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 § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
1. Claims 5-6 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 5 recites “the plurality of points is computed based on at least one of”, and it is not clear which dependent features are mutually inclusive, so the Examiner treats all of the dependent features as individual features where only one feature is required to satisfy “at least one of”.
Claim 6 recites “the new surface quality score” and it is not clear if this is the same as the second quality score.
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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(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.
2. Claims 1-9, 12, 14, 16-17, and 19-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US 20210321872 A1: Ofer Saphier et al., (herein after “Saphier”).
Regarding claim 1, An intraoral scanning system (Saphier, §Abstract: “A method of intraoral scanning includes receiving a first one or more intraoral scans of a patient's oral cavity”), comprising:
an intraoral scanner (Saphier, P[0028]: “ a system comprises: an intraoral scanner to generate the one or more intraoral scans”); and
a computing device (Saphier, P[0028]: “ and a computing device connected to the intraoral scan via a wired or wireless connection, the computing device to perform the method”), wherein the computing device is to:
receive a plurality of intraoral scans of a dental site from the intraoral scanner during an intraoral scanning session (Saphier, P[0029]: “ receiving a first one or more intraoral scans of a patient's oral cavity”);
generate a three-dimensional (3D) surface of the dental site based on the plurality of intraoral scans (Saphier, P[0029]: “automatically generating a first three-dimensional surface of the first one of the upper dental arch or the lower dental arch using the first one or more intraoral scans”);
determine a first surface quality score for a first region of the 3D surface (Saphier, P[0573]: “processing logic may additionally or alternatively determine a clarity value and/or quality value for surfaces … ”);
output a first view of the 3D surface to a display, wherein the first region of the 3D surface is shown with a first visualization associated with the first surface quality score (Saphier, P[0573]: “Processing logic may mark such surfaces (or portions of surfaces) that have low quality values on the 3D model. For example, the surface quality scores for one or more surface portions may be compared to a quality threshold. Any surfaces (or surface portions) having surface quality scores that are below the quality threshold may be marked or highlighted.”, and see Fig. 7, which shows the process generates the 3D surface from the intraoral scanning and shows that the process of updating the scanned models is iterative.);
receive one or more additional intraoral scans of the dental site during the intraoral scanning session (Saphier, P[0574]: “processing logic 1600 determines which areas to rescan using the techniques set forth in US Publication No. 2021/0059796, which is incorporated by reference herein.”);
update the 3D surface based on the one or more additional intraoral scans (Saphier, Fig. 7 shows iterative scanning which updates the 3D surface based on the new scanning data acquired.);
determine a new surface quality score for the first region of the updated 3D surface (Saphier, due to Fig. 7 showing that the process is iterative, a new surface quality score is determined as described above and disclosed in P[0573]).; and
output a first view of the updated 3D surface to the display, wherein the first region of the updated 3D surface is shown with a second visualization associated with the new surface quality score (Saphier, P[0573]: “Processing logic may mark such surfaces (or portions of surfaces) that have low quality values on the 3D model. For example, the surface quality scores for one or more surface portions may be compared to a quality threshold. Any surfaces (or surface portions) having surface quality scores that are below the quality threshold may be marked or highlighted.”, and see Fig. 7, which shows the process generates the 3D surface from the intraoral scanning and shows that the process of updating the scanned models is iterative.);
Regarding claim 2, wherein the computing device is further to:
input at least one of the first region of the 3D surface or the plurality of intraoral scans associated with the first region into a trained machine learning model, wherein the trained machine learning model outputs the first surface quality score is disclosed by Saphier in P[0573]: “processing logic may additionally or alternatively determine a clarity value and/or quality value for surfaces”, where Saphier uses “processing logic” instead of a machine learning model. However, Saphier also discloses in P[0461]: “processing logic inputs the training data into an untrained machine learning model. At block 906, processing logic trains the untrained ML model based on the training dataset to generate a trained ML model that identifies restorative objects in intraoral scans, 2D images, 3D surfaces and/or projections of 3D surfaces … In one embodiment, the machine learning model is trained based on the training dataset to generate a trained machine learning model that performs segmentation of intraoral scans, images and/or 3D surfaces (or projections of 3D surfaces) into dental classes. This may include performing pixel-level classification of intraoral scans, 3D surfaces, images, etc. into dental classes. The machine learning model may also be trained to output one or more other types of predictions, image-level classifications (e.g., role classifications), pixel-level classifications, patch-level classifications (where a patch is a group of pixels), decisions, and so on.”, and therefore contemplates and discloses utilizing a trained machine learning model to output quality scores from pixel level classification.
