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 .
Response to Amendment
Claims 1, 4, 8, 10, and 12-13 are amended. Claims 1-8 and 10-13 are pending in this application.
Claim Rejections - 35 USC § 103
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 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-8 and 10-13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Favorskaya et al., “DIGITAL WATERMARKING OF 3D MEDICAL VISUAL OBJECTS” in view of Weiss et al., US 2021/0059796.
Regarding claim 1, Favorskaya discloses an intra image processing method (Section 1. Introduction, first sentence; digital processing methods) performed by an intraoral image processing device comprising a processor (Abstract, first sentence; medical equipment (a processor is implied) provides 3D models of scanning organs), the method comprising:
obtaining a first intraoral image (Section 5. Embedding and Extraction Schemes, first paragraph; Fig. 3a; and Section 6. Experimental Results, first paragraph; each of sliced images related to 3D model of a single tooth, 3D models of several teeth, or 3D model of a whole jaw; original or host slice); and
obtaining a second intraoral image by embedding input additional information including at least one of a text and an image into at least a partial area of the first intraoral image such that the partial area is modified (Section 4. Selecting Regions for Embedding; Section 5. Embedding and Extraction Schemes, first paragraph; Figs. 3b-3g; and Section 6. Experimental Results, first paragraph; select carefully regions for embedding and corresponding type of transform for embedding; b textual watermark, c ROI watermark (increased in 3 times), d fragile watermark (Figs. 3b-3d are additional information), e watermarked slice after embedding of ROI watermark, f watermarked slice after embedding of ROI and textual watermarks, g watermarked slice after embedding of ROI, textual, and fragile watermarks (Figs. 3e-3g are embedded additional information into second intraoral images)),
wherein the first intraoral image is “two-dimensional” scan data obtained by imaging the surface of the object (Abstract, first sentence; Section 5. Embedding and Extraction Schemes, first paragraph; Fig. 3a and 3e-3g; and Section 6. Experimental Results, first paragraph; medical equipment provides 3D models of scanning organs; each of sliced images related to 3D model of a single tooth, 3D models of several teeth, or 3D model of a whole jaw; original or host slice and embedded slices of original slice).
Favorskaya discloses claim 1 as enumerated above, but Favorskaya does not explicitly disclose the first intraoral image and second intraoral image is three-dimensional scan data and modifying data values that determine a three-dimensional surface of an object corresponding to the partial area as claimed.
However, Weiss discloses intraoral scanner 150 may include a probe (e.g., a hand held probe) for optically capturing three-dimensional structures. Each intraoral image may be a two-dimensional (2D) or 3D image that includes a height map of a portion of a dental site, and may include x, y and z information. The trained machine learning model makes a pixel level decision for each pixel in an input image as to whether that pixel should be adjusted and/or how the pixel should be adjusted to correct the input image (para 0115 and 0303).
Therefore, taking the combined disclosures of Favorskaya and Weiss as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate intraoral scanner 150 may include a probe (e.g., a hand held probe) for optically capturing three-dimensional structures. Each intraoral image may be a two-dimensional (2D) or 3D image that includes a height map of a portion of a dental site, and may include x, y and z information. The trained machine learning model makes a pixel level decision for each pixel in an input image as to whether that pixel should be adjusted and/or how the pixel should be adjusted to correct the input image as taught by Weiss into the invention of Favorskaya for the benefit of identifying, generating and/or correcting margin lines and/or other dental features in digital models (Weiss: para 0001).
Regarding claim 2, the intra image processing method of claim 1, Favorskaya in the combination further disclose comprising identifying an additional information input area for displaying the additional information in the first intraoral image (Section 4. Selecting Regions for Embedding; Section 5. Embedding and Extraction Schemes, second paragraph; and Section 6. Experimental Results, first paragraph).
Regarding claim 3, the intra image processing method of claim 2, Favorskaya in the combination further disclose wherein the identifying of the additional information input area comprises identifying the additional information input area in remaining areas other than an oral cavity area of the first intraoral image (Section 4. Selecting Regions for Embedding; Section 5. Embedding and Extraction Schemes, second paragraph; and Section 6. Experimental Results, first paragraph).
