DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
2. Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Continued Examination Under 37 CFR 1.114
3. A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on March 6, 2026 has been entered.
Response to Amendment
4. The amendment filed March 6, 2026 has been entered. Claims 1-3, 5-12, and 14-18 remain pending in the application. Applicant’s amendments to the Claims have overcome the objections and 35 U.S.C. 112(b) rejections previously set forth in the Final Office Action mailed December 8, 2025.
Response to Arguments
5. Applicant's arguments filed March 6, 2026 have been fully considered but they are not persuasive.
6. Applicant argues that Minchenkov et al. (U.S. Patent Application Publication No. 2020/0349698 A1), hereinafter referred to as Minchenkov, fails to teach receiving a user input for selecting the identified tooth or gingival region as a reconstruction region.
Examiner replies that even if Minchenkov does not teach the above recited limitation, Brown et al. (U.S. Patent Application Publication No. 2021/0073998 A1), hereinafter referred to as Brown, teaches a user input for selecting a tooth or gingival region as a reconstruction region in the Abstract and Paragraphs 101-103. Thus, receiving a user input for selecting the identified tooth or gingival region as a reconstruction region is taught by the prior art.
7. Applicant argues that Minchenkov and Brown do not teach generating a three-dimensional image “by using only data of the two-dimensional image corresponding to the selected at least one region.”
Examiner replies that the Applicant’s arguments with respect to this limitation are considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Lemchen (U.S. Patent Application Publication No. 2008/0305458 A1) teaches generating a three-dimensional image using only the data of the two-dimensional image corresponding to the selected region in Paragraph 7 and 8.
8. Conclusion: The independent claims and their dependents remain rejected.
Specification
9. The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed. MPEP 606.01 states “Where the title is not descriptive of the invention claimed, the examiner should require the substitution of a new title that is clearly indicative of the invention to which the claims are directed.”
The following title is suggested: “ELECTRONIC DEVICE AND IMAGE PROCESSING METHOD FOR GENERATING A THREE-DIMENSIONAL IMAGE FOR A REGION IN AN ORAL CAVITY”
Claim Rejections - 35 USC § 103
10. 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.
11. The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
12. Claim(s) 1-2, 8-11, and 17-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Minchenkov et al. (U.S. Patent Application Publication No. 2020/0349698 A1), hereinafter referred to as Minchenkov, in view of Brown et al. (U.S. Patent Application Publication No. 2021/0073998 A1), hereinafter referred to as Brown, and Lemchen (U.S. Patent Application Publication No. 2008/0305458 A1).
13. Regarding claim 1, Minchenkov teaches an electronic device comprising: a communication circuit communicatively connected to a three-dimensional scanner (Paragraph 42-43 and Figure 1 teach an electronic device 105 with an intraoral scanner 150, which is a three-dimensional scanner. It also teaches that the electronic device 105 can communicate with the scanner and the scanner can transmit data to the device which means the electronic device has a communication circuit);
an input device (Paragraph 42 and Figure 1 teach an electronic device 105 can have an input device like a keyboard, mouse, or tablet for user input);
at least one memory configured to store a correlation model constructed by modeling a correlation between a two-dimensional image set regarding oral cavities of subjects and a data set in which a tooth region and a gingival region are identified in each image of the two-dimensional image set according to a machine learning algorithm (Paragraph 6 teaches a plurality of intraoral images which is a two-dimensional image set regarding oral cavities. It further teaches using a machine learning model to classify the pixels in the images into dental classes which include the tooth regions and gum or gingival regions. The classified pixels create a probability map and each probability map has a respective intraoral images. Thus, the plurality of probability maps are the data set in which the tooth and gingival regions are identified; Paragraph 38 teaches machine learning segments the image into dental classes which include teeth, gums, and excess material);
and at least one processor, wherein the at least one processor is configured to (Paragraph 154 and Figure 13 teach a processor within the processing device 1302):
access a two-dimensional image regarding a target oral cavity or target diagnosis model received from the three-dimensional scanner through the communication circuit (Paragraph 43 teaches the scanner transmits the intraoral scan data to the computing device. It further teaches the intraoral scan data can be a two-dimensional image; Paragraph 45 teaches the intraoral scan application in the computing device registers or accesses the intraoral images);
use the correlation model to identify a tooth region and a gingival region from the two- dimensional image regarding the target oral cavity or target diagnostic model (Paragraph 6 teaches using a machine learning model to classify pixels into dental classes like a tooth region or gingival regions; Paragraphs 104-105 and Figure 2 teach the intraoral image 248 is input into the correlation model 255 which segments the image into classes of teeth or gum in the probability map 260);
However, Minchenkov is not relied upon for the below claim language: receiving, through the input device, a user input for selecting at least one of the tooth region and the gingival region as a reconstruction region of the target oral cavity or target diagnosis model; and generating, in response to the user input, a three-dimensional image corresponding to the reconstruction region by using only data of the two-dimensional image corresponding to the reconstruction region.
