WO2020126058A1 - Procédé de correction d'un modèle numérique dentaire - Google Patents

Procédé de correction d'un modèle numérique dentaire Download PDF

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Publication number
WO2020126058A1
WO2020126058A1 PCT/EP2018/086802 EP2018086802W WO2020126058A1 WO 2020126058 A1 WO2020126058 A1 WO 2020126058A1 EP 2018086802 W EP2018086802 W EP 2018086802W WO 2020126058 A1 WO2020126058 A1 WO 2020126058A1
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WO
WIPO (PCT)
Prior art keywords
image
reference model
updated
acquisition conditions
model
Prior art date
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PCT/EP2018/086802
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English (en)
Inventor
Philippe Salah
Original Assignee
Dental Monitoring
Straumann Holding Ag
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Dental Monitoring, Straumann Holding Ag filed Critical Dental Monitoring
Priority to PCT/EP2018/086802 priority Critical patent/WO2020126058A1/fr
Publication of WO2020126058A1 publication Critical patent/WO2020126058A1/fr

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T19/00—Manipulating 3D models or images for computer graphics
    • G06T19/20—Editing of 3D images, e.g. changing shapes or colours, aligning objects or positioning parts
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/50—Depth or shape recovery
    • G06T7/55—Depth or shape recovery from multiple images
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2219/00—Indexing scheme for manipulating 3D models or images for computer graphics
    • G06T2219/20—Indexing scheme for editing of 3D models
    • G06T2219/2021—Shape modification