Regarding claim 3, wherein the plurality of intraoral scans are generated by projecting a structured light (Saphier, P[0245]: “for scanners 150 that use structured light (SL) projectors, the intraoral scan application 115 and/or intraoral scanner 150 can automatically turn on and off the structured light (SL) projectors.”) comprising a plurality of features onto the dental site and capturing the plurality of features on the dental site, and wherein the first surface quality score is determined based at least in part on a quantity of the plurality of features associated with the first region of the 3D surface (Saphier, P[0562]: “determine quality ratings for the first 3D surface and the second 3D surface, and use the quality ratings to determine which 3D surface to use in generating a 3D model or in updating a previously generated 3D model. Quality ratings may be determined for different regions or parts of the first 3D surface and the second 3D surface. Quality ratings may be determined using multiple criteria, such as number of data points (e.g., density of a point cloud), existence, number and/or size of voids, angle of scanner to 3D surface, uncertainty associated with registration between scans in a 3D surface, amount of moving tissue, gum tissue and/or other objects obscuring the preparation tooth (e.g., obscuring the margin line), a cost function value, and so on.”).
Regarding claim 4, wherein the 3D surface is generated based on a plurality of points from the plurality of intraoral scans (generic 3D scanning), and wherein the computing device is further to:
determine a quality score for each point of the plurality of points (Saphier, P[0562]: “ Quality ratings may be determined for different regions or parts of the first 3D surface and the second 3D surface. Quality ratings may be determined using multiple criteria, such as number of data points (e.g., density of a point cloud), existence, number and/or size of voids, angle of scanner to 3D surface, uncertainty associated with registration between scans in a 3D surface, amount of moving tissue, gum tissue and/or other objects obscuring the preparation tooth (e.g., obscuring the margin line), a cost function value, and so on.”);
determine a subset of the plurality of points that are associated with the first region (Saphier, P[0563]: “logic divides the first 3D surface and the second 3D surface into superpixels (or other equivalent structure in 3D). A superpixel is a group of pixels that share common characteristics (e.g., like pixel intensity). In one embodiment, each superpixel may be assigned a quality score. Superpixels associated with the first 3D surface may be compared to overlapping superpixels from the second 3D surface, and superpixels with a highest quality value may be selected.”); and
determine the first surface quality score for the first region based on quality scores of the subset of the plurality of points and on a quantity of the subset of the plurality of points (Saphier, P[0563]: “each superpixel may be assigned a quality score. Superpixels associated with the first 3D surface may be compared to overlapping superpixels from the second 3D surface, and superpixels with a highest quality value may be selected.”).
Regarding claim 5, as best understood, wherein the quality score for a point of the plurality of points is computed based on at least one of:
a) a distance between the point and at least one of a first camera or a second camera of the intraoral scanner that captured the point in generation of an intraoral scan of the plurality of intraoral scans and b) a distance between the first camera and the second camera;
c) a distance between the point and a camera of the intraoral scanner that captured the point in generation of the intraoral scan and d) a distance between the camera and a structured light projector of the intraoral scanner that projected structured light to the point;
a number cameras of the intraoral scanner that captured the point in generation of the intraoral scan;
a spot size associated with the point;
an angle between a normal to the 3D surface at the point and an imaging axis of the camera that captured the point in generation the intraoral scan; or
a type of material of the dental site at the point.
Is disclosed by Saphier in P[0562]: “ Quality ratings may be determined for different regions or parts of the first 3D surface and the second 3D surface. Quality ratings may be determined using multiple criteria, such as number of data points (e.g., density of a point cloud), existence, number and/or size of voids, angle of scanner to 3D surface, uncertainty associated with registration between scans in a 3D surface, amount of moving tissue, gum tissue and/or other objects obscuring the preparation tooth (e.g., obscuring the margin line), a cost function value, and so on.”, and further in P[0563]: “logic divides the first 3D surface and the second 3D surface into superpixels (or other equivalent structure in 3D). A superpixel is a group of pixels that share common characteristics (e.g., like pixel intensity). In one embodiment, each superpixel may be assigned a quality score. Superpixels associated with the first 3D surface may be compared to overlapping superpixels from the second 3D surface, and superpixels with a highest quality value may be selected.”