Regarding claim 4, the intra image processing method of claim 2, Favorskaya in the combination further disclose comprising
receiving a selection of at least one of a tooth and gingiva as a target (Section 5. Embedding and Extraction Schemes, first paragraph),
wherein the identifying of the additional information input area comprises identifying the additional information input area in remaining areas other than an area within a certain range from the at least one of the tooth and the gingiva (Section 4. Selecting Regions for Embedding; Section 5. Embedding and Extraction Schemes, second paragraph; and Section 6. Experimental Results, first paragraph).
Regarding claim 5, the intra image processing method of claim 2, Favorskaya and Weiss further disclose wherein the identifying of the additional information input area comprises identifying the additional information input area from the first intraoral image by using a neural network trained (Weiss: para 0140; a trained neural network) to identify additional information input areas from a plurality of intraoral images (Favorskaya: Abstract; Section 4. Selecting Regions for Embedding; Section 5. Embedding and Extraction Schemes, second paragraph; and Section 6. Experimental Results, first paragraph).
Regarding claim 6, the intra image processing method of claim 2, Favorskaya in the combination further disclose comprising
outputting a user interface screen for selecting the additional information input area (Figs. 3b-3d and Section 6. Experimental Results, first paragraph),
wherein the identifying of the additional information input area comprises identifying a selected area as the additional information input area in response to the user interface screen (Section 4. Selecting Regions for Embedding; Section 5. Embedding and Extraction Schemes, second paragraph; and Section 6. Experimental Results, first paragraph).
Regarding claim 7, the intra image processing method of claim 2, Favorskaya in the combination further disclose comprising outputting at least one of a user interface screen on which the identified additional information input area is displayed and a user interface screen on which the input additional information is displayed in the identified additional information input area (Figs. 3b-3d and Section 6. Experimental Results, first paragraph).
Regarding claim 8, the intra image processing method of claim 7, Favorskaya in the combination further disclose wherein,
when the input additional information has a size greater than or equal to a predetermined size and when there are a plurality of additional information input areas, the outputting of the user interface screen on which the input additional information is displayed comprises outputting an identifier indicating a position of the additional information input area instead of the additional information, or outputting the additional information input area in a reduced size (Section 4. Selecting Regions for Embedding; Section 5. Embedding and Extraction Schemes; Figs. 3b-3d; and Section 6. Experimental Results, first paragraph).
Regarding claim 10, the intra image processing method of claim 1, Favorskaya and Weiss in the combination further disclose wherein
the obtaining of the second intraoral image into which the additional information is embedded comprises obtaining the second intraoral image by embedding the additional information into the first intraoral image by replacing variables or color values of pixels of a two-dimensional image mapped to the first intraoral image (Favorskaya: Section 4. Selecting Regions for Embedding; Section 5. Embedding and Extraction Schemes, first paragraph; Section 6. Experimental Results, first paragraph); and Section 7. Conclusions), thereby modifying the data values that determined the three-dimensional surface of the object (Weiss: para 0303).
Regarding claim 11, the intra image processing method of claim 1, Favorskaya in the combination further disclose wherein
the first intraoral image is the three-dimensional scan data expressed as at least one of dots and mesh (Section 1. Introduction; 3D models are 3D polygonal mesh
models), and
the obtaining of the second intraoral image into which the additional information is embedded comprises obtaining the second intraoral image by embedding the additional information in the first intraoral image by changing a color of at least one of a point, a vertex, and a polygon including the vertex of the first intraoral image located at a position corresponding to an outline of at least one of a text and an image included in the additional information (Section 4. Selecting Regions for Embedding; Section 5. Embedding and Extraction Schemes, first paragraph; Figs. 3b-3g; and Section 6. Experimental Results, first paragraph).
Regarding claim 12, this claim recites substantially the same limitations that are performed by claim 1 above, and it is rejected for the same reasons.
Regarding claim 13, this claim recites substantially the same limitations that are performed by claim 1 above, and it is rejected for the same reasons.
Response to Arguments
Applicant's arguments with respect to claims 1-8 and 10-13 have been considered but are moot in view of the new ground(s) of rejection.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to VAN D HUYNH whose telephone number is (571)270-1937. The examiner can normally be reached 8AM-6PM.
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/VAN D HUYNH/Primary Examiner, Art Unit 2665
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