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.
Claim 6 is 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. Intervening claim 4 introduces a new instance of “a curve” that is different than the instance of “a curve” that was introduced in base claim 1. Thus, one of ordinary skill in the art cannot know which of “the curve” is being referred to in claim 6. Is it the curve from claim 1 or from claim 4? Thus, the metes and bounds of claim 6 cannot be ascertained. Note that seemingly analogous claim 15 depends directly from independent claim 10, so there is no discrepancy for claim 15.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 19 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the broadest reasonable interpretation of the limitations, “A computer-readable recording medium on which a program including at least one instruction for performing an intraoral image processing method by a computer is recorded” includes a program recorded on a transitory signal, which does not fall into any statutory category. Amending this claim to require the interpretation that the “computer-readable recording medium” is non-transitory would overcome this rejection.
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) 1-7, 9-16, 18, and 19 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by US 2023/0005196 A1 (Khaitov).
As per claim 1, Khaitov teaches an intraoral image processing method comprising:
acquiring three-dimensional intraoral data by scanning an oral cavity including teeth (Khaitov:
Fig. 2 (shown below): mainly 201;
para 4: “identifying at least one tooth reference point for each of at least two teeth on a dental model; identifying at least one offset point corresponding to each of said at least one tooth reference points such that said at least one offset point is on a gingival surface of said dental model and positioned outside an interproximal area”;
para 8: “A dental model is a representation of teeth, gingiva, palate, jaws, and/or other items in the mouth, such as brackets, crowns, and/or veneers.”;
para 213: “In step 201, the dental model is obtained. As discussed above, the dental model may be a three-dimensional scan or a digital model, although it is not limited to these embodiments. A three-dimensional scan may be made from an cast of a patient's teeth, or directly from the patient.”);
acquiring a tooth region including teeth from the three-dimensional intraoral data (Khaitov:
Fig. 2 (shown below): mainly 202;
para 4: “identifying at least one offset point corresponding to each of said at least one tooth reference points such that said at least one offset point is on a gingival surface of said dental model and positioned outside an interproximal area”;
para 46: “dental model that has undergone tooth segmentation may also have a visible apex identified, by one of the methods discussed above. This allows the identification of visible apices for individual tooth in a dental model”;
para 47: “A dental model comprising more than one tooth may undergo tooth segmentation, i.e. segmenting the model into individual teeth. This may further be accompanied by identifying the teeth through a classification algorithm”;
para 214: “Step 202 segments the teeth and gingiva. Some discussion of mesh segmentation may be found in Shamir, 2008. Tooth segmentation divides the scan into tooth and gingiva, as well as separating individual teeth.”);
acquiring a gingival region having an edge formed as a curve having a smaller curvature than a curvature of an edge of the tooth region, based on the tooth region (Khaitov:
Fig. 2 (shown below): mainly 203-208;
Abstract: “generating the edge curve by connecting the offset points such that the edge curve is outside the interproximal area and on the gingival surface”;
Para 4: “generating said edge curve by connecting the offset points such that the edge curve is outside the interproximal area and on the gingival surface”;
Para 25: “In one embodiment, a tooth reference point may be a visible apex. A visible apex is an optimum of the margin line of the tooth, e.g. the lowest point or highest point visible for the margin line and/or a portion of the margin line. An optimum can be identified by finding a point with an optimal measurement. The margin line of the tooth is boundary between tooth and gingiva.”;
Para 27: “Connecting several visible apices can offer an approximation of the shape of the gingiva below the teeth, an useful marker in finding an edge curve.”;
Para 51: “The offset direction can be chosen in a number of ways, and need not be the same for each offset point. It may be based off an anatomical feature, such as the tooth long axis and/or the occlusal plane. It may be based on some geometrical information, such as planes of the dental model as a whole or centers of particular teeth. It may also be based on a calculation of any of the above, for example, an average of tooth long axes, or a normal of the occlusal plane. One embodiment uses a mathematical model to calculate a plane based on anatomical data, as discussed below”;
Para 53: “The at least one offset point allows the creation of an edge curve that is based on a patient's anatomy, but can be modified to improve the function of a dental device.”;
para 74: “The dental arch is generated by fitting a third-order curve to the mesial-distal midpoints of the teeth of a jaw, by a method such as least squares regression. This results in a smooth curve that approximates the arch of the jaw, but may not pass directly through every mesial-distal midpoint. The offset plane is generated as discussed above”;
para 214: “Step 202 segments the teeth and gingiva. Some discussion of mesh segmentation may be found in Shamir, 2008. Tooth segmentation divides the scan into tooth and gingiva, as well as separating individual teeth.”;
para 216: “Step 204 identifies at least one control point, as discussed above. An edge curve can be generated from offset points from tooth reference points alone. However, identifying control points allows for more control over the edge curve, for example, in controlling the waviness of the edge curve.”;
para 217: “An edge curve can be made smoother or wavier, for the situation, or given a bit more coverage where necessary. See FIG. 12A-C for examples of such tailoring”;
[0218] Step 206 identifies at least one terminal tooth point, as discussed above. Using at least one terminal tooth point in addition to the offset points may allow for a more precise fit than using offset points alone. Methods for identifying terminal tooth points are discussed above, and below, particular in FIG. 9.