Regarding claim 6, as best understood, the Examiner would like to note that the language of claim 6 does not include that the various grading rubrics are different rubricks other than their numbering.
further comprising:
determining a first grading rubric for the first region (Saphier, P[0562]: “Quality ratings may be determined for different regions or parts of the first 3D surface and the second 3D surface. Quality ratings may be determined using multiple criteria”), where the quality ratings are evaluated based on a “rubric” or set of rules or steps to follow.;
determining the first visualization corresponding to the first surface quality score and the second visualization corresponding to the new surface quality score based on the first grading rubric (Saphier, P[0311]: “Intraoral scan application 115 may additionally mark and/or highlight specific segments of the margin line that are unclear, uncertain, and/or indeterminate. Additionally, or alternatively, intraoral scan application 115 may mark and/or highlight specific areas (e.g., a surface) that is unclear, uncertain and/or indeterminate. For example, segments of the margin line that are acceptable may be shown in a first color (e.g., green), while segments of the margin line that are unacceptable may be shown in a second color (e.g., red).”), where scanned sections that are deemed unsatisfactory are marked for rescanning which produces another visualization, and due to it being an iterative process, it can produce a third visualization. Furthermore, see P[0573]: “mark such surfaces (or portions of surfaces) that have low quality values on the 3D model. For example, the surface quality scores for one or more surface portions may be compared to a quality threshold. Any surfaces (or surface portions) having surface quality scores that are below the quality threshold may be marked or highlighted.”, and P[0574]: “processing logic 1600 determines which areas to rescan”);
determining a third surface quality score for a second region of the 3D surface (Saphier, P[0573]: “mark such surfaces (or portions of surfaces) that have low quality values on the 3D model. For example, the surface quality scores for one or more surface portions may be compared to a quality threshold. Any surfaces (or surface portions) having surface quality scores that are below the quality threshold may be marked or highlighted.”),
determining a second grading rubric for the second region (which may be the same as the first grading rubric, Saphier, P[0562]: “Quality ratings may be determined for different regions or parts of the first 3D surface and the second 3D surface. Quality ratings may be determined using multiple criteria”), where the quality ratings are evaluated based on a “rubric” or set of rules or steps to follow.); and
determining a third visualization corresponding to the third surface quality score based on the second grading rubric, wherein the second region of the 3D surface is shown with the third visualization, where the process of Saphier is iterative and indicates to rescan when the quality of the portion of a scan has too low of quality and the visualization of the 3D model is updated each iteration. Saphier, P[0573]: “mark such surfaces (or portions of surfaces) that have low quality values on the 3D model. For example, the surface quality scores for one or more surface portions may be compared to a quality threshold. Any surfaces (or surface portions) having surface quality scores that are below the quality threshold may be marked or highlighted (for rescanning).”, see P[0295]: “may provide feedback on areas that fail to meet certain quality criteria and that might benefit from rescanning to generate a better quality 3D model of a dental site.”
Regarding claim 7, wherein the computing device is further to:
determine whether a restorative treatment or an orthodontic treatment is to be performed for the dental site (Saphier, P[0321]: “re-computations can be performed to determine updates for segmentation, role identification, restorative workflow identification, orthodontic workflow identification”); and
select a grading rubric (list of steps) that associates surface quality scores with visualizations based on whether the restorative treatment or the orthodontic treatment is selected (Saphier, P[0103]: “automatically initiating a restorative dental procedure workflow, wherein the prescription is for a dental prosthesis; and responsive to determining that the user only performs orthodontic dental procedures, automatically initiating an orthodontic dental procedure workflow, wherein the prescription is for orthodontia.”), where each workflow has their own list of steps/grading rubric, where the workflow dictates which surface quality score is associated with which visualizations based on restorative treatment vs orthodontic treatment.
