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 § 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.
Claims 1-22 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) mathematical calculations and/or generalized data gathering. See 2019 Revised Patent Subject Matter Eligibility Guidance.
Step 2A Prong 1. The claim limitations starting with “extracting” and “cutting” and “generate” are generalized mathematical/data gathering steps of manipulating a numerical set. The claim limitations of “determining” and “searching” are performing mathematical calculations on sets of data points i.e. numbers.
Step 2A Prong 2. This judicial exception is not integrated into a practical application because evaluating additional elements recited in the claim individually and in combination, the claim as a whole does not integrate the exception into a practical application. The claims recite the following additional elements that merely define the intended environment (dental data), general computing (processors) or are just extra-solution activity. The elements do not impact structure or steps performed by the device. Claims that are omitted in the list below just repeat or do not recite anything additional.
Claims 1 and 20: recite “computerized tomography” “patient’s eyes and nose” “teeth portion” “right teeth” “left teeth”
Claim 2: “maxilla” mandible”
Claims 21 and 22: computer readable storage medium, hardware processor
Step 2B. Evaluating additional elements recited, the claim as a whole does not recite additional elements that amount to significantly more than the judicial exception. The analysis above in parts and re-evaluated again for the claims as a whole, the additional elements are mere description of mathematical calculations and data gathering steps on dental data, which is well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II. The limitations remain insignificant extra-solution activity even upon reconsideration. Even when considered in combination, the additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, which cannot provide an inventive concept.
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.
Claims 1-22 are rejected under 35 U.S.C. 112(b), as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Claims 1 and 20 recite “left teeth landmark point” and “right teeth landmark point” without specifying if they refer to “landmark points of the CT data” or “landmark points of the CT data” and thus render the claim ambiguous and yielding mixed interpretations.
Additionally, Claims 1 and 20 recite “a second landmark point” and “third distance” but without first reciting a “first landmark point” or “first distance” and “second distance” thus creating indefiniteness.
Thus the claims are unclear and dependent claims 2-20 and 21-22 are rejected for the same reasons.
Claim Rejections - 35 USC § 103
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.
Claims 1-3, 9-12, 16-17 and 19-22 are rejected under 35 U.S.C. 103 as being unpatentable over US 20220122264 A1 REYNARD; Delphine et al. in view of Chang YB, Xia JJ, Gateno J, Xiong Z, Zhou X, Wong ST. An automatic and robust algorithm of reestablishment of digital dental occlusion. IEEE Trans Med Imaging. 2010 Sep;29(9):1652-63.
Consider Claim 1 and 22
Reynard teaches An automated method for aligning 3D (three-dimensional) dental data (Fig. 5, [0008]-[0013], steps a-e, Fig. 6), the method comprises:
extracting landmark points of a CT (computerized tomography) data ([0048] and Fig. 5: where the first model can be either a CBCT or an intraoral scanner. See also [0055] that introduces the registration refinement for each tooth of the first model with each corresponding tooth of the second model. The feature matching algorithm [0055-0066] contains a step of feature descriptors extraction (see [0059-0064] step (i)) which corresponds to the recited landmark points.);
extracting landmark points of scan data of a digital impression model ([0048,0053] and Fig. 5 where the second model can be either a CBCT or an intraoral scanner. See also [0055] that introduces the registration refinement for each tooth of the first model with each corresponding tooth of the second model. The feature matching algorithm [0055-0066] contains a step of feature descriptors extraction (see [0059-0064] step (i)) which corresponds to the recited landmark points.);
determining an up vector representing a direction of a patient's eyes and nose and identifying left and right of the landmark points of the scan data ([0049, [0053] where the individual teeth segmentation and labeling with axis information implicitly means that the left, right and up orientation of the tooth is determined.);
extracting a teeth portion of the scan data ([0053] where, after the coarse registration, the labeling of tooth in the second 3D model based on the segmentation of teeth in the first model,
corresponds to the teeth portion extraction in the scan data.);
searching a source point of the scan data of the CT data to generate a candidate target point group ([0059-0064] step ii) where the RAN SAC method to select several set of three correspondences of feature descriptors corresponds to the candidate target
point group generation.);
and determining the candidate target point group having a smallest error with the landmark points of the CT data as a final candidate ([0059-0064] step ii), where "The candidate relative transform with the highest number of consistent correspondences becomes the final relative placement", which corresponds to the candidate target point group determination).
