or more neural networks.

[0203] In step III), to create the updated model, one can modify a model defined according to user characteristics, or a model from a database, for example an initial model, an intermediate model, or a final model.

[0204] In step III), the updated model can be determined as being the model to be tested obtained at the end of the following cycle of steps i) to iii): i) creation of a model to be tested, then ii) determination of a distance representative of the difference between all the updated projections and the model to be tested, then, iii) if said representative distance exceeds a predetermined acceptability threshold, modification of the model to be tested and return to step i).

[0205] The representative distance can be evaluated from elementary distances, each elementary distance being determined, for a respective updated projection, by an evaluation of the difference between said updated projection and an optimal reference projection, a reference projection being a representation, on a reference image representing a view of the model to be tested, of a virtual light mark resulting from the projection, on the model to be tested, of a virtual light beam of the same shape as the light beam projected onto the arch in step I), the optimal reference image being the reference image showing the reference projection which has a minimum distance with the updated projection.

[0206] The model to be tested may be segmented to define tooth models and modification of the model to be tested includes displacements of the tooth models and / or deformations of these tooth models.

[0207] The first model to be tested and modified may be a dental arch model, preferably selected based on user characteristics, or a model from a database, for example an initial model, an intermediate model, or a final model.

[0208] In step III), at least one, preferably two methods are implemented from among the optimization methods, the artificial intelligence methods, the methods of evaluating dimensions by stereovision, the methods of evaluating dimensions by analyzing the shape of the luminous mark and the methods of evaluating dimensions by analyzing the distance between remarkable points of the marked images.

[0209] In step c), a retention device 44 is designed from the updated model 42. The design can be done manually, for example by a technician or a dental care professional.

[0210] Alternatively, the design is carried out by means of software, preferably automatically, i.e. without human intervention. The retainer is designed so as to maintain the user's teeth in the configuration of the teeth at the updated instant. To ensure this maintenance, the shape of the orthodontic appliance is conventionally in accordance with that of the patient's dental arch at the updated instant, so that the orthodontic appliance does not, at the updated instant, exert an action tending to move teeth.

[0211] Preferably, the retention appliance is a retention arch intended to be fixed, for example glued, to the user's teeth. Alternatively, the retention appliance is an orthodontic retainer.

[0212] The design of the retention appliance consists of determining a shape of the appliance capable of maintaining the configuration of the teeth at the current time.

[0213] In step d), the retention device 52 is manufactured.

[0214] In one embodiment, the manufacturing results from an impression made on a part physically representing the updated model. Steps c) and d) are then combined. For example, a metal wire can be pressed onto a plaster cast or a polymer material, physically representing the updated model, in order to produce a retention arch. A splint made of a polymer material can also be manufactured by molding on such a part.

[0215] The retainer can also be made directly from the updated model, for example by designing a 3D model of the retainer and then manufacturing it, for example by printing it with a 3D printer.

[0216] Preferably, when the retention appliance is a retention arch, a transfer splint is also manufactured, the transfer splint allowing the retention arch to be easily positioned on the user's teeth. First, the retention arch is positioned in the orthodontic transfer splint with an adhesive substance. Second, the orthodontic transfer splint is positioned in the service position on the user's teeth. Transport, positioning, and fixation of the retention arch are thus facilitated. In particular, it is possible to position and fix the arch in a single step. In addition, since the orthodontic transfer splint is designed from a three-dimensional model representing the user's dental arch, the retention arch can be positioned precisely. The article "Simple and rapid method of indirect retention" by Christine MULLER et al., Orthod Fr 2009;80:233-238, EDP Sciences, SFODF, 2009 DOI: 10.105 l / orthodfr / 2009006, describes an example of a method for manufacturing an orthodontic transfer splint. In step e), optional, the manufactured retainer is sent, preferably to the dental professional or to the user. The user may receive, with the retainer, instructions indicating how to wear and / or position the retainer. Advantageously, the user therefore does not have to go to the dental professional, either for the acquisition of a 3D model using a 3D scanner or to receive the retainer and / or for the retainer to be positioned in his mouth.

[0217] Preferably, steps b) and c) are implemented by computer, preferably without human intervention. Step d) and / or e) may also be carried out without human intervention. The computer implementing step c) may communicate, after step c), instructions from the design for manufacturing the retention device to a manufacturing device 50.

[0218] Figure 5 schematically illustrates a design kit 1 according to the invention.

[0219] The design kit 1 comprises an image acquisition device 20, preferably a mobile phone, and a computer system 40, for example a computer, comprising a computer program product configured to implement step b) of a manufacturing method according to the invention, better still to implement steps b) to c) of a manufacturing method according to the invention. The computer program product may also be configured to send design instructions 64 directly to a manufacturing device 50.

[0220] The image acquisition apparatus 20 can communicate with the computer system to transmit the acquired updated image(s) 60 to the computer system 40, via digital communications. In a particular embodiment, the acquisition apparatus and the computer system are integrated into a mobile phone.

[0221] The reference model may be derived from a database 30, accessible, via digital communications, to the computer system. The reference model may be transmitted 62 to the computer system, in particular by being downloaded. The database may be in a remote server.

[0222] The design kit 1 may include the manufacturing device, the manufacturing device preferably being configured to communicate with the computer system. Once the design of the retention device is completed, the computer system 40 may send manufacturing instructions 64 to the manufacturing device 50.

[0223] Example

[0224] An updated image 22 is acquired by means of a mobile phone 20, preferably by the user, preferably remotely from a dental or orthodontic practice.