Regarding claim 8, wherein the computing device is further to:
receive a plurality of two-dimensional (2D) images of the dental site (Saphier, P[0129]: “receiving an intraoral scan of an oral cavity, the intraoral scan having been generated by an intraoral scanner comprising a probe inserted into the oral cavity; receiving one or more two-dimensional (2D) images generated by the intraoral scanner”); and
determine a quantity of the plurality of 2D images that depict the first region, Saphier, P[0296]: “With a few number of scans for a surface at a particular area, the area may be produced but with low certainty or low quality. Intraoral scan application 115 may flag such areas that have too few data points for further scanning.”;
wherein the first surface quality score for the first region is based at least in part on the quantity of the plurality of 2D images that depict the first region, where the number of images/scans directly influences the quality of the output, where more images means higher quality since there is more information present, and Saphier discloses rescanning an area when the quality is deemed to be insufficient, P[0295]: “Intraoral scan application 115 may provide feedback on areas that fail to meet certain quality criteria and that might benefit from rescanning”, and P[0296]: “If insufficient 2D color images of an area have been generated, then the color quality for that area may be low. Accordingly, intraoral scan application 115 may flag an area for further scanning to receive additional color information for that area. In another example, surface quality (e.g., number of known points on a surface) may depend on a number of scans that have been received for that surface. With a few number of scans for a surface at a particular area, the area may be produced but with low certainty or low quality. Intraoral scan application 115 may flag such areas that have too few data points for further scanning.”
Regarding claim 9, wherein the computing device is further to:
determine a first roughness and a first resolution associated with the first region of the 3D surface (Saphier, P[0125]: “receiving a second intraoral scan generated by the intraoral scanner; determining distances of points depicted in the second intraoral scan from the probe of the intraoral scanner; determining those points in the second intraoral scan having a distance that is less than or equal to the distance threshold; comparing those points in the second intraoral scan having distances that are less than or equal to the distance threshold to those points in the intraoral scan having distances that are less than or equal to the distance threshold; and determining, based on the comparing, points that have distances that are less than or equal to the distance threshold in both the intraoral scan and the second intraoral scan; wherein the one or more criteria comprise a criterion that the amount of points that have distances that are less than or equal to the distance threshold are shared by a plurality of intraoral scans.”, where the Specification of the present Application describes roughness in P[0041]: “the first roughness is determined based on distances between points from one or more intraoral scans of the plurality of intraoral scans”);
wherein the first surface quality score (Saphier, P[0133]: “for each segment of the one or more segments, determining a first quality rating of the segment if the first three-dimensional surface is used”) is determined based at least in part on the first roughness and the first resolution (Saphier, P[0295]: “intraoral scan application 115 analyzes a generated 3D surface or 3D model and determines one or more quality ratings for the 3D model or surface.”, therefore, the quality rating is based on the resolution as well, P[0035]: “the three-dimensional model comprises a single variable resolution three-dimensional surface, wherein the first portion of the single variable resolution three-dimensional surface has the first resolution and the second portion of the variable resolution three-dimensional surface has the second resolution.”).
Regarding claim 12, wherein the intraoral scanner comprises a plurality of cameras each having at least one of a different position or a different orientation in the intraoral scanner (Saphier, P[0244]: “images of intraoral objects will initially appear first in the FOV of the front cameras of scanner 150 (if scanner includes multiple cameras)”, where the scanner has multiple cameras in different positions.), and wherein the computing device is further to:
receive a plurality of two-dimensional (2D) images each generated by a different camera of the plurality of cameras, where each camera in the scanner takes its own image, P[0244]: “images of intraoral objects will initially appear first in the FOV of the front cameras of scanner 150 (if scanner includes multiple cameras)”;
determine a 2D image of the plurality of 2D images associated with improved intraoral scan quality, where the images are displayed to the user and if the quality is too low, the user is instructed to rescan to improve quality, P[0295]: “Intraoral scan application 115 may provide feedback on areas that fail to meet certain quality criteria and that might benefit from rescanning”; and
output the determined 2D image to the display, wherein responsive to output of the determined 2D image, a doctor using the intraoral scanner will reposition the intraoral scanner in a manner that causes the improved intraoral scan quality (Saphier, P[0295]: “Intraoral scan application 115 may provide feedback on areas that fail to meet certain quality criteria and that might benefit from rescanning”), where the rescanning prompts the doctor to rescan the low quality area which requires the repositioning of the scanner to acquire information related to the low quality area to improve the scan.
Regarding claim 14, output a notice to at least one of stop generating new intraoral scans of the first region or to move on to a next region (Saphier, P[0094]: “the intraoral scanner to begin generating the plurality of intraoral scans or to stop generating intraoral scans based on whether the one or more two-dimensional images depict an interior of a mouth.”, and Saphier, P[0333]: “The system can decide to output a pop-up warning to the dentist”).
The rest of the features of claim 14 are recited nearly identically to those recited in claim 1. Claim 14 is rejected for reasons analogous to those discussed above in conjunction with claim 1.