wherein a vector from a second landmark point of the scan data to a right teeth landmark point is defined as {right arrow over (v.sub.R)}, and a vector from the second landmark point to a left teeth landmark point is defined as {right arrow over (v.sub.L)}, cutting the scan data into a plane having a normal vector of {right arrow over (v.sub.R)} at a point moved from the right teeth landmark point by a third distance in the direction of {right arrow over (v.sub.R)}; and, cutting the scan data into a plane having a normal vector of {right arrow over (v.sub.L)} at a point moved from the left teeth landmark point by the third distance in the direction of {right arrow over (v.sub.L)}. (Claims specify a cropping of the scan data in the cranio-caudal direction (up vector). Reynard teaches cropping models [0068] To complete the segmentation processing of FIG. 6, a labeling and axis definition step S862 assigns a number or other label to the tooth from the second model and applies a registration matrix to the axis and other features (such as cusps) of the tooth of the first model, to identify the axis and other features of the tooth of the second model. This step obtains and stores the data used for segmentation of each tooth in the second model, including position, axis, and cervical limit A complete segmentation step S866 performs final segmentation processing for the second model, generating a segmented model. A display step S870 then provides display rendering, storage, or transmission of the second model segmentation. [0069] FIG. 7 shows an example of tooth segmentation from a first 3D model image of the lower jaw.)
Reynard does not explicitly disclose search of a source point of the scan data on a spline curve of the CT data;
Chang teaches searching a source point of the scan data on a spline curve of the CT data to generate a candidate target point group (Chang Fig. 3, Section III, Paragraph 1: “….The curve of maxillary teeth [Fig. 3(a)] is extracted from maxillary fossae including the pits on incisal palatal surfaces and the central grooves of premolars and molars. The curve of mandibular teeth [Fig. 3(b)] is extracted from the incisal edges, and the buccal cusps of the premolars and molars. Ideally, the two curves should be superimposed in the MI. .. In the first step, we identify feature points on the cusps, incisal edges, central grooves, pits, and fossae to approximately represent the dental curves along the arches instead of finding the continuous dental curves…”)
e wherein a vector from a second landmark point of the scan data to a right teeth landmark point is defined as {right arrow over (v.sub.R)}, and a vector from the second landmark point to a left teeth landmark point is defined as {right arrow over (v.sub.L)}, cutting the scan data into a plane having a normal vector of {right arrow over (v.sub.R)} at a point moved from the right teeth landmark point by a third distance in the direction of {right arrow over (v.sub.R)}; and, cutting the scan data into a plane having a normal vector of {right arrow over (v.sub.L)} at a point moved from the left teeth landmark point by the third distance in the direction of {right arrow over (v.sub.L)}. Chang further teaches trimming models Pg. 11, Right Col. Paragraph 2 “Hiew et al. [25] used the right and posterior surfaces of the model bases to perform the dental model alignment. They first trimmed the right and posterior surfaces of the upper and lower plaster model bases so they would be perfectly in the same plane with the teeth in the correct occlusion. “)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Reynard and combine it with the noted teachings of Chang in order to obtain approximate dental occlusion (Chang Section III, Paragraph 1)
Further regarding claim 22, the combination teaches A non-transitory computer-readable storage medium having stored thereon at least one program comprising commands, which when executed by at least one hardware processor, performs the method of claim 1 (Reynard [0035] A control logic processor 80, configurable to execute programmed instructions, is in signal communication with imaging device 16 and a display 84.)