Brown teaches receiving, through the input device, a user input for selecting at least one of the tooth region and the gingival region as a reconstruction region of the target oral cavity or target diagnosis model (Abstract teaches features like the tooth and gingiva can be selected and segmented. Selecting these features teach selecting a reconstruction region under broadest reasonable interpretation; Paragraph 75 teaches the system operates with user input; Paragraph 101-103 teaches the user can select certain features like the teeth or gingiva and based on those selections, a subset of images with those features are selected. The teeth and gingiva are regions in a target oral cavity).
Minchenkov and Brown are considered analogous to the claimed invention because both are in the same field of creating three-dimensional images from intraoral scans. Thus, it would have been obvious to a person holding ordinary skill in the art before the effective filing date to modify the electronic device of identifying the tooth and gingiva regions taught by Minchenkov with creating a selecting a reconstruction region taught by Brown in order to allow users to manipulate the selected teeth or gingiva for later processing like designing a treatment plan or forming orthodontic appliances (Brown Paragraph 103).
However, Minchenkov and Brown are not relied upon for the below claim language: generating, in response to the user input, a three-dimensional image corresponding to the reconstruction region by using only data of the two-dimensional image corresponding to the reconstruction region.
Lemchen teaches generating, in response to the user input, a three-dimensional image corresponding to the reconstruction region by using only data of the two-dimensional image corresponding to the reconstruction region (Paragraph 7 teaches “generating a first three dimensional intra-oral image of the crown of a tooth or crowns of a plurality of selected teeth” and Paragraph 8 teaches generating the three-dimensional image by “using optical scanning … crown of the tooth or crowns of the plurality of selected teeth.” The selected teeth teach a selected reconstruction region and the optical scanning of that region teaches the two-dimensional images. Thus, this teaches creating a three-dimensional image corresponding to the reconstruction region using only the data of the two dimensional images corresponding to the reconstruction region; Paragraph 7 also teaches creating a second three-dimensional image of the root of the selected teeth and Paragraph 10 teaches using the radiographic or magnetic resonance scans of those selected teeth in order to create the three dimensional image of the root. This teaches creating a three dimensional image of the selected region using only data of the two dimensional image corresponding to that region).
Minchenkov, Brown, and Lemchen are considered analogous to the claimed invention because both are in the same field of creating three-dimensional images from intraoral scans. Thus, it would have been obvious to a person holding ordinary skill in the art before the effective filing date to modify the electronic device of identifying the tooth and gingiva regions taught by Minchenkov and Brown with the generation of the three-dimensional image using only data of the two-dimensional image taught by Lemchen in order to provide dimensional accuracy when working on the tooth (Lemchen Paragraph 6).
14. Regarding claim 2, Minchenkov in view of Brown and Lemchen teaches the limitations of claim 1. Minchenkov further teaches the electronic device wherein the data set comprises multiple two-dimensional images, and each of the multiple two-dimensional images is an image in which each of the tooth region and the gingival region is masked in each image of the two-dimensional image set (Paragraph 6 teaches the plurality of probability maps are associated with a respective intraoral image. Thus, it comprises of multiple 2D images. The plurality of probability maps which label the regions as a tooth or gum in the image can be considered the data set; Paragraph 69 teaches the probability map can be considered a mask where the dental classes or tooth and gingival regions are annotated or masked with probability values; Paragraph 97 teaches the image has an associated mask or probability map that indicates the dental classes associated with the pixels in the image; Paragraphs 104-105 and Figure 2 teach the intraoral image 248 is input into the correlation model 255 which outputs a probability map and segments the image into dental classes of teeth or gum.).
