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 Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
Claim 7 recites limitations “a time point synchronization unit configured to synchronize acquisition time points of cone beam computed tomography (CBCT) data and 3D scan data; a coordinate synchronization unit configured to conform coordinate systems of the CBCT data and the 3D scan data; a 3D scan image construction unit configured to construct a 3D scan image in which a motion is corrected by matching depth maps created each time the 3D scan data are acquired; and a CBCT 3D image construction unit configured to construct a CBCT 3D image in which the motion is corrected from the CBCT data by applying motion information acquired by matching the depth maps”. have been interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because it uses/they use a linking word “unit” “configured to” coupled with functional language respectively recited after each of the aforementioned claim limitations, without reciting sufficient structure to achieve the function. Furthermore, the generic placeholder is not preceded by a structural modifier.
A review of the specification shows that the following appears to be the corresponding structure described in the specification for the 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph limitation: see figure 2 and corresponding text. If applicant wishes to provide further explanation or dispute the examiner’s interpretation of the corresponding structure, applicant must identify the corresponding structure with reference to the specification by page and line number, and to the drawing, if any, by reference characters in response to this Office action.
If applicant does not intend to have the claim limitation(s) treated under 35 U.S.C. 112(f) applicant may amend the claim(s) so that it/they will clearly not invoke 35 U.S.C. 112(f) or present a sufficient showing that the claim recites/recite sufficient structure, material, or acts for performing the claimed function to preclude application of 35 U.S.C. 112(f).
For more information, see MPEP § 2173 et seq. and Supplementary Examination Guidelines for Determining Compliance With 35 U.S.C. 112 and for Treatment of Related Issues in Patent Applications, 76 FR 7162, 7167 (Feb. 9, 2011).
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.
The USPTO “Interim Guidelines for Examination of Patent Applications for Patent Subject Matter Eligibility” (Official Gazette notice of 23 February 2010), Annex IV, reads as follows:
The USPTO recognizes that applicants may have claims directed to computer readable media that cover signals per se, which the USPTO must reject under 35 U.S.C. § 101 as covering both non-statutory subject matter and statutory subject matter. In an effort to assist the patent community in overcoming a rejection or potential rejection under 35 U.S.C. § 101 in this situation, the USPTO suggests the following approach. A claim drawn to such a computer readable medium that covers both transitory and non-transitory embodiments may be amended to narrow the claim to cover only statutory embodiments to avoid a rejection under 35 U.S.C. § 101 by adding the limitation "non-transitory" to the claim. Cf. Animals - Patentability, 1077 Off. Gaz. Pat. Office 24 (April 21, 1987) (suggesting that applicants add the limitation "non-human" to a claim covering a multi-cellular organism to avoid a rejection under 35 U.S.C. § 101). Such an amendment would typically not raise the issue of new matter, even when the specification is silent because the broadest reasonable interpretation relies on the ordinary and customary meaning that includes signals per se. The limited situations in which such an amendment could raise issues of new matter occur, for example, when the specification does not support a non-transitory embodiment because a signal per se is the only viable embodiment such that the amended claim is impermissibly broadened beyond the supporting disclosure. See, e.g., Gentry Gallery, Inc. v. Berkline Corp., 134 F.3d 1473(Fed. Cir. 1998).
Claim 8 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter as follows. Claim 8 defines a “computer program ” embodying functional descriptive material. However, the claim does not define a non-transitory computer-readable medium or memory and is thus non-statutory for that reason (i.e., “examination the pending claims must be interpreted as broadly as their terms reasonably allow). The broadest reasonable interpretation of a claim drawn to a computer readable medium (also called machine readable medium and other such variations) typically covers forms of non-transitory tangible media and transitory propagating signals per se in view of the ordinary and customary meaning of computer readable media, particularly when the specification is silent. See MPEP 2111.01. When the broadest reasonable interpretation of a claim covers a signal per se, the claim must be rejected under 35 U.S.C. § 101 as covering non-statutory subject matter. See In see Official Gazette Notice 1351 OG212, February 23,2010). That is, the scope of the presently claimed “computer program product ” typically covers forms of non-transitory tangible media and transitory propagating signals per se. The examiner suggests amending the claim to embody the program on a “computer readable medium” and adding the limitation ”non-transitory ” to the claim or equivalent in order to make the claim statutory. Any amendment to the claim should be commensurate with its corresponding disclosure.