[0219] Step 207 fits the edge curve to the offset points and, if they exist, any terminal tooth points. The methods for fitting this curve are discussed above.
[0220] Step 208 post-processes the edge curve. Postprocessing the edge curve can offer more customization and make manufacturing easier. This includes removing loops, setting minimum widths, setting minimum curve radii, and manual adjustment of the edge curve, as discussed above.
[0227] Step 500 shows tooth 501 in the dental model, with margin line 502 and margin lines points 503.
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[0275] FIG. 12B shows an edge curve 1214 generated for the lingual side of a set of teeth 1211. Here, the second offset distance is zero, and the offset points from tooth reference points 1213 (dots) and the offset points from control points 1214 (squares) are lined up. Hence, the edge curve 1214 is straighter may be suitable for the lingual side.
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[0270] FIG. 11 shows methods of fitting the edge curve over a terminal tooth.
[0271] FIG. 11A shows an edge curve generated in part by fitting the edge curve to a terminal tooth point that is a mesial-distal midpoint projected to the surface. Here, the edge curve includes offset points for the final tooth, and the terminal tooth point takes the edge curve through the center of the occlusal surface of terminal tooth.
[0272] FIG. 11B shows a edge curve generated in part by fitting the edge curve over a terminal tooth by fitting the edge curve to three margin line point shifted upwards onto the tooth. As can be seen, the edge curve fits over most of the terminal tooth.
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); and
displaying the tooth region and the gingival region as a final selection region (Khaitov:
paras 135-143, 193, 280: display*;
Fig. 14 (shown below);
[0280] FIG. 14 shows an embodiment displaying an original curve section and a modified curve section.
[0281] In Step 1400, an edge curve 1403 on a digital dental model 1401 is shown, along with a validation area 1402. A validation area may define an area that the edge curve is prevented from going into, e.g., due to clinical or mechanical constraints. For example, a minimum width may be demarcated by a validation area. The validation area may include an interproximal area, which may for example be defined by a bounding box.
[0282] In Step 1410, an edge curve 1413 on a digital dental model 1411 is shown, along with a validation area 1412. The edge curve 1413 comprises original curve section 1414 and modified curve section 1415. Curve sections 1414 and 1415 are shown at different transparencies to distinguish between them, and modified curve section 1415 remains outside the validation area 1412.
[0283] In Step 1420, modified edge curve 1423 on a digital dental model 1411 is shown, along with a validation area 1412. Note that the modified curve section 1415 is now part of the edge curve, and original curve section 1414 is not. As such the edge curve is still valid based on validation area 1422. Note also that cursor 1426 may be used to find a user-input point.
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).
As per claim 2, Khaitov teaches the intraoral image processing method of claim 1, wherein the acquiring of the tooth region comprises acquiring the tooth region by identifying scan data about teeth and scan data about gingiva included in the three-dimensional intraoral data (Khaitov: See arguments and citations offered in rejecting claim 1 above; Fig. 2: mainly 202 and para 214 (both shown above)).