15. Regarding claim 8, Minchenkov in view of Brown and Lemchen teaches the limitations of claim 1. Minchenkov further teaches the electronic device wherein the correlation model is a correlation model machine-trained to extract at least one feature of texture, density, color, tooth shape, gingival shape, and intraoral cavity shape of the tooth region and the gingival region identified in each image of the two-dimensional image set (Paragraph 38 teaches the machine learning model or correlation model identifies the teeth, gums, and other materials in the image and segments it; Paragraph 52-53 teaches in the machine learning model or correlation model which is used to label the dental classes in the two-dimensional image, one of the layers in the model extracts the features like the teeth and gum shapes in order to identify the tooth and gum regions),
and derive a correlation between the two-dimensional image set and the data set by using the extracted at least one feature (Paragraph 104-105 and Figure 2 teach the intraoral image 248 is input into the correlation model 255 which outputs a probability map and segments the image into dental classes of teeth or gum. The probability values assigned to each pixel for which class it belongs to can be considered the correlation between the two-dimensional image set, which are the intraoral images, and data set, which are the probability maps).
16. Regarding claim 9, Minchenkov in view of Brown and Lemchen teaches the limitations of claim 1. Minchenkov further teaches the electronic device wherein the machine learning algorithm is one of a deep neural network, a recurrent neural network, a convolutional neural network, a machine learning model for classification-regression analysis, or a reinforcement learning model (Paragraph 53 teaches the machine learning algorithm can be a deep neural network).
17. Regarding claim 10, claim 10 is the method claim of electronic device claim 1 and is accordingly rejected using substantially similar rationale as to that which is set for with respect to claim 1.
18. Regarding claim 11, Minchenkov in view of Brown and Lemchen teaches the limitations of claim 10. Claim 11 is similar in scope to claim 2. Therefore, similar rationale as applied in the rejection of claim 2 applies herein.
19. Regarding claim 17, Minchenkov in view of Brown and Lemchen teaches the limitations of claim 10. Claim 17 is similar in scope to claim 8. Therefore, similar rationale as applied in the rejection of claim 8 applies herein.
20. Regarding claim 18, Minchenkov in view of Brown and Lemchen teaches the limitations of claim 10. Claim 18 is similar in scope to claim 9. Therefore, similar rationale as applied in the rejection of claim 9 applies herein.
21. Claim(s) 3 and 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Minchenkov et al. (U.S. Patent Application Publication No. 2020/0349698 A1), hereinafter referred to as Minchenkov, in view of Brown et al. (U.S. Patent Application Publication No. 2021/0073998 A1), hereinafter referred to as Brown, and Lemchen (U.S. Patent Application Publication No. 2008/0305458 A1), as applied to claim 1 and 10 above, and further in view of Nishimura et al. (U.S. Patent Application Publication No. 2021/0104048 A1), hereinafter referred to as Nishimura.
22. Regarding claim 3, Minchenkov in view of Brown and Lemchen teaches the limitations of claim 1. Minchenkov further teaches the electronic device further comprising a display (Paragraph 42 teaches the computing device includes a display),
However, Minchenkov, Brown, and Lemchen are not relied upon for the below claim language: the electronic device wherein the at least one processor is configured to display, through the display, the two-dimensional image regarding the target oral cavity or target diagnosis model, in which the tooth region and the gingival region are identified.
Nishimura teaches the electronic device wherein the at least one processor is configured to display, through the display (Paragraph 77 teaches an electronic device which a processor and display), the two-dimensional image regarding the target oral cavity or target diagnosis model, in which the tooth region and the gingival region are identified (Paragraph 8 teaches segmenting the tooth region and surrounding region which can be considered the gingival region; Paragraph 38 teaches machine learning segments the image into dental classes which include teeth, gums, and excess material; Paragraph 72 and 76 teaches displaying a masked image from the segmentation on a display).