Consider Claim 2
The combination teaches The method of claim 1, wherein the landmark points of the CT data includes three or more landmark points in a maxilla and three or more landmark points in a mandible , and wherein the landmark points of the scan data includes three landmark points (Reynard [0059-0064] step ii) where at least two set of 3 corresponding points are matched; Renard Figs. 7-8 showing mandible, Fig. 4 showing maxilla and mandible; See also Chang Figs. 3-4 maxilla and mandible curves, 5 feature points shown in Fig. 4, Section III Paragraphs 1-3).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination and combine it with the noted teachings of Chang in order to obtain approximate dental occlusion (Chang Section III, Paragraph 1)
Consider Claim 3
The combination teaches The method of claim 2,
wherein a first landmark point and a third landmark point of the scan data indicate outermost points of teeth of the scan data in a lateral direction (Examiner notes that points arbitrarily chosen as design choice; Chang Section III Fig. 4 (a) A and B are the points on distobuccal cusps, and C is on the cutting edge of the incisors. D and E are the points on the interstices between the canines and the first premolars; Reynard Fig. 10 1103 1104 points C1, C2 are outer points of teeth in a lateral direction;).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination and combine it with the noted teachings of Chang in order to obtain approximate dental occlusion (Chang Section III, Paragraph 1)
Consider Claim 9.
The combination teaches The method of claim 1, further comprising determining whether the CT data and the scan data have a same area,
wherein when , th is a first threshold value for determining that the CT data and the scan data have the same area, p1, p3 and p5 are the landmark points of the CT data, Pi 1, P2 and p1i are the landmark points of the
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scan data and is satisfied, the CT data and the scan data are determined to have the same area (See Reynard where same area [i.e. convergence reached] based on distance threshold of from base and target point clouds [0061-0063] “.. A correspondence is consistent with the candidate relative transform if the moving query point, moved using the candidate relative transform, is within a predefined distance from the target query point. The candidate relative transform with the highest number of consistent correspondences becomes the final relative placement. The score indicates the quality of the final relative placement and can be the corresponding number of consistent correspondences. [0062] (iii) Accept or reject the relative placement based on the score. The relative placement may be rejected in case the score is below a predetermined threshold..”);.
Consider Claim 10
The combination teaches The method of claim 1,
wherein the extracting the teeth portion of the scan data comprises:
extracting a highest point among a first landmark point, a second landmark point and a third landmark point of the scan data in a direction of the up vector when the scan data represent maxilla data, cutting the scan data into a plane having a normal vector of the up vector at a point moved from the highest point by a first distance in a positive direction of the up vector;
and cutting the scan data into a plane having a normal vector of the up vector at a point moved from the highest point by a second distance in a negative direction of the up vector.
(Claims specify a cropping of the scan data in the cranio-caudal direction (up vector). Reynard teaches cropping models [0068] To complete the segmentation processing of FIG. 6, a labeling and axis definition step S862 assigns a number or other label to the tooth from the second model and applies a registration matrix to the axis and other features (such as cusps) of the tooth of the first model, to identify the axis and other features of the tooth of the second model. This step obtains and stores the data used for segmentation of each tooth in the second model, including position, axis, and cervical limit A complete segmentation step S866 performs final segmentation processing for the second model, generating a segmented model. A display step S870 then provides display rendering, storage, or transmission of the second model segmentation. [0069] FIG. 7 shows an example of tooth segmentation from a first 3D model image of the lower jaw.;
Chang further teaches trimming models Pg. 11, Right Col. Paragraph 2 “Hiew et al. [25] used the right and posterior surfaces of the model bases to perform the dental model alignment.They first trimmed the right and posterior surfaces of the upper and lower plaster model bases so they would be perfectly in the same plane with the teeth in the correct occlusion. “)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination and combine it with the noted teachings of Chang in order to reduce data size for registration (Chang Section III, Paragraph 1)
Consider Claim 11.
The combination teaches The method of claim 10,
wherein the extracting the teeth portion of the scan data further comprises:
extracting a lowest point among the first landmark point, the second landmark point and the third landmark point of the scan data in the direction of the up vector when the scan data represent mandible data, cutting the scan data into a plane having a normal vector of the up vector at a point moved from the lowest point by the first distance in a positive direction of the up vector;
and cutting the scan data into a plane having a normal vector of the up vector at a point moved from the lowest point by the second distance in a negative direction of the up vector.