[0225] The updated image 22 is sent to a computer system 40. The computer system may or may not be integrated into the mobile phone. Preferably, the computer system is a specialized application, which can be installed on the mobile phone.

[0226] The computer system 40 can preferably communicate with a database 30 comprising intermediate, initial and final models from one or more orthodontic treatment scenarios, representing configurations of the user's dental arch. The intermediate and final models represent theoretical configurations of the user's dental arch. The initial model is a model acquired by the dental care professional, conventionally, preferably by means of a 3D scanner. In step b), the reference model is determined by selecting a model from the database 30.

[0227] Alternatively, in step b), the reference model 32 is manually selected and sent to the computer system 40, for example by the dental care professional or a technician.

[0228] From the updated image 22 and the reference model 32, the computer system 40 can determine the updated model 42, as described in step c) of a method according to the invention.

[0229] The computer system 40 can then, using the updated model 42, design a retention appliance 52, as described in step d) of a method according to the invention, optionally with the help of an operator or a dental care professional. The determination of the updated model (step c)) and the design of the retention appliance (step d)) can be carried out remotely from each other. The computer system can comprise several processors.

[0230] Preferably, the mobile phone comprises a specialized application configured to implement steps a) to c) according to the invention, preferably steps a) to d) according to the invention. Step d) of designing the retention appliance makes it possible to determine instructions for manufacturing said retention appliance. The retention appliance 52 may be a retention arch or an orthodontic retaining splint. These instructions are advantageously sent to a manufacturing device 50.

[0231] The manufacturing device manufactures the restraint device based on the instructions. The manufacturing device may be a 3D printer. The 3D printer may be at the user's premises.

[0232] After manufacturing, the retention appliance can be sent directly to the user. Preferably, when the retention appliance is a retention arch, it is sent in a transfer tray, which includes, in addition to the arch, glue for fixing the retention arch to the user's teeth when the transfer tray is positioned on said teeth of the user.

[0233] As is now clear, a method according to the invention makes it possible to manufacture a retention appliance from one or more updated images, preferably photos taken by the user, and from a reference model acquired when the teeth had not yet reached their final configuration. This manufacturing can therefore be carried out without the intervention of the orthodontist specifically for this purpose, which avoids the user having to make an appointment with the latter.

[0234] Thus, by acquiring simple extra-oral images of the user's teeth, i.e. images acquired using an image acquisition device located outside the user's mouth during acquisition, it is possible to design and manufacture a retention device, without the user needing to physically consult their dental care professional. In particular, a method according to the invention makes it possible to manufacture retention arches intended to be positioned on an intrados surface of the user's teeth, from the acquisition of extra-oral images, representing in particular the extrados surface of the user's teeth.

[0235] Of course, the invention is not limited to the embodiments described above and shown.

Claims

Demands 1. A method for manufacturing a retainer, said method comprising the following steps: before step a), during orthodontic treatment, generating a reference model representing the user's dental arch; a) at a current time, at the end of or after the completion of orthodontic treatment, acquiring at least one two-dimensional image of at least a portion of a user's dental arch, referred to as the "current image," using an image acquisition device; b) generating a three-dimensional digital model representing the user's dental arch, referred to as the "current model," from the current image, the current model being obtained by deforming the reference model from the current image; c) designing, from the current model and preferably by computer, a retainer adapted to maintaining the teeth in their configuration at the current time; d) manufacturing the retainer.

2. A method according to claim 1, wherein the acquisition of the updated image is carried out by the user, preferably outside of an orthodontic or dental office.

3. A method according to any one of the preceding claims, wherein the retention device is a retention arch or an orthodontic retention splint, preferably a retention arch.

4. A method according to any one of the preceding claims, wherein the reference model represents the user's dental arch in a desired theoretical configuration at an intermediate time in orthodontic treatment or at a final time in orthodontic treatment, referred to as the "intermediate model" or "final model" respectively.

5. A method according to any one of the preceding claims, wherein the reference model is a final model. A method according to any one of the preceding claims, wherein, in step b), the reference model is obtained by means of a LIDAR integrated into a user's mobile phone or by implementing a method for modeling a dental arch, preferably using a user's mobile phone, said modeling method comprising the following steps: 1) analysis of an image representing the user's dental arch so as to determine at least one tooth area and at least one tooth attribute value associated with said tooth area, preferably a type or number of the tooth to which the tooth area belongs; 2) for each tooth area determined in step 1), search, in a historical library containing more than 1000 tooth models associated with said tooth attribute value, called "historical tooth models", for a historical tooth model with maximum proximity to the tooth area, called "optimal tooth model"; 3) Arranging all the optimal tooth models to create a model that exhibits maximum concordance with the image analyzed in step 1), said image being, for obtaining the updated model, said updated image, or, for obtaining the reference model, an image acquired before the updated time. A method according to any one of the preceding claims, wherein, in step b), the reference model is obtained by implementing a method for generating a three-dimensional digital model of a dental arch comprising the following steps: I) projection of at least one beam of light onto the user's dental arch, so as to draw at least one light mark on the arch; II) simultaneously with step I), movement of the dental arch through the beam and acquisition, during said movement, of a series of "marked" images of said arch each showing a representation of the projected mark, or "projection"; III) identification of said projection on each marked image, then fabrication of a three-dimensional digital model exhibiting maximum concordance with the set of projections.

8. A method according to any one of the preceding claims, comprising, after step d), a step e): e) sending the retainer, preferably to the user or the dental professional.

9. A method according to any one of the preceding claims, wherein the acquisition device is a mobile phone and / or the retainer is manufactured using a 3D printer.

Images