Minchenkov and Nishimura are considered analogous to the claimed invention because both are in the same field of identifying regions in a two-dimensional image of a scan. Brown and Lemchen are considered analogous to the claimed invention because it is in the same field of creating three-dimensional images from intraoral scans. Thus, it would have been obvious to a person holding ordinary skill in the art before the effective filing date to modify the electronic device that identifies the tooth and gingival region taught by Minchenkov in view of Brown and Lemchen with the displaying of the two-dimensional image with the identified regions taught by Nishimura in order to help the user understand the construction of the teeth (Nishimura Paragraph 76).
23. Regarding claim 12, Minchenkov in view of Brown and Lemchen teaches the limitations of claim 10. Claim 12 is similar in scope to claim 3. Therefore, similar rationale as applied in the rejection of claim 3 applies herein.
24. Claim(s) 5 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Minchenkov et al. (U.S. Patent Application Publication No. 2020/0349698 A1), hereinafter referred to as Minchenkov, in view of Brown et al. (U.S. Patent Application Publication No. 2021/0073998 A1), hereinafter referred to as Brown, and Lemchen (U.S. Patent Application Publication No. 2008/0305458 A1), as applied to claim 1 and 10 above, and further in view of Fang et al. (WIPO Patent Application Publication No. 2022/193909 A1), hereinafter referred to as Fang. The effective filing date of Fang was confirmed through foreign priority document CN 114114769 A which had the same subject matter.
25. Regarding claim 5, Minchenkov in view of Brown and Lemchen teaches the limitations of claim 1. However, Minchenkov, Brown, and Lemchen are not relied upon for the below claim language: generating the three-dimensional image regarding the target oral cavity or target diagnosis model by using a Poisson algorithm to connect multiple points included in the set reconstruction region to each other.
Fang teaches generating the three-dimensional image regarding the target oral cavity or target diagnosis model by using a Poisson algorithm to connect multiple points included in the set reconstruction region to each other (Paragraph 51-53 teaches using the Poisson algorithm to create a three-dimensional model of the teeth based on a point cloud. A three-dimensional model of the teeth is a three-dimensional image regarding the target oral cavity).
Minchenkov, Brown, Lemchen, and Fang are considered analogous to the claimed invention because all are in the same field of creating three-dimensional images of teeth. Thus, it would have been obvious to a person holding ordinary skill in the art before the effective filing date to modify the electronic device that identifies and selects a region for reconstruction taught by Minchenkov in view of Brown and Lemchen with the Poisson algorithm taught by Fang in order to reconstruct a surface that is a gap (Fang Paragraph 53).
26. Regarding claim 14, Minchenkov in view of Brown and Lemchen teaches the limitations of claim 10. Claim 14 is similar in scope to claim 5. Therefore, similar rationale as applied in the rejection of claim 5 applies herein.
27. Claim(s) 6 and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Minchenkov et al. (U.S. Patent Application Publication No. 2020/0349698 A1), hereinafter referred to as Minchenkov, in view of Brown et al. (U.S. Patent Application Publication No. 2021/0073998 A1), hereinafter referred to as Brown, and Lemchen (U.S. Patent Application Publication No. 2008/0305458 A1), as applied to claim 1 and 10 above, and further in view of Rubbert et al. (U.S. Patent Application Publication No. 2002/0006217 A1), hereinafter referred to as Rubbert.
28. Regarding claim 6, Minchenkov in view of Brown and Lemchen teaches the limitations of claim 1. However, Minchenkov fails to teach the electronic device wherein the at least one processor is configured to: generate the three-dimensional image regarding the target oral cavity or target diagnosis model by using an interpolation method to fill a gap between multiple points included in the set reconstruction region.
Brown teaches the electronic device wherein the at least one processor is configured to: generate the three-dimensional image regarding the target oral cavity or target diagnosis model (Paragraph 97 teaches a hole filling engine to fill in holes in the mesh when creating the three-dimensional model).
Minchenkov and Brown are considered analogous to the claimed invention because both are in the same field of creating three-dimensional images from intraoral scans. Thus, it would have been obvious to a person holding ordinary skill in the art before the effective filing date to modify the electronic device of identifying the tooth and gingiva regions taught by Minchenkov with filling in gaps taught by Brown in order to allow users to manipulate the selected teeth or gingiva for later processing like designing a treatment plan or forming orthodontic appliances (Brown Paragraph 103).