Definitions

  • the present invention relates to a method to correct a three-dimensional digital model of an arch of a patient, a computer program for implementing this method, an acquisition apparatus provided with this program, and a method to manufacture an orthodontic part from said model.
  • the manufacturing of an orthodontic appliance requires that an orthodontist scans the patient’s arches to generate a three-dimensional digital model, or « initial reference model East
  • the initial reference model is segmented to create, for each tooth, a three-dimensional digital model of each tooth, or « tooth model East
  • the orthodontist, or a laboratory with the help of the orthodontist moves one or more tooth models of the initial reference model to obtain a “target reference model” or“set up”.
  • the initial and target models are used by the laboratory to manufacture one or more orthodontic parts accordingly, for instance aligners.
  • defects i.e. differences between the initial reference model and the modelized patient’s arch, may stem from the resolution of the scanner and/or from the way the scanner is operated.
  • Defects may also be generated when the initial reference model is not directly produced from a scan of the teeth, but is produced from a plaster mold of the teeth.
  • WO 2016/066651 discloses the generation of an updated reference model by the deformation of an initial reference model obtained from a scan of the teeth. Such deformation may also generate defects.
  • a defect cannot be corrected. For instance, it is so large that no interpolation is possible. Then, the laboratory must refuse the defective model and inform the orthodontist. The orthodontist must invite the patient for a new scan acquisition. Most time and money is lost. In addition, this additional visit is inconvenient for the patient and places stress on the orthodontist.
  • the model might be affected with defects which cannot be detected but are prejudicial. Therefore, the orthodontic treatment will not take place normally, the patient will be angry and will place stress much on the orthodontist.
  • One aim of the present invention is to address, at least partially, the above-mentioned problems.
  • the invention provides a method of correction of a three-dimensional digital model of an arch of a patient, or“reference model”, said method comprising the following steps:
  • a method according to the invention makes it possible correcting a reference model with simple updated images, and in particular from photographs.
  • a method according to the invention may in particular include one or more of the additional characteristics of the depending claims.
  • steps 2) to 4) are executed for more than two, more than five, preferably more than ten or more than fifty updated images. The number of remaining defects decreases accordingly.
  • Step 2) preferably comprises the following steps:
  • the reference model may be generated by a deformation of an initial reference model, which itself was produced by a scan of an arch of the patient.
  • the reference model may in particular be an updated reference model produced according to the method disclosed in WO 2016/066651, incorporated by reference.
  • Such an updated reference model may in particular be used to evaluate an orthodontic treatment and/or modify an orthodontic treatment.
  • the updated reference model may be used to design new aligners.
  • the invention also concerns an acquisition apparatus comprising:
  • an image acquisition apparatus in particular a digital camera, to acquire updated images of an arch of a patient
  • a scanner configured to generate a reference model of said arch; - a processing module configured to correct said reference model with said updated images to get a corrected reference model according to a method according to the invention, and preferably inform an operator if a defect cannot be corrected, and in particular if this defect has a potential prejudicial effect.
  • the processing module is configured so that the information of the operator occurs less than five minutes, preferably less than one minute, preferably less than thirty seconds, preferably less than ten seconds, preferably less than one second after the correction of the reference model.
  • the operator of the acquisition apparatus is rapidly informed and may immediately generate a new reference model.
  • the corrected reference model may in particular be used to manufacture an orthodontic part.
  • the invention therefore also concerns a method to manufacture an orthodontic part, said method comprising, after the production of a corrected reference model according to steps 1) to 4), the following steps:
  • the manufacture is preferably achieved by a centralized laboratory, i.e. a laboratory manufacturing appliances for a plurality of orthodontists.
  • the invention also relates to:
  • - a computer program and in particular an application specifically for mobile phones, comprising program code instructions for the execution of one or more, preferably all, of the steps 2) to 4), when said program is run by a computer, and - a computer medium on which is stored such a program, for example a memory or a CD-ROM.
  • A“patient” should be understood to mean any person for whom a method is implemented in order to monitor the teeth thereof, whether this person is sick or not.
  • An“orthodontic part” refers to any part of an orthodontic apparatus, or to a complete orthodontic apparatus, for instance an aligner.
  • a « model » is a three-dimensional digital model, for example of .stl or .Obj, .DXF 3D, IGES, STEP, VDA, or point cloud type.
  • a model, called“3D” may be observed from any angle.
  • A“defect” is a part of a model of a dental arch which does not correctly represent this arch.
  • the model may represent asperities or recesses which, in reality, i.e. in the dental arch, do not exist.
  • the length of a defect is less than 5 mm, 3mm, 2mm or 1mm.
  • Tunnels et bridges are usual examples of defects from 3D scans.
  • a defect can be, in particular, an excess of 3D material, a distorted incisal edge, a hole or a distortion in the mesh, a double skin, a push through, or an insufficient definition, an autointersection.
  • An excess of 3D material may stem from artefacts. For instance, a part of the tong may be represented in the model.
