DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Pellissard et al. (U.S. Pub. No. 2023/0334549), hereinafter “Pellissard”, as cited in the IDS filed 10 January 2024.
*Note: evidentiary reference Fouquet et al. (Interest in the early extraction of temporary maxillary canines to prevent the inclusion of permanent canines and determination of the Canine Congestion Index®. Radiological retrospective study, 2017, J Dentofacial Anom Orthod, Vol. 20, No. 404, Pages 1-13), hereinafter “Fouquet”, is relied on for the treatment of claims 3 and 15.
Regarding claim 1, Pellissard teaches:
A method for selecting a toothbrush for a subject, the method comprising (See the Abstract.):
maintaining a data store comprising information for a plurality of toothbrushes, each of which is associated with a category (See [0301]-[0303]: “The database of dental products from which the relevant dental products are selected preferably comprises records for more than 100, more than 500 or more than 1,000, more than 5,000 or more than 10,000 dental products and/or less than 1,000,000 dental products. Each record conventionally includes an identifier for a respective dental product and a set of values for the variables involved in the rules. For example, a record for a dental product can include values for the following variables:…hardness, for example, for a toothbrush; bristle density, for a toothbrush;”.);
receiving image data that shows a plurality of teeth of the subject (See [0130]: “In step a), after having launched the dedicated application, an operator, preferably the target consumer or someone close to the target consumer, acquires, by means of the mobile telephone, at least one updated image Ia (see FIG. 1 ) depicting at least part of one of the dental arches of the target consumer.”);
processing the image data to identify a dental arch of the subject (See [0115]: “For example, each record of the learning database can include an image of a dental arch and a description identifying, in this image, the depictions of the teeth, or “tooth areas”, and the corresponding tooth numbers. After being trained, the neural network can thus identify, on an image presented thereto, the depictions of the teeth and the corresponding tooth numbers.”);
processing the image data to classify the dental arch according to a classification that is selected from a plurality of candidate classifications (See [0266]: “A plurality of neural networks can be trained in order to each determine the value of a respective dental attribute. For example, if the dental objective is to select at least one product for improving breath, neural networks can be trained in order to determine the values of one or more of the following dental attribute(s): presence of tartar, presence of dental plaque, presence of a whitish tongue, lack of saliva.”);
using the selected classification to select, from the data store, a toothbrush having a category that is associated with the selected classification of the subject’s dental arch (See [0268]: “In particular, it can select the one or more relevant dental product(s) from a database of dental products, “DB_dental products”, as a function of the dental attribute values V determined in step b)”. Then see [0303] for examples of “dental attribute values”: “hardness, for example, for a toothbrush; bristle density, for a toothbrush;”.); and
providing the subject with the selected toothbrush, information about the selected toothbrush, or both (See [0340]: “In step d), the target consumer can be presented with a response to advise them of the one or more selected dental product(s) and, preferably, to provide them with directions for their use.”).
Regarding claim 2, Pellissard teaches:
The method of claim 1, wherein the plurality of candidate classifications comprise: a first classification corresponding to a regular or wide arch (See [0376]: “the dental objective is to correct/improve the alignment of the teeth, the dental organ is one or two arches, the dental attribute is a congestion index and/or an occlusion class, and/or a vertical overhang value, and/or a horizontal overhang value,”. The examiner asserts that a congestion index indicating a normal condition meets the claimed “first classification corresponding to a regular…arch”.); a second classification corresponding to a narrow arch (See [0376]: “the dental objective is to correct/improve the alignment of the teeth, the dental organ is one or two arches, the dental attribute is a congestion index and/or an occlusion class, and/or a vertical overhang value, and/or a horizontal overhang value,”. The examiner asserts that a congestion index indicating an abnormal condition meets the claimed “second classification corresponding to a narrow arch”.); and a third classification corresponding to a truncated arch (See [0376]: “the dental objective is to correct/improve the alignment of the teeth, the dental organ is one or two arches, the dental attribute is a congestion index and/or an occlusion class, and/or a vertical overhang value, and/or a horizontal overhang value,”. The examiner asserts that occlusion class (pointing to occlusional instability) is an indicator of a shortened dental arch, and in that way meets the claimed “third classification corresponding to a truncated arch”.).