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 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.
Claims 1-3 and 7-8 are rejected under 35 U.S.C. 103 as being unpatentable over JOO et al. (KR 2016000482) in view of Mei et al. (Registration of the Cone Beam CT and Blue-Ray Scanned Dental Model Based on Improved ICP Algorithm, International Journal of Biomedical Imaging Volume 2014, Article ID 348740, 20124, pages 1-8, USPTO-892).
Regarding claims 1 and 7 JOO disclose matching data, which is performed by an apparatus for matching data, comprising (JOO, page 4, paragraph 5 disclose FIG. 4A is a view showing marking points (3D Surface Landmarks) on the 3D Stone Model obtained in FIG. 3. FIG. FIG. 4B is a diagram showing marking points (3D Volume Landmarks) for matching with a 3D Stone Model on a 3D Head Image obtained in FIG. 1. FIG. FIG. 4c is a diagram illustrating a 3D head image of a 3D mouth surface model and a 3D head image by performing a 3D landmark-transformation based on a 3D mark point, (3D Stone Model) are matched, and paragraph 9, discloses Thereafter, registration is performed using the mark points displayed on the 3D Stone Model and the mark points displayed on the 3D Head Image. That is, a conversion process of rotating and translating the mark points displayed in the 3D Head Image to the mark points displayed in the 3D Stone Model to the minimum error is performed in the 3D mouth image The same applies to the surface model and consequently the 3D mouth surface model is matched to the 3D head image. This process is called 3D Landmark-Transform. This corresponds to matching data ):
synchronizing acquisition time points of cone beam computed tomography (CBCT) data and 3D scan data (JOO page 3, paragraph 3 recites FIG. 1 is a diagram illustrating a process of acquiring a 3D head image through a CBCT scanning method according to an embodiment of the present invention, page 3, paragraph eleventh disclose FIG. 3A is a view illustrating a process of generating a 3D stone model based on a tomography of a gypsum model using tomography equipment such as CBCT according to an exemplary embodiment of the present invention. FIG. 3B is a diagram illustrating a method of scanning a gypsum model with a 3D scanner according to an exemplary embodiment of the present invention, or scanning a patient's mouth based on an intra-oral 3D scanner, Model (3D Stone Model), page 7, paragraph sixth disclose the guide may be a 3D Stone Model, a clipped 3D Head Image, or the like, as shown in FIG. 7B. In addition, such as the ability to visualize changes in measured values used in 3D diagnosis and 3D analysis in real-time. Since in the system of JOO above process is performed to obtain and visualize changes in measured values used in 3D diagnosis and 3D analysis in real-time visualize changes in measured values used in 3D diagnosis and 3D analysis in real-time it is obvious in the system of JOO acquisition time points of cone beam computed tomography (CBCT) data and 3D scan data are synchronized and also note: page 5, paragraph 5, time point and coordinates of two are synchronized).;
conforming coordinate systems of the CBCT data and the 3D scan data (JOO, page 3 third paragraph 3D head model image through CBCT and paragraph eleventh disclose stone model image based on 3D intra-oral scanner and page 5, fifth paragraph disclose the upper left molar 3D Tooth Crown Model is extracted from a 3D Stone Model matched to a 3D Head Image, and the 3D Tooth Crown Model is extracted from the 3D Stone Model, The 3D Tooth Volume Model extracted from the 3D Head Image is acquired and the 3D tooth model is generated by synchronizing the coordinate systems of the two models. Therefore it is obvious in the system of JOO that conforming coordinate systems of the CBCT data and the 3D scan data);
constructing a 3D scan image in which a motion is corrected by matching depth maps created each time the 3D scan data are acquired (JOO, page 4, paragraph 5 disclose FIG. 4A is a view showing marking points (3D Surface Landmarks) on the 3D Stone Model (depth map) obtained in FIG. 3. FIG. FIG. 4B is a diagram showing marking points (3D Volume Landmarks) for matching with a 3D Stone Model (depth map) on a 3D Head Image (depth map) obtained in FIG. 1. FIG. FIG. 4c is a diagram illustrating a 3D head image of a 3D mouth surface model and a 3D head image by performing a 3D landmark-transformation based on a 3D mark point, (3D Stone Model) are matched, and paragraph 9, discloses Thereafter, registration is performed using the mark points displayed on the 3D Stone Model (depth map) and the mark points displayed on the 3D Head Image (depth map). This obviously registration/ match of two depth maps would provide removing motion or movement artifact and JOO, page 5, fifth paragraph disclose the upper left molar 3D Tooth Crown Model is extracted from a 3D Stone Model (depth map) matched to a 3D Head Image (depth map). This disclosure of JOO obviously corresponds to constructing a 3D scan image in which a motion is corrected by matching depth maps created each time the 3D scan data are acquired); and