  • a distorted incisal edge is also a common defect. Indeed, the incisal edges are difficult to scan and the edges of the vestibular faces may not perfectly match the edges of the lingual faces.
  • a model is commonly a mesh of lines. It may locally present holes or distorsions so that it does not correctly represent the real teeth.
  • the mesh may be irregular or may have regions in which it is not connex, i.e. which do not comprise any line common to different triangles of the model.
  • a non-manifold mesh is also a defect, i.e. when more than two triangles are defining a common line of the 3D model.
  • a model may also comprise an overlap, i.e. a superposition of two layers, or “double skins”, which should be avoided.
  • a model may have a precision which locally is too low, i.e. an insufficient definition.
  • An“image” is understood to be a two-dimensional image, like a photograph.
  • An image is formed by pixels.
  • An « image of an arch » and a « model of an arch » are representations of a part or of a complete arch.
  • The“acquisition conditions” specify the position and the orientation in space of an image acquisition apparatus in relation to the teeth of the patient or to a tooth model of the patient, and preferably the calibration of this image acquisition apparatus. Acquisition conditions are called “virtual” when they correspond to a simulation in which the acquisition apparatus would be in said acquisition conditions (theoretical positioning and preferably calibration of the acquisition apparatus).
  • The“calibration” of an acquisition apparatus is made up of all the values of the calibration parameters.
  • A“calibration parameter” is a parameter intrinsic to the acquisition apparatus (unlike its position and its orientation), the value of which influences the image acquired.
  • the calibration parameters are chosen from the group formed by the diaphragm aperture, the exposure time, the focal distance and the sensitivity.
  • A“scanner” is an apparatus making it possible to obtain a three-dimensional representation of an object.
  • A“discriminating piece of information” is a characteristic information which may be extracted from an image ⁇ "image feature"), conventionally by a computer processing of this image.
  • a discriminating piece of information may have a variable number of values.
  • an outline information may be equal to one or zero depending on whether a pixel belongs or does not belong to an outline.
  • a brightness information may take a large number of values. The processing of the image makes it possible to extract and quantify the discriminating piece of information.
  • the discriminating information may be represented as a“map”.
  • a map is therefore the result of the processing of an image to make the discriminating piece of information more visible.
  • a point of an image results from the projection of a point of the dental arch of the patient along the observation direction during the acquisition of the image (direction of the objective of the image acquisition apparatus).
  • the point of the reference model representing this point of the dental arch is called“parent point” of the image point.
  • The“fit” between two objects is a measure of the difference between these objects.
  • An object“best fits” another object when it results from an optimization treatment to reduce said difference below a determined threshold.
  • the search of a reference image best fitting with the reference model is achieved by searching virtual acquisition conditions best fitting with the actual acquisition conditions.
  • Two images best fitting with each other substantially represent the same object, in the same way. Put differently, the representations of the object on the two images are substantially superimposable.
  • An updated image also best fits with a reference model when a view of the reference model provides a reference image which best fits with the updated image.
  • Metaheuristic methods in particular comprise:
  • evolutionist algorithms preferably chosen from: evolution strategies, genetic algorithms, differential evolution algorithms, distribution estimation algorithms, artificial immunity systems, Shuffled Complex Evolution path recomposition, simulated annealing, ant colony algorithms, particle swarm optimization algorithms, taboo search, and the GRASP method;
  • - figure 3 is an example of a reference image
  • FIG. 4 (4a-4b) illustrates the generation of a reference map from a reference image
  • FIG. 5 illustrates the generation of an updated image with a separator (5a-5b), and the generation of an updated map from an updated image (5c-5d),
  • FIG. 6 schematically illustrates the relative position of register marks 12 on updated images 14i and 14 2 of a separator 10, depending on the direction of observation (broken line).
  • a method according to the invention comprises the steps 1) to 4) mentioned above.
  • the reference model may be prepared from measurements performed on the teeth of the patient or on a physical mold of his or her teeth, for example a plaster mold.
  • the reference model is preferably created by means of a professional apparatus, for example by means of a 3D scanner, preferably implemented by a health professional, for example by an orthodontist or an orthodontic laboratory.
  • a professional apparatus for example by means of a 3D scanner
  • a health professional for example by an orthodontist or an orthodontic laboratory.
  • the patient or the physical model of his or her teeth may advantageously be arranged in a precise position and the professional apparatus may be refined.
  • the result thereof is a very accurate reference model.
  • the initial reference model preferably provides an information on the positioning of the teeth with an error of less than 5/10 mm, preferably less than 3/10 mm, preferably less than 1/10 mm.
  • the reference model may also be an updated reference model prepared as disclosed in WO 2016 066651.
  • an updated image la is taken of the arch by means of an image acquisition apparatus, in actual acquisition conditions.
  • the image acquisition apparatus is preferably a digital camera.