Regarding claim 3, Pellissard teaches:
The method of claim 2, wherein: each of the candidate classifications is associated with a corresponding angle; and processing the image data to classify the dental arch comprises: measuring a plurality of angles formed between a plurality of combinations of teeth of the dental arch, and selecting one of the candidate classifications that is associated with a smallest of the measured angles (See [0376]: “the dental objective is to correct/improve the alignment of the teeth, the dental organ is one or two arches, the dental attribute is a congestion index and/or an occlusion class, and/or a vertical overhang value, and/or a horizontal overhang value,”. *The examiner asserts that evidentiary reference Fouquet shows in Fig. 4 that the congestion and occlusion indices of Pellissard are characterized by measured angles between pairs of teeth.).
Regarding claim 4, Pellissard teaches:
The method of claim 2, wherein processing the image data to classify the dental arch comprises providing the image data to a trained image classification model to return one or more candidate classifications (See [0266]: “A plurality of neural networks can be trained in order to each determine the value of a respective dental attribute. For example, if the dental objective is to select at least one product for improving breath, neural networks can be trained in order to determine the values of one or more of the following dental attribute(s): presence of tartar, presence of dental plaque, presence of a whitish tongue, lack of saliva.”).
Regarding claim 5, Pellissard teaches:
The method of claim 4, further comprising training an image classification model on a plurality of labeled images of dental arches to generate the trained image classification model (See [0115]-[0116]: “For example, each record of the learning database can include an image of a dental arch and a description identifying, in this image, the depictions of the teeth, or “tooth areas”, and the corresponding tooth numbers. After being trained, the neural network can thus identify, on an image presented thereto, the depictions of the teeth and the corresponding tooth numbers. The second object can be an image, and in particular an image that is identical to the first object, but it is “labeled”, i.e., in which information, and in particular a value for a dental attribute, has been added, for example, in graphical form.”).
Regarding claim 6, Pellissard teaches:
The method of claim 1, wherein processing the image data to identify the dental arch of the user comprises: analyzing the image data to determine whether the image data shows at least a minimum number of teeth; if the image data shows at least the minimum number of teeth, determining that at least a portion of the teeth form the dental arch; and if the image data does not include at least the minimum number of teeth, prompting a user to take one or more additional images until the user returns image data that shows at least the minimum number of teeth (See [0135]: “In one embodiment, the dedicated application guides the operator when they position the mobile telephone. To this end, it analyses, preferably by means of a neural network, the content of the preview image displayed on the screen of the mobile telephone in order to determine whether the angle of the mobile telephone and/or the distance between the mobile telephone and the mouth of the target consumer allows an updated image to be acquired that is well suited for the analysis to be carried out in step b). If this is not the case, it notifies the operator and, preferably, provides them with instructions for modifying said angle and/or said distance.” The examiner asserts that a captured “updated image” that is “well suited for the analysis” includes showing the claimed “minimum number of teeth”, especially given the discussion in [0133] and [0136], in that “observation of the dental arches” is improved “relative to the teeth they want to photograph”.).
Regarding claim 7, Pellissard teaches:
The method of claim 6, wherein either: the image data is from a camera image, and prompting the user to take the one or more additional images comprises prompting the user to use a digital camera to take a new image (See [0135]: “In one embodiment, the dedicated application guides the operator when they position the mobile telephone. To this end, it analyses, preferably by means of a neural network, the content of the preview image displayed on the screen of the mobile telephone in order to determine whether the angle of the mobile telephone and/or the distance between the mobile telephone and the mouth of the target consumer allows an updated image to be acquired that is well suited for the analysis to be carried out in step b). If this is not the case, it notifies the operator and, preferably, provides them with instructions for modifying said angle and/or said distance.”); or the image data is that of a dental impression tray, and prompting the user to take the one or more additional images comprises prompting the subject, or prompting a dental professional to instruct the subject, to bite down on a new dental impression tray (See [0132]-[0133]: “The updated image is preferably an extra-oral image, preferably taken at a distance ranging between 5 cm and 40 cm from the mouth of the target consumer. In one embodiment, the target consumer separates their lips to reveal their teeth. They can simply smile, or pull their lips with their fingers, or push them back with a tool, for example, with a spoon, or use a conventional dental retractor, as shown in FIG. 2 . A dental retractor is a well-known device comprising channels 12 extending around an opening 14. The target consumer places their lips in the channels, which allows them to be separated and improves the observation of the dental arches through the opening.”).