constructing a CBCT 3D image in which the motion is corrected from the CBCT data by applying motion information acquired by matching the depth maps (JOO, page 5, first paragraph discloses FIG. 5 is a flowchart illustrating a method of acquiring a 3D Tooth Volume Model of a tooth from a 3D Head Image generated (based on CBCT image and page 5, paragraph sixth disclose the generated 3D tooth models are generated based on the 3D head image (CBCT) and the 3D stone model (3D scan depth map) matched to the 3D head model (CBCT depth map) through the above-described process, . Since the coordinate system of the 3D tooth crown model (3D Tooth Crown Model) and the 3D tooth volume model (3D Tooth Volume Model) that make up the 3D tooth model are synchronized with each other, the 3D tooth model The 3D Tooth Crown Model and the 3D Tooth Volume Model are similar to the actual teeth which are moved as one, so that the simulation for the tooth correction simulation described later It can be used for an operation. This obviously corresponds to constructing a CBCT 3D image in which the motion is corrected from the CBCT data by applying motion information acquired by matching the depth maps).
In the same field of endeavor of matching/registration and conforming of coordinate of cone beam computed tomography (CBCT) data and scan data
Mei disclose conforming coordinate systems of the CBCT data and the 3D scan data (Mei page 1, ABSTRACT disclose Multimodality image registration and fusion has complementary significance for guiding dental implant surgery. As the needs of the different resolution image registration, we develop an improved Iterative Closest Point (ICP) algorithm that focuses on the registration of Cone Beam Computed Tomography (CT) image and high-resolution Blue-light scanner image. The proposed algorithm includes two major phases, coarse and precise registration. Firstly, for reducing the matching interference of human subjective factors, we extract feature points based on curvature characteristics and use the improved three point’s translational transformation method to realize coarse registration. Then, the feature point set and reference point set, obtained by the initial registered transformation, are processed in the precise registration step. Even with the unsatisfactory initial values, this two steps registration method can guarantee the global convergence and the convergence precision, page 3 paragraph 2.3 The Coarse Registration thru paragraph 2.4 The Precise Registan disclose matching/registration and conforming of coordinate of cone beam computed tomography (CBCT) data and scan data ICP algorithm and transformation).
Therefore it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to conform coordinate systems of the CBCT data and the 3D scan data by matching/registration as shown by combination of JOO and Mei because such a system provides precise automated 3D multimodality registration and fusion for dental implant surgery as stated Mei in the ABSTRACT and page 6 , paragraph 5 Conclusion.
Regarding claim 2 JOO disclose conforming a frame rate of a CBCT imaging apparatus for acquiring the CBCT data and a frame rate of a 3D scan imaging apparatus for acquiring the 3D scan data and conforming a time point at which the CBCT imaging apparatus begins to detect the CBCT data and a time point at which the 3D scan imaging apparatus begins to capture the 3D scan data (JOO JOO page 3, paragraph 3 recites FIG. 1 is a diagram illustrating a process of acquiring a 3D head image through a CBCT scanning method according to an embodiment of the present invention, page 3, paragraph eleventh disclose FIG. 3A is a view illustrating a process of generating a 3D stone model based on a tomography of a gypsum model using tomography equipment such as CBCT according to an exemplary embodiment of the present invention. FIG. 3B is a diagram illustrating a method of scanning a gypsum model with a 3D scanner according to an exemplary embodiment of the present invention, or scanning a patient's mouth based on an intra-oral 3D scanner, Model (3D Stone Model), page 7, paragraph sixth disclose the guide may be a 3D Stone Model, a clipped 3D Head Image, or the like, as shown in FIG. 7B. In addition, such as the ability to visualize changes in measured values used in 3D diagnosis and 3D analysis in real-time. Since in the system of JOO above process is performed to obtain and visualize changes in measured values used in 3D diagnosis and 3D analysis in real-time visualize changes in measured values used in 3D diagnosis and 3D analysis in real-time it is obvious in the system of JOO acquisition time points of cone beam computed tomography (CBCT) data and 3D scan data are synchronized and also note: page 5, paragraph 5, time point and coordinates of two are synchronized. Since the JOO system is used in real-time therefor it is obvious that in thew system of JOO to conforming a frame rate of a CBCT imaging apparatus for acquiring the CBCT data and a frame rate of a 3D scan imaging apparatus for acquiring the 3D scan data and conforming a time point at which the CBCT imaging apparatus begins to detect the CBCT data and a time point at which the 3D scan imaging apparatus begins to capture the 3D scan data).