(Claims specify a cropping of the scan data in the cranio-caudal direction (up vector). Reynard teaches cropping models [0068] To complete the segmentation processing of FIG. 6, a labeling and axis definition step S862 assigns a number or other label to the tooth from the second model and applies a registration matrix to the axis and other features (such as cusps) of the tooth of the first model, to identify the axis and other features of the tooth of the second model. This step obtains and stores the data used for segmentation of each tooth in the second model, including position, axis, and cervical limit A complete segmentation step S866 performs final segmentation processing for the second model, generating a segmented model. A display step S870 then provides display rendering, storage, or transmission of the second model segmentation. [0069] FIG. 7 shows an example of tooth segmentation from a first 3D model image of the lower jaw.; Chang further teaches trimming models Pg. 11, Right Col. Paragraph 2 “Hiew et al. [25] used the right and posterior surfaces of the model bases to perform the dental model alignment. They first trimmed the right and posterior surfaces of the upper and lower plaster model bases so they would be perfectly in the same plane with the teeth in the correct occlusion. “)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination and combine it with the noted teachings of Chang in order to reduce data size for registration (Chang Section III, Paragraph 1)
Consider Claim 12
The combination teaches The method of claim 10, wherein an absolute value of the third distance is less than an absolute value of the first distance and an absolute value of the second distance. (Claims teach arbitrary numerical values and “distance” metrics without specifying the metrics, and thus design choice requiring ordinary skill in the art).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination and combine it with the noted teachings of Chang in order to reduce data size for registration (Chang Section III, Paragraph 1)
Consider Claim 16.
The combination teaches The method of claim 1,
wherein the searching the source point of the scan data on the spline curve of the CT data comprises calculating the spline curve C(u) based on a plurality of landmark points of a maxilla of the CT data or a plurality of landmark points of a mandible of the CT data.
(Chang Fig. 3, Section III, Paragraph 1: “..we use the first pair (Fig. 3) to perform initial alignment of the models. The curve of maxillary teeth [Fig. 3(a)] is extracted from maxillary fossae including the pits on incisal palatal surfaces and the central grooves of premolars and molars. The curve of mandibular teeth [Fig. 3(b)] is extracted from the incisal edges, and the buccal cusps of the premolars and molars. Ideally, the two curves should be superimposed in the MI. Those dental curves can be viewed as 3-D continuous curves (not necessarily fitting polynomial curves) along the dental arches. Based on those assumptions above, we have developed an automatic approach for initially positioning the models. In the first step, we identify feature points on the cusps, incisal edges, central grooves, pits, and fossae to approximately represent the dental curves along the arches instead of finding the continuous dental curves. In the second step, the dental curves of the maxillary and mandibular arches are superimposed using a point matching algorithm to complete the initial alignment…”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination and combine it with the noted teachings of Chang in order to obtain approximate dental occlusion (Chang Section III, Paragraph 1)
Consider Claim 17.
The combination teaches The method of claim 17, wherein the source point includes three points of a left teeth landmark point, a second landmark point and a right teeth landmark point (Chang Section III Fig. 4 (a) A and B are the points on distobuccal cusps, and C is on the cutting edge of the incisors. D and E are the points on the interstices between the canines and the first premolars).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination and combine it with the noted teachings of Chang in order to obtain approximate dental occlusion (Chang Section III, Paragraph 1).
Consider Claim 19.
The combination teaches The method of claim 17,
wherein the determining the candidate target point group having the smallest error with the landmark points of the CT data as the final candidate comprises:
transforming the candidate target point group to a domain of the CT data using a transform matrix;
and calculating a transform error as an average of distances between the transformed candidate target point group and the landmark points of the CT data (See Reynard [0061] (ii) Perform feature matching using both sets of feature descriptors to generate a relative placement and a score. AND [0063] (iv) Refine the relative placement using an iterative closest point algorithm and generate a distance measure; both instances of matching and refinement teach steps of transforming and calculating error as average of distance).