Regarding claim 8, Pellissard teaches:
The method of claim 1, further comprising: receiving additional information about the subject; and when selecting the toothbrush from the data store, also using the additional information to select the toothbrush (See [0138]-[0139]: “In step a), the mobile telephone can also acquire additional information. The additional information is preferably information that cannot be deduced from the analysis of the updated image, or that can only be deduced therefrom with difficulty. The additional information acquired in step a) is referred to as “first additional information” (reference “Ic1” in FIG. 1 ). The first additional information can be sent directly to the processing computer that carries out step 2) and/or can be recorded, with an identifier of the target consumer or of the mobile telephone, in a “DB_Consumers” database that the processing computer has access to in order to execute step c).”).
Regarding claim 9, Pellissard teaches:
The method of claim 8, wherein receiving the additional information about the subject and using the additional information to select the toothbrush comprises: determining an age status of the subject; and only selecting a toothbrush that is associated with the age status of the subject (See [0164]: “Finally, the additional information can contain features of the target consumer, for example: their age;”.).
Regarding claim 10, Pellissard teaches:
The method of claim 8, wherein receiving the additional information about the subject and using the additional information to select the toothbrush comprises: processing the image data to determine a spacing classification of the teeth of the subject; and selecting a toothbrush that is also associated with the spacing classification (See [0182]-[0183]: “The dental attribute can be absolute, for example, it can relate to the whiteness of one or more teeth. Alternatively, the dental attribute can be relative, for example, it can relate to a color difference between two teeth or a gap between two adjacent teeth or an average gap between the teeth depicted on the updated image. Determining the value of the dental attribute can also require a comparison reference that cannot be derived from the updated image. For example, the dental attribute can relate to a previous situation of the target consumer. The comparison reference can be, for example, the value of the dental attribute assessed during a previous cycle of step a) to d).”).
Regarding claim 11, Pellissard teaches:
The method of claim 8, wherein receiving the additional information about the subject and using the additional information to select the toothbrush comprises: determining whether the subject has braces; and only selecting a toothbrush that is associated with braces (See [0164]: “Finally, the additional information can contain features of the target consumer, for example:…whether or not they are wearing an orthodontic appliance, in which case they may be asked to specify the nature of this orthodontic appliance;”.).
Regarding claim 12, Pellissard teaches:
The method of claim 8, wherein receiving the additional information about the subject and using the additional information to select the toothbrush comprises: determining whether the subject has a specified dental condition, wherein the dental condition comprises one or more of the following: gum disease, furcation, or back triangle (See [0162]: “The additional information can also specify one or more “dental” objectives, beyond the single requirement identified from the updated image. For example, the dental objective can be “whitening the teeth” or “reducing plaque”, or “reducing tartar”, or “reducing a soft tissue inflammation”,”.); and selecting a toothbrush that is also associated with the specified dental condition (See [0268]: “In particular, it can select the one or more relevant dental product(s) from a database of dental products, “DB_dental products”, as a function of the dental attribute values V determined in step b)”. Then see [0303] for examples of “dental attribute values”: “hardness, for example, for a toothbrush; bristle density, for a toothbrush;”.).
Regarding claim 13, Pellissard teaches:
A method of treating a dental patient comprising the method of claim 1 (See [0376]: “and, in step c), instead of or in addition to the relevant dental product, a relevant type of orthodontic treatment and/or a duration of a relevant orthodontic treatment is selected, and then, in step d) said relevant type of orthodontic treatment and/or said relevant orthodontic treatment duration are presented;”.).
Pellissard teaches the system of claim 14 for the reasons given in the treatment of claim 1.
Pellissard teaches claim 15 for the reasons given in the treatment of claims 2 and 3.
Pellissard teaches claim 16 for the reasons given in the treatment of claim 4.
Pellissard teaches claim 17 for the reasons given in the treatment of claim 6.
Pellissard teaches claim 18 for the reasons given in the treatment of claims 9, 10, 11, and 12.
Regarding claim 19, Pellissard teaches:
The system of claim 14, further comprising additional programming instructions that are configured to place the toothbrush in a shopping cart of an e-commerce platform (See [0018]: “criteria for delivering the one or more relevant dental product(s) in step d), for example, the delivery mode, the delivery date, the payment terms;”. An e-commerce platform is implied.).
Pellissard teaches the system of claim 20 for the reasons given in the treatment of claim 1.
Contact
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JONATHAN S LEE whose telephone number is (571)272-1981. The examiner can normally be reached 11:30 AM - 7:30 PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Andrew Bee can be reached at (571)270-5183. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Jonathan S Lee/Primary Examiner, Art Unit 2677