Regarding claim 16, wherein to determine that the surface quality score for the first region fails to satisfy the one or more criteria the computing device is to:
determine that the surface quality score for the first region is below a surface quality threshold and that additional surface quality scores of one or more additional regions proximate to the first region are at or above the surface quality threshold (Saphier, P[0295]: “Different quality ratings may be assigned to different portions of the 3D model, such as to portions of a margin line, areas of a preparation tooth, areas surrounding a preparation tooth, and so on. Intraoral scan application 115 may provide feedback on areas that fail to meet certain quality criteria and that might benefit from rescanning to generate a better quality 3D model of a dental site.”, where rescanning is an option provided when a threshold is not met, P[0348]: “Quality values above a threshold may be determined to be a scanning success. This can also include assigning quality values to portions or regions of 3D surfaces or 3D models. Portions or regions with quality values that are below a threshold may be flagged for rescanning.”).
Regarding claim 17, determine a first surface quality score for a first region of the 3D surface based at least in part on a) a quantity of points, from the plurality of points, that are associated with the first region and b) quality scores of the points that are associated with the first region (Saphier, P[0562]: “determine quality ratings for the first 3D surface and the second 3D surface, and use the quality ratings to determine which 3D surface to use in generating a 3D model or in updating a previously generated 3D model. Quality ratings may be determined for different regions or parts of the first 3D surface and the second 3D surface. Quality ratings may be determined using multiple criteria, such as number of data points (e.g., density of a point cloud), existence, number and/or size of voids, angle of scanner to 3D surface, uncertainty associated with registration between scans in a 3D surface, amount of moving tissue, gum tissue and/or other objects obscuring the preparation tooth (e.g., obscuring the margin line), a cost function value, and so on.”).;
The rest of the features of claim 17 are recited nearly identically to those recited in claim 1. Claim 17 is rejected for reasons analogous to those discussed above in conjunction with claim 1.
Claim 19 recites features nearly identical to those recited in claim 9. Claim 19 is
rejected for reasons analogous to those discussed above in conjunction with claim 9.
Regarding claim 20, wherein:
the first resolution is determined based at least in part on the quantity of points that are associated with the first region, where the resolution is directly related to the quantity of data points, where more data points equals higher resolution, (Saphier, P[0562]: “determine quality ratings for the first 3D surface and the second 3D surface, and use the quality ratings to determine which 3D surface to use in generating a 3D model or in updating a previously generated 3D model. Quality ratings may be determined for different regions or parts of the first 3D surface and the second 3D surface. Quality ratings may be determined using multiple criteria, such as number of data points (e.g., density of a point cloud), existence, number and/or size of voids, angle of scanner to 3D surface, uncertainty associated with registration between scans in a 3D surface, amount of moving tissue, gum tissue and/or other objects obscuring the preparation tooth (e.g., obscuring the margin line), a cost function value, and so on.”).; and
the first roughness is determined based on distances between the points associated with the first region and nearest points on the 3D surface (Saphier, P[0125]: “receiving a second intraoral scan generated by the intraoral scanner; determining distances of points depicted in the second intraoral scan from the probe of the intraoral scanner; determining those points in the second intraoral scan having a distance that is less than or equal to the distance threshold; comparing those points in the second intraoral scan having distances that are less than or equal to the distance threshold to those points in the intraoral scan having distances that are less than or equal to the distance threshold; and determining, based on the comparing, points that have distances that are less than or equal to the distance threshold in both the intraoral scan and the second intraoral scan; wherein the one or more criteria comprise a criterion that the amount of points that have distances that are less than or equal to the distance threshold are shared by a plurality of intraoral scans.”, where the Specification of the present Application describes roughness in P[0041]: “the first roughness is determined based on distances between points from one or more intraoral scans of the plurality of intraoral scans”).
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.
3. Claims 10-11, 13, and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Saphier in view of US 20180028065 A1: Gilad Elbaz et al., (herein after “Elbaz”).
Regarding claim 10, wherein the computing device is further to:
determine one or more scanning suggestions that, if implemented, would cause the new surface quality score for the first region to improve (Saphier, P[0205]: “The system includes logic to determine what portions of data to use from each scan to generate a highest quality 3D model. Additionally, after each scan/rescan, the system may compute and show occlusal surfaces, margin lines, insertion path (including any insertion path problems), and so on.”, where rescanning improves the surface quality score.); and
output the one or more scanning suggestions to the display (Saphier, P[0209]: “one or more output devices (e.g., a display, printer, touchscreen, speakers, etc.), and/or other hardware components.”).