  • step 1) occurs less than 1 hour, preferably less than 10 minutes, preferably than 5 minutes, preferably less than 1 minute after the reference model has been prepared from measurements performed on the teeth of the patient or on a physical mold of his or her teeth. This is particularly useful when the image acquisition apparatus is part of the scanner used to prepare the reference mold and when the updated images are used to correct defects of this reference model.
  • the image acquisition apparatus may be part of an acquisition apparatus according to the invention. However, a method according to the invention does not require an accurate positioning of the image acquisition apparatus relative to the teeth.
  • a separator 10 is used, as represented in figure 5a.
  • the first function of the separator is to separate the lips in order to improve the visibility of the teeth.
  • Step 1) may comprise one or more characteristics of step b) disclosed in WO 2016 066651, incorporated by reference.
  • a view of a“reference model” is called a“reference image”.
  • the reference model is explored to find a reference image best fitting with the updated image.
  • Figures 3 and 4a are examples of reference images.
  • Step 2) may comprise one or more characteristics of steps c), d), and e) disclosed in WO 2016 066651, as far as they concern the search of reference images best fitting with updated images.
  • the updated image is analyzed so as to produce an updated map relating to at least one discriminating piece of information (figures 5 c and 5d).
  • An updated map represents a discriminating piece of information in the reference frame of the updated image.
  • the discriminating information is preferably chosen from the group consisting of a piece of outline information, a piece of color information, a piece of density information, a piece of distance information, a piece of brightness information, a piece of saturation information, a piece of information on the glare and combinations of such pieces of information.
  • figure 4b is an updated map relating to the outline of the teeth obtained from the updated image of figure 4a.
  • virtual acquisition conditions roughly approximating the actual acquisition conditions are determined.
  • at least the relative position of the image acquisition apparatus at the moment when the updated image was taken is determined.
  • This rough assessment advantageously makes it possible to determine a restricted set of virtual acquisition conditions likely to correspond to the actual acquisition conditions, and, in this set, virtual acquisition conditions constituting the best point of departure for the following operations. It therefore makes it possible to considerably speed up these operations.
  • One or more heuristic rules are preferably used. For example, preferably, there are excluded, from the virtual acquisition conditions likely to be tested in the following operations, the conditions which correspond to a position of the image acquisition apparatus behind the teeth or at a distance from the teeth greater than 1 m.
  • register marks are used that are represented on the updated image, and in particular register marks 12 of the separator, to determine a substantially conical region of space delimiting the virtual acquisition conditions likely to be tested in the following operations, or“test cone”.
  • the register marks are then identified on the updated image, as described previously.
  • Simple trigonometrical computations make it possible to approximately determine the direction from which the updated image has been taken.
  • a best fitting reference image is searched, preferably according to steps 21) to 25).
  • Metaheuristic preferably evolutionist, optimization methods, particularly in the simulated annealing methods, may be used for this search.
  • virtual acquisition conditions“to be tested” are determined, that is to say a virtual position and a virtual orientation likely to match the actual position and orientation of the acquisition apparatus during the capture of the updated image, but also, preferably, a virtual calibration likely to match the actual calibration of the acquisition apparatus during the capture of the updated image.
  • the first virtual acquisition conditions to be tested may be random. Preferably, they are chosen from the restricted set which was previously roughly determined, and in particular from the virtual acquisition conditions corresponding to the most promising virtual acquisition conditions, that is to say those constituting the best springboard for approximating, as rapidly as possible, the actual acquisition conditions.
  • the image acquisition apparatus is then virtually configured in the virtual acquisition conditions to be tested in order to acquire a reference image of the reference model in these virtual acquisition conditions to be tested.
  • the reference image therefore corresponds to the image that the image acquisition apparatus would have taken if it had been placed, relative to the reference model to be tested, and optionally calibrated, in the virtual acquisition conditions to be tested.
  • the reference image may therefore be exactly superimposed on the updated image.
  • the differences between the updated image and the reference image result from errors in the assessment of the virtual acquisition conditions if they do not correspond exactly to the actual acquisition conditions.
  • the discriminating information is compared on these two images. More specifically, from the reference image, a reference map is produced representing the discriminating information (figures 4a and 4b).
  • the updated and reference maps, the two of them relating to the same discriminating information are then compared and the difference between these two maps is assessed by means of a score.
  • the discriminating information is the outline of the teeth
  • the score may for example be a coefficient of correlation.
  • the virtual acquisition conditions comprise the calibration parameters of the acquisition apparatus.
  • the score is all the higher as the values of the calibration parameters tested come closer to the values of the calibration parameters of the acquisition apparatus used at step 1). For example, if the diaphragm aperture tested is far from that of the acquisition apparatus used at step 1), the reference image exhibits blurred regions and sharp regions which do not correspond to the blurred regions and to the sharp regions of the updated image. If the discriminating information is the outline of the teeth, the updated and reference maps do not therefore represent the same outlines and the score will be low.