Regarding claim 3 Mei disclose calculating a transform by using an iterative closest point (ICP) algorithm to minimize a matching error of the CBCT data and the 3D scan data (Mei page 1, ABSTRACT disclose Multimodality image registration and fusion has complementary significance for guiding dental implant surgery. As the needs of the different resolution image registration, we develop an improved Iterative Closest Point (ICP) algorithm that focuses on the registration of Cone Beam Computed Tomography (CT) image and high-resolution Blue-light scanner image. The proposed algorithm includes two major phases, coarse and precise registration. Firstly, for reducing the matching interference of human subjective factors, we extract feature points based on curvature characteristics and use the improved three point’s translational transformation method to realize coarse registration. Then, the feature point set and reference point set, obtained by the initial registered transformation, are processed in the precise registration step. Even with the unsatisfactory initial values, this two steps registration method can guarantee the global convergence and the convergence precision, page 3 paragraph 2.3 The Coarse Registration thru paragraph 2.4 The Precise Registan disclose matching/registration and conforming of coordinate of cone beam computed tomography (CBCT) data and scan data ICP algorithm and transformation. This corresponds to calculating a transform by using an iterative closest point (ICP) algorithm to minimize a matching error of the CBCT data and the 3D scan data );
applying the transform to the 3D scan data (ABSTACT disclose, we develop an improved Iterative Closest Point (ICP) algorithm that focuses on the registration of Cone Beam Computed Tomography (CT) image and high-resolution Blue-light scanner image. The proposed algorithm includes two major phases, coarse and precise registration. Firstly, for reducing the matching interference of human subjective factors, we extract feature points based on curvature characteristics and use the improved three point’s translational transformation method to realize coarse registration. Then, the feature point set and reference point set, obtained by the initial registered transformation, are processed in the precise registration step and page 3 paragraph 2.3 The Coarse Registration thru paragraph 2.4 The Precise Registan disclose matching/registration and conforming of coordinate of cone beam computed tomography (CBCT) data and scan data ICP algorithm and transformation. This corresponds to applying the transform to the 3D scan data and
moving the 3D scan data, to which the transform is applied, to the CBCT data (ABSTACT disclose, we develop an improved Iterative Closest Point (ICP) algorithm that focuses on the registration of Cone Beam Computed Tomography (CT) image and high-resolution Blue-light scanner image. The proposed algorithm includes two major phases, coarse and precise registration. Firstly, for reducing the matching interference of human subjective factors, we extract feature points based on curvature characteristics and use the improved three point’s translational transformation method to realize coarse registration. Then, the feature point set and reference point set, obtained by the initial registered transformation, are processed in the precise registration step and page 3, left-column paragraph 2.3.1 thru right-column 2.4 disclose coarse to precise registration of two i.e. 3D scan data and CBCT using translation and rotation transformation therefore it is obvious that moving the 3D scan data, to which the transform is applied, to the CBCT data because two image are matched and registered.
Regarding claim 8, JOO disclose a computer program stored in computer readable medium to execute the claim 1 (see the analysis of claim 1 and 7 above and JOO page 10, paragraphs second and fourth disclose computer system program).
Allowable Subject Matter
Claims 4-6 are objected as being dependent on rejected base claim but would be allowable over the prior art record if rewritten in the independent form including the limitations of the base claim and any intervening claims.
Communication
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ISHRAT I SHERALI whose telephone number is (571)272-7398. The examiner can normally be reached Monday-Friday 8:00AM -5:00 PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Matthew Bella can be reached on 571-272-7778. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ISHRAT I SHERALI/Primary Examiner, Art Unit 2667
ISHRAT I. SHERALI
Examiner
Art Unit 2667
Prosecution Insights