Even though Saphier does not explicitly disclose determine that the new surface quality score for the first region has failed to improve for a threshold amount of time and that the new surface scanning quality score is below a surface quality threshold, Elbaz discloses determine that the new surface quality score for the first region has failed to improve for a threshold amount of time and that the new surface scanning quality score is below a surface quality threshold through the use of dynamic scanning times as disclosed by Elbaz in P[0184]: “The method or apparatus may determine the quality of the scanned data 709, such as the quality of the scanned surface data, and may adjust the scanning duration(s) (e.g., the second duration) accordingly. An estimate of quality may be made automatically, for example, based on blurring, over- or under-saturation, etc. For example, the duration of a scanning scheme may be dynamically adjusted (e.g., increased or decreased) based on the quality of the scans in this modality; if the prior x scans in this modality are below a first (e.g., minimum) quality threshold (quantifying one or more of: blurring, over-saturation, under-saturation, etc.) the scan duration for that modality, d.sub.i, may be increased. Scan time may be reduced if the duration of the scan is above a minimum duration and the quality is above a second quality threshold (which may be the same as the first quality threshold or greater than the first quality threshold). Reducing the scan duration may allow the duration of other scanning modalities to increase and/or the rate of switching between scanning modalities to increase. Alternatively or additionally, the scan duration for a modality may be adjusted based on the completeness of the 3D model being reconstructed. For example, when scanning a region of the 3D model having a more complete surface model (e.g., regions over which the surface model has already been made), the duration of the surface scan may be decreased, and the duration of the penetrative scan (e.g., a reflective scan using a near-IR wavelength, or a trans-illumination scan using a near-IR wavelength) may be increased to increase the resolution and/or extent of the internal structures. Similarly, the frequency of the scanning in each mode may be adjusted dynamically by the apparatus. Any of the methods and apparatuses described herein may also be configured to give feedback to the user to slow down or add scans from a specific angle by showing these missing regions or angles in the 3D graphical display.”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Saphier to incorporate dynamic scan times, as taught by Elbaz, to arrive at the claimed invention discussed above. Such a modification is the result of combining prior art elements according to known methods to yield predictable results. It is predictable that the proposed modification would have provided the benefit of reducing computational load dynamically based on detected surface quality.
Regarding claim 11, wherein the computing device is further to:
determine that the new surface quality score for the first region has failed to improve for a threshold amount of time and that the new surface scanning quality score is below a surface quality threshold is disclosed by Elbaz in P[0184]: “The method or apparatus may determine the quality of the scanned data 709, such as the quality of the scanned surface data, and may adjust the scanning duration(s) (e.g., the second duration) accordingly. An estimate of quality may be made automatically, for example, based on blurring, over- or under-saturation, etc. For example, the duration of a scanning scheme may be dynamically adjusted (e.g., increased or decreased) based on the quality of the scans in this modality; if the prior x scans in this modality are below a first (e.g., minimum) quality threshold (quantifying one or more of: blurring, over-saturation, under-saturation, etc.) the scan duration for that modality, d.sub.i, may be increased. Scan time may be reduced if the duration of the scan is above a minimum duration and the quality is above a second quality threshold (which may be the same as the first quality threshold or greater than the first quality threshold). Reducing the scan duration may allow the duration of other scanning modalities to increase and/or the rate of switching between scanning modalities to increase. Alternatively or additionally, the scan duration for a modality may be adjusted based on the completeness of the 3D model being reconstructed. For example, when scanning a region of the 3D model having a more complete surface model (e.g., regions over which the surface model has already been made), the duration of the surface scan may be decreased, and the duration of the penetrative scan (e.g., a reflective scan using a near-IR wavelength, or a trans-illumination scan using a near-IR wavelength) may be increased to increase the resolution and/or extent of the internal structures. Similarly, the frequency of the scanning in each mode may be adjusted dynamically by the apparatus. Any of the methods and apparatuses described herein may also be configured to give feedback to the user to slow down or add scans from a specific angle by showing these missing regions or angles in the 3D graphical display.”; and
increase a zoom setting for the first region (Saphier, P[0297]: “The automatically generated trajectory may additionally or alternatively zoom in on the identified problem areas.”).