As per claim 3, Khaitov teaches the intraoral image processing method of claim 1, wherein the acquiring of the tooth region comprises, when the teeth are separated into individual tooth regions in the three-dimensional intraoral data, acquiring the tooth region by combining the individual tooth regions into one region (Khaitov: See arguments and citations offered in rejecting claim 1 above;
Fig. 2 (shown below): mainly 202;
para 4: “identifying at least one offset point corresponding to each of said at least one tooth reference points such that said at least one offset point is on a gingival surface of said dental model and positioned outside an interproximal area”;
para 46: “dental model that has undergone tooth segmentation may also have a visible apex identified, by one of the methods discussed above. This allows the identification of visible apices for individual tooth in a dental model”;
para 47: “A dental model comprising more than one tooth may undergo tooth segmentation, i.e. segmenting the model into individual teeth. This may further be accompanied by identifying the teeth through a classification algorithm”;
para 214: “Step 202 segments the teeth and gingiva. Some discussion of mesh segmentation may be found in Shamir, 2008. Tooth segmentation divides the scan into tooth and gingiva, as well as separating individual teeth.”
Fig. 2 (shown above): mainly 207-209;
Para 64: “the offset distance is measured by the length of each path along the facets of the mesh of the three-dimensional scan or model.”;
Para 79: “the dental model is a digital three-dimensional data object expressed as a three-dimensional mesh or a point cloud. Each vertex of the three-dimensional mesh and point of the point cloud has Euclidean coordinates. These Euclidean coordinates can be used to calculate a distance from the dental model point”;
Para 84: “where the surface normal of the surface-projected dental model point is compared to a range of expected values. The surface normal may be the normal for a nearby facet of the mesh of the dental model, or an average of normal for nearby facets”;
Figs. 4A-4B;
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: a mesh is generated for the model and the final selection of the curve and region, after tooth and gum segmentation, is relative to this mesh model).
As per claim 4, Khaitov teaches the intraoral image processing method of claim 1, wherein the acquiring of the gingival region comprises: acquiring a curve that is a certain distance away from the edge of the tooth region; and determining the edge of the gingival region using some of points on the curve (Khaitov: See arguments and citations offered in rejecting claim 1 above;
Para 48: “displacing a corresponding dental model point based on a offset distance and a offset direction, wherein a corresponding dental model point is an instance of the tooth reference points or the at least one control point”;
Para 51: “The offset direction can be chosen in a number of ways, and need not be the same for each offset point. It may be based off an anatomical feature, such as the tooth long axis and/or the occlusal plane. It may be based on some geometrical information, such as planes of the dental model as a whole or centers of particular teeth. It may also be based on a calculation of any of the above, for example, an average of tooth long axes, or a normal of the occlusal plane. One embodiment uses a mathematical model to calculate a plane based on anatomical data, as discussed below”;
Para 217: “Step 205 identifies offset points, based on the tooth reference points and any control points, if there are control points. Identifying offset points means displacing the tooth reference points and/or control points by an offset distance in an offset direction. This may be done by one of the methods discussed above. By controlling the offset distance for different groups of offset points, the edge curve may be tailored to the specific situation, as discussed below and above. An edge curve can be made smoother or wavier, for the situation, or given a bit more coverage where necessary. See FIG. 12A-C for examples of such tailoring.”
[0218] Step 206 identifies at least one terminal tooth point, as discussed above. Using at least one terminal tooth point in addition to the offset points may allow for a more precise fit than using offset points alone. Methods for identifying terminal tooth points are discussed above, and below, particular in FIG. 9.
[0219] Step 207 fits the edge curve to the offset points and, if they exist, any terminal tooth points. The methods for fitting this curve are discussed above.
[0220] Step 208 post-processes the edge curve. Postprocessing the edge curve can offer more customization and make manufacturing easier. This includes removing loops, setting minimum widths, setting minimum curve radii, and manual adjustment of the edge curve, as discussed above.).