  • the score is then assessed by means of an assessment function.
  • the assessment function makes it possible to decide whether the cycling to search the best fitting virtual acquisition conditions (steps 21) to 25)) must be continued or stopped.
  • the assessment function may for example be equal to 0 if the cycling must be stopped or be equal to 1 if the cycling must continue.
  • the value of the assessment function may depend on the score reached. For example, it may be decided to continue the cycling if the score does not exceed a threshold. For example, if an exact match between the updated and reference images leads to a score of 100%, the threshold may be, for example, 95%. Obviously, the higher the threshold, the better the accuracy of the assessment of the virtual acquisition conditions if the score comes to exceed this threshold.
  • the value of the assessment function may also depend on scores obtained with virtual acquisition conditions tested previously.
  • the value of the assessment function may also depend on random parameters and/or on the number of cycles already performed.
  • the assessment function may then lead to the decision to quit the cycling although the best score obtained has not reached said threshold. This decision may result, for example, from a number of cycles greater than a predetermined maximum number.
  • a random parameter in the assessment function may also authorize the continuation of tests of new virtual acquisition conditions, although the score appears satisfactory.
  • the assessment functions conventionally used in the metaheuristic, preferably evolutionist, optimization methods, particularly in the simulated annealing methods, may be used for the assessment function.
  • step 25 if the value of the assessment function indicates that it is decided to continue the cycling, the virtual acquisition conditions to be tested are modified and a cycle is recommenced consisting in producing a reference image and a reference map, then in comparing this reference map with the updated map to determine a score.
  • the modification of the virtual acquisition conditions corresponds to a virtual movement in space and/or to a modification of the orientation and/or, preferably, to a modification of the calibration of the acquisition apparatus.
  • This modification may be random.
  • the modification is preferably guided by heuristic rules, for example by favoring the modifications which, according to an analysis of the preceding scores obtained, appear the most favorable to increase the score.
  • the cycling is continued until the value of the assessment function indicates that it is decided to exit from this cycling, for example if the score reaches or exceeds said threshold.
  • the optimization of the virtual acquisition conditions is preferably performed by using a metaheuristic method, preferably evolutionist, preferably a simulated annealing algorithm. Such an algorithm is well known for nonlinear optimization.
  • the method may be stopped (failure situation) or restarted with a new discriminating piece of information and/or with a new updated image.
  • the method may also be continued with the virtual acquisition conditions corresponding to the best score reached. A warning may be emitted in order to inform the user of the error on the result.
  • the virtual acquisition conditions correspond substantially to the actual acquisition conditions.
  • the virtual acquisition conditions comprise the calibration parameters of the acquisition apparatus.
  • the method conducted thus makes it possible to assess the values of these parameters without it being necessary to know the nature of the acquisition apparatus or its setting.
  • the step 1) may therefore be performed with no particular precautions.
  • the search for the actual calibration is performed by comparing an updated image with views of an initial reference model in virtual acquisition conditions to be tested.
  • it does not require the updated image to show a standard calibration gauge, that is to say a gauge whose features are precisely known making it possible to determine the calibration of the acquisition apparatus.
  • the observation of the reference model in the virtual acquisition conditions provides a reference image best fitting with the updated image.
  • the reference image is compared with the updated image. Differences correspond to defects to be corrected.
  • the corresponding reference and updated maps are compared.
  • a superimposition of these two maps makes the differences, i.e. the defects, visible since the defects appear on the reference map, but not on the updated map.
  • the reference model is corrected accordingly.
  • the correction might be done manually, with a computer enabling the modification of the reference model.
  • the correction is done with at least one second updated image, as illustrated in Figure 1 and described hereafter.
  • the discriminating information is a piece of outline information.
  • the reference model 20 comprises a defect 22.
  • the first reference image Iri has been acquired by observation of the reference model 20 in first virtual acquisition conditions simulating actual acquisition conditions under which the first updated image Iai has been acquired.
  • the treatment of the first reference image Iri results in a first reference map Qj which shows a first“reference” outline 311 with the defect 22.
  • the first updated map Cai obtained from the first updated image Iai, represents a first “updated” outline 30i, on which the defect 22 is not visible (since it was not on the arch).
  • the first updated map Cai is superimposed with the first reference map Qj .
  • the superimposition makes the defect 22 visible.
  • the superimposition also provides a first correct outline portion, which should replace the defect 22, i.e. the points of the first updated outline which were not visible on the first reference map.
  • first outline points 321 of the first correct outline portion are not sufficient to determine the position of respective outline parent points 34 in the updated reference model 20.