Consider Claim 20 and 22
The rejection of Claim 1 teaches claims 1 and 23 teaches all the limitations and in addition the combination further teaches determining whether the CT data and the scan data have a same area (See Reynard where same area [i.e. convergence reached] [0061-0063]); searching a source point of the scan data on a spline curve of the CT data to generate a candidate target point group when the CT data and the scan data have different areas (See Reynard where searching [feature matching] when the CT data scan data have different areas [i.e. placement is not met, correspondence score is below threshold] [0061-0062] “.. A correspondence is defined as the smallest distance from one feature descriptor onto the other set of feature descriptors. Feature matching then involves the selection of a group of correspondences to generate a relative placement. This step is typically performed using the Random Sample Consensus (RANSAC) algorithm, which consists of the random selection of three correspondences to compute a candidate relative transform and then counting the number of correspondences consistent with this candidate relative transform. A correspondence is formed of two feature descriptors, one from the moving and one from the target point cloud with normals. Each feature descriptor corresponds to a query point. A correspondence is consistent with the candidate relative transform if the moving query point, moved using the candidate relative transform, is within a predefined distance from the target query point. The candidate relative transform with the highest number of consistent correspondences becomes the final relative placement. The score indicates the quality of the final relative placement and can be the corresponding number of consistent correspondences. [0062] (iii) Accept or reject the relative placement based on the score. The relative placement may be rejected in case the score is below a predetermined threshold…”);
Further regarding claim 23, the combination teaches A non-transitory computer-readable storage medium having stored thereon at least one program comprising commands, which when executed by at least one hardware processor, performs the method of claim 21 (Reynard [0035] A control logic processor 80, configurable to execute programmed instructions, is in signal communication with imaging device 16 and a display 84. )
Claims 4-8 are rejected under 35 U.S.C. 103 as being unpatentable over Reynard et al. and Chang et. al. as cited above, further in view of KR 101292811 B1 정제교 et al.
Consider Claim 4
The combination teaches The method of claim 1, wherein when a first landmark point of the scan data is p1, a second landmark point of the scan data is pi 2, a third landmark point of the scan data is pi (Examiner notes that points arbitrarily chosen as design choice; Chang Section III Fig. 4 (a) points A-E; Reynard Fig. 10 1103 1104 points C1, C2;).
The combination does not explicitly disclose an average vector obtained by averaging all normal vectors from all points forming meshes of the scan data is 1T, the left and the right of the landmark points of the scan data are identified using a cross product of pi 1 - pi 2 and pi 3 - pi 2 and the average vector.
정제교 teaches an average vector obtained by averaging all normal vectors from all points forming meshes of the scan data is 1T, the left and the right of the landmark points of the scan data are identified using a cross product of pi 1 - pi 2 and pi 3 - pi 2 and the average vector (the determination of the scan data orientation (up vector, left, right) based on trivial vector cross product formula in a routine design modifications of well known prior art teachings, See 정제교 Pg. 3 Paragraph 3: the upper surface (lower surface) of each plane perpendicular vector data obtained in the plane of the mesh (11, 12) are oblique to each other based on the inner product between the vector to determine that there is on the same plane when the value of the upper surface variations, internal or external sharply in the side portion of the non-repair vector boundary value vector dot product values change rapidly evolved, so to calculate the vector dot junction plane (or there is an effect that can take advantage of the vector inner product value in the detection to automatically detect a highlight value (threshold) of the outline of the top surface (bottom surface)) corresponding shape formed in the markers (10) ( 11) is used to synchronize the three-dimensional coordinate system of the image capture device, etc. )
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination and combine it with the noted teachings of 정제교in order to synchronize the three-dimensional coordinate system of the image capture device (See 정제교 Pg. 3 Paragraph 3).