As per claim 5, Khaitov teaches the intraoral image processing method of claim 4, wherein the intraoral image processing method further comprises: displaying an object for setting the certain distance; and receiving a user input for the object, and setting the certain distance (Khaitov: See arguments and citations offered in rejecting claim 4 above;
para 52: para 52: “The offset distance can be identified by a method from the list comprising: user input”;
para 122: “The user input may include one or more of a manually drawn line, different from the original curve section, in between the first point and the second point with a drawing tool, or moving a point on the curve and adjusting the curve around the moved curve, or marking at least one point proximal to the original curve section”;
para 129: “the user input for a modified curve section may be based on moving a point on the curve, and the modified curve section may be based on the movement of that point”;
para 130: “First, a primary curve point is found. This is a point on a curve and may be, for example, a control point, a tooth reference point, a point based on the prior points, or any other point on the curve. Next, the primary curve point is moved. This may be done, for example, with user input, and/or by a pre-determined distance and direction. User-input may come from, for example, a user moving the primary curve point itself, or by finding a user-input point, as described below”;
para 133: “user input may be based on a user-input point, such as a point that a user selects near the curve. In an embodiment, a user selects a user-input point, such as a nearby pixel on a screen, and the primary curve point is the point nearest the user input point, e.g. with the shortest Euclidean distance between the points. This allows the user to move the curve without precisely selecting a point on the curve, and may be particularly useful where the input device is a computer mouse, and a user can click a point near the curve without worrying over much about the accuracy of their click.”;
para 135: “In an embodiment, the modified curve section is displayed, e.g. on a screen or another device. Such display on the screen may be provided as a preview of the possible change in the edge curve. This allows a user to see what a change to an curve would be like before actually changing it. This further permits the user to make changes that still comply with the validation procedures as described above.”).
As per claim 6, Khaitov teaches the intraoral image processing method of claim 4, wherein the acquiring of the gingival region comprises determining the edge of the gingival region such that the edge of the gingival region has a smaller curvature than the curvature of the curve (Khaitov: See arguments and citations offered in rejecting claim 4 above).
As per claim 7, Khaitov teaches the intraoral image processing method of claim 4, wherein the intraoral image processing method further comprises:
receiving a user input for selecting a palate region including scan data about a palate in the three-dimensional intraoral data (Khaitov: See arguments and citations offered in rejecting claim 4 above; para 8: “A dental model is a representation of teeth, gingiva, palate, jaws, and/or other items in the mouth, such as brackets, crowns, and/or veneers.”;
[0017] The offset points may be used to define an edge curve for the entire edge of a dental device, or a portion of the edge of a dental device, for example, the lingual side only.
Para 113: “obtaining a user-input point; and selecting as the primary curve point a curve point of the original curve section closest to the user-input point.”;
[0252] Step 810 shows obtaining a set of dental model data 812 based on dental model 811. The dental model data set 812 is comprised of the mesial and distal points for each tooth in dental model 811. The mesial and distal points may be identified by a user or automatically identified.
[0275] FIG. 12B shows an edge curve 1214 generated for the lingual side of a set of teeth 1211. Here, the second offset distance is zero, and the offset points from tooth reference points 1213 (dots) and the offset points from control points 1214 (squares) are lined up. Hence, the edge curve 1214 is straighter may be suitable for the lingual side.
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: By selecting the lingual side for the points and curve, as opposed to the buccal side, the user selects the palate.); and
determining a first reference point and a second reference point for distinguishing between a lingual side of teeth and a buccal side of teeth among points on the curve (Khaitov: See arguments and citations offered in rejecting claim 4 above; para 30: “the margin line points may be separated into groups, for example, lingual margin line points and buccal margin line points.”;
para 91: “on the lingual side of a clear aligner, the edge curve may be smoother, as the surface is smoother there and it improves the comfort of the wearer by facilitating a smoother edge next to the tongue. On the buccal side however, the surface is bumpier and adding waves provides a better grip on the surface”;
para 94: “The base of the bounding box is the quadrilateral defined by the first tooth's buccal visible apex, the first tooth's lingual visible apex, the second tooth's buccal visible apex, and the second tooth's lingual visible apex.”;
para 112: “Where at least one edge curve defines the both lingual and buccal sides of a dental device, the offset points may be divided into lingual and buccal offset points.”;
para 113: “Euclidean distances may be calculated, for example, between each lingual point and each buccal point.”;
[0259] Step 900 shows tooth 901, gingiva 902, buccal gingival surface 903, and tooth reference point 904. Tooth reference point 904 is a visible apex on the buccal side of tooth 901.