Regarding claim 13, wherein the computing device is further to:
determine that the new surface quality score for the first region has failed to improve for a threshold amount of time is disclosed by Elbaz in P[0184]: “The method or apparatus may determine the quality of the scanned data 709, such as the quality of the scanned surface data, and may adjust the scanning duration(s) (e.g., the second duration) accordingly. An estimate of quality may be made automatically, for example, based on blurring, over- or under-saturation, etc. For example, the duration of a scanning scheme may be dynamically adjusted (e.g., increased or decreased) based on the quality of the scans in this modality; if the prior x scans in this modality are below a first (e.g., minimum) quality threshold (quantifying one or more of: blurring, over-saturation, under-saturation, etc.) the scan duration for that modality, d.sub.i, may be increased. Scan time may be reduced if the duration of the scan is above a minimum duration and the quality is above a second quality threshold (which may be the same as the first quality threshold or greater than the first quality threshold). Reducing the scan duration may allow the duration of other scanning modalities to increase and/or the rate of switching between scanning modalities to increase. Alternatively or additionally, the scan duration for a modality may be adjusted based on the completeness of the 3D model being reconstructed. For example, when scanning a region of the 3D model having a more complete surface model (e.g., regions over which the surface model has already been made), the duration of the surface scan may be decreased, and the duration of the penetrative scan (e.g., a reflective scan using a near-IR wavelength, or a trans-illumination scan using a near-IR wavelength) may be increased to increase the resolution and/or extent of the internal structures. Similarly, the frequency of the scanning in each mode may be adjusted dynamically by the apparatus. Any of the methods and apparatuses described herein may also be configured to give feedback to the user to slow down or add scans from a specific angle by showing these missing regions or angles in the 3D graphical display.”; and
make a determination that additional intraoral scans of the first region will not improve the updated surface quality score for the region is disclosed when the program determines that the model is complete and no longer highlights problem areas in the scan which is disclosed by Saphier in P[0404]: “When scanning of a segment (e.g., upper or lower dental arch) is complete, 3D model generator 276 performs a more accurate registration and stitching of intraoral scans 248 from input data 262 to generate a 3D model 278 of the completed segment.”, and this feature is also disclosed by Elbaz in at least P[0185]: “Once sufficient scanning area has been completed, the combined 3D model of the intraoral region may be assembled using the scanned data 711”, and P[0117]: “The durations of each of the scans (e.g., the scanning time for each mode) may be fixed, it it may be adjustable. For example the duration of the penetrative scan (d) may be dynamically adjusted (e.g., increased or decreased) during scanning base on the quality of the images received, the completeness of the 3D reconstruction of internal structures, etc. Similarly, the duration of the surface scan may be dynamically adjusted during scanning based on the quality of the image(s) being scanned (e.g., the prior images and/or the current image, etc.), the completeness of the 3D surface model for the region being scanned, etc.”.
Claim 15 recites features nearly identical to those recited in claim 13. Claim 15 is
rejected for reasons analogous to those discussed above in conjunction with claim 13.
4. Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Saphier in view of US 20210059796 A1: Assaf Weiss et al., (herein after “Weiss”).
Regarding claim 18, wherein the computing device is further to:
input data for the plurality of points from the one or more of the plurality of intraoral scans into a trained machine learning model (Saphier, uses a trained model for classification that uses the plurality of points from the scans, P[0007]: “comprises inputting the first one or more intraoral scans into a machine learning model that has been trained to classify intraoral scans”), wherein the trained machine learning model outputs the quality score for each of the plurality of points. Saphier does not explicitly disclose that their machine learning model is for determining a quality score.
However, Weiss discloses utilizing a machine learning model to determine quality scores, P[0011]: “the trained machine learning model further outputs an indication for at least a section of the margin line as to whether the section of the margin line depicted in the image is a high quality margin line or a low quality margin line.”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Saphier to utilize the machine learning model to determine and provide a quality score/rating, as taught by Weiss, to arrive at the claimed invention discussed above. Such a modification is the result of combining prior art elements according to known methods to yield predictable results. It is predictable that the proposed modification would have reduced the amount of time taken to provide a quality rating by utilizing a MLM rather than a person manually providing the values, which increases the speed at which the process is completed.
Conclusion
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/TY MITCHELL BEATTY/Examiner, Art Unit 2663
/GREGORY A MORSE/ Supervisory Patent Examiner, Art Unit 2698