Consider Claim 5
The combination teaches The method of claim 4,
wherein when the scan data represent maxilla data and a discriminant d<0, a left teeth landmark point pL representing a left outermost point of teeth of the patient is pi i and a right teeth landmark point pR representing a right outermost point of the teeth of the patient is pi3, wherein when the scan data represent the maxilla data and the discriminant d>=0, the left teeth landmark point pL is pi;
and the right teeth landmark point PR is pu, and
wherein the discriminant d is defined as
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(the determination of the scan data orientation (up vector, left, right) based on trivial vector cross product formula in a routine design modifications of well known prior art teachings, See
정제교 Pg. 3 Paragraph 3)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination and combine it with the noted teachings of 정제교in order to synchronize the three-dimensional coordinate system of the image capture device (See 정제교 Pg. 3 Paragraph 3).
Consider Claim 6
The combination teaches The method of claim 5,
wherein when the scan data represent a mandible data and the discriminant d<0, the left teeth landmark point pL is p13 and the right teeth landmark point pR is pi1, and
wherein when the scan data represent the mandible data and the discriminant d>=0, the left teeth landmark point PL is pi and the right teeth landmark point PR is Pi3 .
((the determination of the scan data orientation (up vector, left, right) based on trivial vector cross product formula in a routine design modifications of well known prior art teachings, See
정제교 Pg. 3 Paragraph 3)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination and combine it with the noted teachings of 정제교in order to synchronize the three-dimensional coordinate system of the image capture device (See 정제교 Pg. 3 Paragraph 3).
Consider Claims 7-8
Examiner notes that claims 7-8 are rejected in a similar manner as claims 4-6 as the determination of the scan data orientation (up vector, left, right) based on trivial vector cross product formula in a routine design modifications of well known prior art teachings, See
정제교 Pg. 3 Paragraph 3) in combination teaches The method of claim 1,
wherein when the up vector is i, a left teeth landmark point representing a left outermost point of a teeth of the patient is PL, a right teeth landmark point representing a right outermost point of the teeth of the patient is PR, a second landmark point of the scan data is pi2, and the scan data represent the maxilla data,
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as recited by Claim 7 and further teaches The method of claim 1,
wherein when the up vector is i, a left teeth landmark point representing a left outermost point of a teeth of the patient is PL, a right teeth landmark point representing a right outermost point of the teeth of the patient is PR, a second landmark point of the scan data is P12, and the scan data represent the mandible data,
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As recited by claim 8.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination and combine it with the noted teachings of 정제교in order to synchronize the three-dimensional coordinate system of the image capture device (See 정제교 Pg. 3 Paragraph 3).
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-22 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-22 of U.S. Patent No. 12023221. Although the claims at issue are not identical, they are not patentably distinct from each other because issued patent contains all of the same limitations as the instant claim.
Instant Application
U.S. Patent No. US 12023221
An automated method for aligning 3D (three-dimensional) dental data, the method comprises: extracting landmark points of a CT (computerized tomography) data; extracting landmark points of scan data of a digital impression model; determining an up vector representing a direction of a patient's eyes and nose and identifying left and right of the landmark points of the scan data; extracting a teeth portion of the scan data; searching a source point of the scan data on a spline curve of the CT data to generate a candidate target point group; and determining the candidate target point group having a smallest error with the landmark points of the CT data as a final candidate,
wherein a vector from a second landmark point of the scan data to a right teeth landmark point is defined as {right arrow over (v.sub.R)}, and a vector from the second landmark point to a left teeth landmark point is defined as {right arrow over (v.sub.L)}, cutting the scan data into a plane having a normal vector of {right arrow over (v.sub.R)} at a point moved from the right teeth landmark point by a third distance in the direction of {right arrow over (v.sub.R)}; and, cutting the scan data into a plane having a normal vector of {right arrow over (v.sub.L)} at a point moved from the left teeth landmark point by the third distance in the direction of {right arrow over (v.sub.L)}.