Paras 260-262;
[0263] Step 930 selects an area of interest 937. This may be done, for example, by user input or by automatic selection, and ensures that the translated tooth reference point 936 comes out on the buccal gingival surface 933. The tooth 931, gingiva 932, tooth reference point 934, and offset vector 935 are also shown.
[0277] FIG. 13 shows a bounding box.
[0278] In an embodiment, bounding boxes are used to identify if a point is in an interproximal area. Here, the bounding box 1308 is shown. The dental model 1301 has teeth 1302 and 1303. Tooth 1302 has a lingual visible apex 1304 and a buccal visible apex 1305. Tooth 1303 has a lingual visible apex 1306 and a buccal visible apex 1307. Visible apices 1304, 1305, 1306, and 1307 are translated opposite an offset direction by a pre-determined distance, for example, 1 cm. A bounding box 1308 is the space bounded by the visible apices 1304, 1305, 1306, and 1307, and their translations.
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);
wherein the acquiring of the gingival region comprises determining the edge of the gingival region based on points corresponding to the buccal side of teeth among points on the curve (Khaitov: See arguments and citations offered in rejecting claim 4 above; para 40: “an offset plate is limited to either the lingual or the buccal side, with a boundary along, e.g. the mesial distal axis, and the visible apex for each side is found with different offset planes.”;
para 78: “the area of interest may be the lingual side or the buccal side of the dental model data”).
As per claim 9, Khaitov teaches the intraoral image processing method of claim 1, wherein the intraoral image processing method further comprises acquiring tooth model data corresponding to the final selection region by generating mesh data extending from the edge of the final selection region (Khaitov: See arguments and citations offered in rejecting claim 1 above;
Fig. 2 (shown above): mainly 207-209;
Para 64: “the offset distance is measured by the length of each path along the facets of the mesh of the three-dimensional scan or model.”;
Para 79: “the dental model is a digital three-dimensional data object expressed as a three-dimensional mesh or a point cloud. Each vertex of the three-dimensional mesh and point of the point cloud has Euclidean coordinates. These Euclidean coordinates can be used to calculate a distance from the dental model point”;
Para 84: “where the surface normal of the surface-projected dental model point is compared to a range of expected values. The surface normal may be the normal for a nearby facet of the mesh of the dental model, or an average of normal for nearby facets”;
Figs. 4A-4B;
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: a mesh is generated for the model and the final selection of the curve and region is relative to this mesh model).
As per claim(s) 10-18, arguments made in rejecting claim(s) 1-9 are analogous, respectively. Khaitov also teaches an intraoral image processing device comprising: a display; memory storing one or more instructions; and a processor, wherein the processor is configured, by executing the one or more instructions stored in the memory (Khaitov: See arguments and citations offered in rejecting claim 1 above; Fig. 1 and associated text: paras 204-211).
As per claim(s) 19, arguments made in rejecting claim(s) 1 are analogous. Khaitov also teaches a computer-readable recording medium on which a program including at least one instruction for performing an intraoral image processing method by a computer is recorded, the intraoral image processing method (Khaitov: See arguments and citations offered in rejecting claim 1 above; Fig. 1 and associated text: paras 204-211).
Allowable Subject Matter
Claims 8 and 17 and objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter:
Limitations pertaining to “acquiring, based on a curve connecting the first reference point to the second reference point on the lingual side of teeth, a second palate region excluding a partial region of the palate region”, in conjunction with other limitations present in the listed claims, independent claim(s), and intervening claims, distinguish over the prior art.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Atiba Fitzpatrick whose telephone number is (571) 270-5255. The examiner can normally be reached on M-F 10:00am-6pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Andrew Bee can be reached on (571) 270-5183. The fax phone number for Atiba Fitzpatrick is (571) 270-6255.
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Atiba Fitzpatrick
/ATIBA O FITZPATRICK/
Primary Examiner, Art Unit 2677