  • first outline point 32i it is not possible identifying precisely the position of the outline parent point 34 along a straight line Di including the first outline point and parallel to the observation direction.
  • a second updated image Ia 2 representing the defect 22, but acquired under a different observation angle than the first updated image can be used.
  • the second updated image Ia 2 is treated in the same way as the first updated image Iai .
  • the second reference image Ir 2 has been acquired by observation of the reference model 20 in second virtual acquisition conditions simulating actual acquisition conditions under which the second updated image Ia 2 has been acquired.
  • the treatment of the second reference image Ir 2 results in a second reference map Cr 2 which shows a second reference outline 31 2 with the defect 22.
  • the second updated map Ca 2 obtained from the second updated image Ia 2 , represents a second updated outline 30 2 , on which the defect 22 is not visible.
  • the second updated map Ca 2 is superimposed with the second reference map Cr 2 .
  • the superimposition makes the defect 22 visible.
  • the superimposition also provides a second correct outline portion, made of second outline points 32 2 , which should replace the defect 22, i.e. the points of the second updated outline which were not visible on the second reference map.
  • the transition between the first virtual acquisition conditions and the second virtual acquisition conditions transforms a plurality of first points of the first reference image or map into respective second reference points of the second reference image or map, respectively.
  • the second reference points of the second reference image or map corresponding to most of said first reference points of the first reference image or map can be easily determined by considering the effect of said transition on said first reference points.
  • the representation, on the second reference image or map, of a reference system 33 represented on the first reference image or map may be determined by the simulation of said transition.
  • a same point of the arch is represented, on the first and second reference images or maps, by first and second reference points which have the same coordinates in the reference system 33, as represented on the first and second reference images or maps, respectively.
  • first and second outline points are associated to define couples which each define an outline parent point 34 of the reference model.
  • the outline parent points are then added to the reference model, the position in space of an outline parent point being at the intersection of straight lines Di and D 2 including the first and second outline points, respectively, and parallel to the observation directions of the reference model to acquire the first and second reference images, respectively.
  • one outline parent point 34 is added for each couple of first and second outline points.
  • First and second“defect” points can be identified on the first and second reference maps Cri and Cr 2 , respectively, by superimposition with the first and second updated maps Cai and Ca 2 , respectively, as explained previously. Then, they are coupled, as explained previously for the first and second outline points.
  • defect parent points are deleted from the reference model, the position in space of a defect parent point being at the intersection of straight lines including the first and second defect points of a couple, respectively, and parallel to the observation directions of the reference model to acquire the first and second reference images, respectively.
  • the corrected reference model is validated.
  • some defects might have been detected and not corrected because the updated images were not configured for the correction. For instance, if only one updated image shows a defect, this defect cannot be deleted and corrected.
  • the uncorrected defect may be acceptable or not, depending on its prejudicial effect.
  • the evaluation whether an uncorrectable defect is acceptable or not may be done by an orthodontist or by a computer, with the help of implemented rules.
  • steps 1) to 5) preferably require less than 5 minutes, preferably less than 1 minute, so that the operator of a scanner used to create the reference model can be informed about the rejection before the patient has left. A new reference model can then be immediately created and corrected.
  • the corrected reference model is validated.
  • the corrected reference model is used to manufacture an orthodontic part, for instance an aligner.
  • the corrected reference model may be deformed, the deformation depending on the orthodontic treatment to be applied. Conventional methods may be applied for this deformation.
  • the method may be implemented successively for each of the two arches or simultaneously for the two arches of the patient.
  • the patient is not limited to a human being.
  • a method according to the invention may be used for another animal.

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Abstract

L'invention concerne un procédé de correction d'un modèle numérique tridimensionnel d'une arcade d'un patient, ou « modèle de référence » (20), ledit procédé comprenant les étapes suivantes : 1) acquisition d'au moins une image bidimensionnelle de ladite arcade, dite « image mise à jour » (Ia1;Ia2), dans des conditions d'acquisition réelles ; 2) recherche, pour chaque image mise à jour, des conditions d'acquisition virtuelle fournissant une image bidimensionnelle du modèle de référence, maximisant l'ajustement avec l'image mise à jour, ou « image de référence » (Ir1;Ir2) ; 3) comparaison de l'image de référence avec l'image mise à jour pour détecter des différences (22); 4) correction du modèle de référence pour réduire lesdites différences pour obtenir un modèle de référence corrigé.
PCT/EP2018/086802 2018-12-21 2018-12-21 Procédé de correction d'un modèle numérique dentaire WO2020126058A1 (fr)

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Cited By (1)

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WO2023215767A3 (fr) * 2022-05-02 2023-12-07 Align Technology, Inc. Procédés et appareils de détection d'espaces interproximaux

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WO2016066651A1 (fr) 2014-10-27 2016-05-06 H43 Development Procede de controle de la dentition

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