An automated method for aligning 3D (three-dimensional) dental data, the method comprises: extracting landmark points of a CT (computerized tomography) data; extracting landmark points of scan data of a digital impression model; determining an up vector representing a direction of a patient's eyes and nose and identifying left and right of the landmark points of the scan data; extracting a teeth portion of the scan data; searching a source point of the scan data on a spline curve of the CT data to generate a candidate target point group; and determining the candidate target point group having a smallest error with the landmark points of the CT data as a final candidate;
wherein extracting a teeth portion of the scan data further comprises: extracting a highest and lowest point among a first landmark point, a second landmark point and a third landmark point of the scan data in a direction of the up vector when the scan data represent maxilla data, wherein a vector from the second landmark point of the scan data to a right teeth landmark point is defined as {right arrow over (v.sub.R)}, and a vector from the second landmark point to a left teeth landmark point is defined as {right arrow over (v.sub.L)}, cutting the scan data into a plane having a normal vector of {right arrow over (v.sub.R )} at a point moved from the right teeth landmark point by a third distance in the direction of {right arrow over (v.sub.R)} and, cutting the scan data into a plane having a normal vector of {right arrow over (v.sub.L)} at a point moved from the left teeth landmark point by the third distance in the direction of {right arrow over (v.sub.L)}.
Similar for the remaining claims. Compare instant claims with issued claims.
Allowable Subject Matter
Claim 13-15 and 18 objected to as being dependent upon a rejected base claim. Those claims would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 101, 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, double patenting and any other rejections, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Considering Claims 13-14
Claim 13 recites, inter alia, cutting the scan data into a plane having a normal vector of the first vector at a point moved from the right teeth landmark point by the third distance in the direction of {right arrow over (v.sub.R)} and by a fourth distance in the direction of the first vector; cutting the scan data into a plane having a normal vector of the second vector at a point moved from the right teeth landmark point by the third distance in the direction of {right arrow over (v.sub.R)} and by the fourth distance in the direction of the second vector; cutting the scan data into a plane having a normal vector of the third vector at a point moved from the left teeth landmark point by the third distance in the direction of {right arrow over (v.sub.L)} and by the fourth distance in the direction of the third vector; and cutting the scan data into a plane having a normal vector of the fourth vector at a point moved from the left teeth landmark point by the third distance in the direction of {right arrow over (v.sub.L)} and by the fourth distance in the direction of the fourth vector.
These features in combination with the features of parent claims 1, 10 and 11 are not found to be taught in the prior art in combination with the other limitations.
Claim 14 further depends on claim 13 and contain allowable subject matter for the same reasons.
Consider Claim 15
Claim 15 recites, inter alia, cutting the scan data into a plane having a normal vector of a vector of {right arrow over (v.sub.M )} which is a sum of {right arrow over (v.sub.L)} and {right arrow over (v.sub.R)} at a point moved from the second landmark point by a fifth distance in the direction of {right arrow over (v.sub.M)}; and cutting the scan data into a plane having a normal vector of a vector of −{right arrow over (v.sub.M)} at a point moved from the second landmark point by the fifth distance in the direction of −{right arrow over (v.sub.M)}.
These features in combination with the features of parent claims 1, 10 and 11 are not found to be taught in the prior art in combination with the other limitations.
Consider Claim 18
Claim 18 recites wherein PL is the left teeth landmark point, P12 is the second landmark point, and pR is the right teeth landmark point,
wherein a first point C(ul) of a target point is searched on C(u) while increasing a parameter u by a first value, a second point C(u2) of the target point is searched on C(u) while increasing the parameter u by a second value, the second point C(u2) of the target point is a point minimizing the dl l=|C(ul)-C(u2)11-1p1L-p2 1, a third point C(u3) of the target point is searched on C(u) while increasing the parameter u by a third value, the third point C(u3) of the target point is a point minimizing the d12=jjC(u2)-C(u3)j-jpP12 -PR I,
wherein when all of dlI, d12 and d13=jjC(u3)-C(ul)jj-|| PR-p|| are less than a second threshold value, the target points C(ul), C(u2) and C(u3) are selected as the candidate target point group, and wherein the target point group includes three points of C(ul), C(u2) and C(u3).
Claim 18 recites subject matter as below which is not taught in the prior art in a manner that combines with the remaining limitations of claim 18 including the parent claims.
Conclusion
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UMAIR AHSAN
Primary Examiner
Art Unit 2647
/UMAIR AHSAN/Primary Examiner, Art Unit 2647
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