However, Minchenkov, Brown, and Lemchen are not relied upon for the below claim language: generating the three-dimensional image regarding the target oral cavity or target diagnosis model by using an interpolation method to fill a gap between multiple points included in the set reconstruction region.
Rubbert teaches generating the three-dimensional image regarding the target oral cavity or target diagnosis model by using an interpolation method to fill a gap between multiple points included in the set reconstruction region (Paragraph 105 teaches creating a three-dimensional image of a tooth from tooth scans; Paragraph 331 and Figure 65 teach an interpolation algorithm to fill in holes or gaps between multiple points in the scan data in three-dimensions).
Minchenkov, Brown, Lemchen, and Rubbert are considered analogous to the claimed invention because all are in the same field of creating three-dimensional images from intraoral scans. Thus, it would have been obvious to a person holding ordinary skill in the art before the effective filing date to modify the electronic device that identifies and selects a region for reconstruction taught by Minchenkov in view of Brown and Lemchen with the interpolation method taught by Rubbert in order to account for missing data in the tooth scan data since a scanner usually cannot capture images of gaps between teeth effectively (Rubbert Paragraph 330-331).
29. Regarding claim 15, Minchenkov in view of Brown and Lemchen teaches the limitations of claim 10. Claim 15 is similar in scope to claim 6. Therefore, similar rationale as applied in the rejection of claim 6 applies herein.
30. Claim(s) 7 and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Minchenkov et al. (U.S. Patent Application Publication No. 2020/0349698 A1), hereinafter referred to as Minchenkov, in view of Brown et al. (U.S. Patent Application Publication No. 2021/0073998 A1), hereinafter referred to as Brown, and Lemchen (U.S. Patent Application Publication No. 2008/0305458 A1), as applied to claim 1 and 10 above, and further in view of Ouyang (U.S. Patent Application Publication No. 2020/0273148 A1).
31. Regarding claim 7, Minchenkov in view of Brown and Lemchen teaches the limitations of claim 1. However, Minchenkov, Brown, and Lemchen are not relied upon for the below claim language: the electronic device wherein the at least one processor is configured to transmit the three-dimensional image regarding the target oral cavity or target diagnosis model to a cloud server.
Ouyang teaches the electronic device wherein the at least one processor is configured to transmit the three-dimensional image regarding the target oral cavity or target diagnosis model to a cloud server (Paragraph 56 teaches transmitting the three-dimensional model to a cloud server; Paragraph 94 teaches creating a three-dimensional image model from oral cavity scans and storing it in the cloud server).
Minchenkov, Brown, Lemchen, and Ouyang are considered analogous to the claimed invention because all are in the same field of creating three-dimensional images from intraoral scans. Thus, it would have been obvious to a person holding ordinary skill in the art before the effective filing date to modify the electronic device that identifies and selects a region taught by Minchenkov in view of Brown and Lemchen with the transmitting the three-dimensional image to the cloud server taught by Ouyang in order to continuously enrich and perfect a three-dimensional image database for future three-dimensional image modeling of the user’s oral cavity (Ouyang Paragraph 95).
32. Regarding claim 16, Minchenkov in view of Brown and Lemchen teaches the limitations of claim 10. Claim 16 is similar in scope to claim 7. Therefore, similar rationale as applied in the rejection of claim 7 applies herein.
Conclusion
33. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
- Shi et al. (U.S. Patent Application Publication No. 2019/0357997 A1) teaches segmenting a person's teeth from an image and creating a treatment plan.
- Sabina et al. (U.S. Patent Application Publication No. 2019/0231490 A1) teaches an intraoral scan of an oral cavity and creating a three-dimensional model.
34. Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRISTINE Y AHN whose telephone number is (571)272-0672. The examiner can normally be reached M-F 9-5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Alicia Harrington can be reached at (571)272-2330. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CHRISTINE YERA AHN/Examiner, Art Unit 2615
/ALICIA M HARRINGTON/Supervisory Patent Examiner, Art Unit 2615
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