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 .
Election/Restrictions
Applicant’s election without traverse of Invention (claims 1-10 and 17-18) in the reply filed on 03/02/2026 is acknowledged. Claims 11-16 and 19-20 are withdrawn.
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 1-10 and 17-18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite an abstract idea as discussed below. This abstract idea is not integrated into a practical application for the reasons discussed below. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception for the reasons discussed below.
Step 1 of the 2019 Guidance requires the examiner to determine if the claims are to one of the statutory categories of invention. Applied to the present application, the claims belong to one of the statutory classes of a process or product as a computer implemented method or a computer system/product.
Step 2A of the 2019 Guidance is divided into two Prongs. Prong 1 requires the examiner to determine if the claims recite an abstract idea, and further requires that the abstract idea belong to one of three enumerated groupings: mathematical concepts, mental processes, and certain methods of organizing human activity.
Regarding claim 1, the independent claims is directed to a computer-implemented method for user-specific selection of a model for determining an implant-related parameter. The claim limitations of “applying at least one first model from the set of models on the first patient image data to determine an implant-related parameter; suggesting the determined implant-related parameter to a dedicated user; receiving...feedback on the suggested implant-related parameter, the user feedback comprising one of a confirmation of the suggested implant-related parameter and an adaption thereof; and selecting, based on the user feedback, at least one second model from the set of models that is to be applied on second patient image data” are directed to an abstract because the claim limitations can be performed via mathematical concepts and mental process, with assistance of basic physical aids or with pen paper. See MPEP § 2106.04(a)(2)(III)(B). Intellectual Ventures LLC v. Symantec Corp., 838 F.3d 1307, 1318 (Fed. Cir. 2016) established that mental processes encompass acts which, absent anything beyond generic computer components, may be “performed by a human, mentally or with pen and paper.” Intellectual Ventures additionally established that if a claim, under its broadest reasonable interpretation, covers performance in the mind but for the recitation of generic computer components, then it is still in the mental processes category of abstract ideas unless the claim cannot be practically performed in the mind.
The judicial exception is not integrated into a “practical application” as defined by the Subject Matter Eligibility Analysis documented in Federal Register 84(4), issued on 07 January 2019 and since documented in MPEP § 2106. While the claim recites that a “one or more processor” that performs the limitations encompassing mental processes, this simply represents implementing the abstract ideas with a computer. The additional limitations in relation to the computer, computer product, or computer system does not offer a meaningful limitation beyond generally linking the use of the method to a computer (see ALICE CORP. v. CLS BANK INT’L 573 U. S. ____ (2014)). The claim does not recite a particular machine applying or being used by the abstract idea. See also subsection I of the cited section and MPEP § 2106.05(f) which indicates that instructions to implement the abstract idea on a computer or that “using a computer as a tool to perform the abstract idea” are not sufficient to integrate a judicial exception into a “practical application” as interpreted by the courts.
Furthermore, the claim does not include additional elements which are sufficient to amount to significantly more than the abstract idea. The claim limitation of “receiving first patient image data indicative of a patient anatomy in which an implant is to be placed” is directed to extra solution activity of gathering data and does not include additional elements which are sufficient to amount to significantly more than the abstract idea.
In consideration of each of the relevant factors and the claim elements both individually and in combination, claim 1 is directed to an abstract idea without sufficient integration into a practical application and without significantly more.
Regarding claims 2-10, the clams further recites limitation (i.e., selecting steps, determining steps, utilizing steps, generating steps, etc.) which are directed to an abstract because the claim limitations can be performed via mathematical concepts and mental process, with assistance of basic physical aids or with pen paper. Furthermore, the claims also recite claim limitations (i.e., receiving steps) which are directed to extra solution activity of gathering data and does not include additional elements which are sufficient to amount to significantly more than the abstract idea. The additional claim limitations of that the implant is a bone screw recited in claim 8 and that the patient anatomy is a spine recited in claim 9 do not add significantly more than the abstract ideas because the claims do not positively recite any steps of implanting the bone screw in the spine.
Regarding claim 17, the independent claims is directed to an apparatus for a user-specific selection of a model for determining an implant-related parameter. The claim limitations of “apply at least one first model from the set of models on the first patient image data to determine an implant-related parameter; suggest the determined implant-related parameter to a dedicated user; receive...feedback on the suggested implant-related parameter, the user feedback comprising one of a confirmation of the suggested implant-related parameter and an adaption thereof; and select, based on the user feedback, at least one second model from the set of models that is to be applied on second patient image data” are directed to an abstract because the claim limitations can be performed via mathematical concepts and mental process, with assistance of basic physical aids or with pen paper. See MPEP § 2106.04(a)(2)(III)(B). Intellectual Ventures LLC v. Symantec Corp., 838 F.3d 1307, 1318 (Fed. Cir. 2016) established that mental processes encompass acts which, absent anything beyond generic computer components, may be “performed by a human, mentally or with pen and paper.” Intellectual Ventures additionally established that if a claim, under its broadest reasonable interpretation, covers performance in the mind but for the recitation of generic computer components, then it is still in the mental processes category of abstract ideas unless the claim cannot be practically performed in the mind.
The judicial exception is not integrated into a “practical application” as defined by the Subject Matter Eligibility Analysis documented in Federal Register 84(4), issued on 07 January 2019 and since documented in MPEP § 2106. While the claim recites that a “one or more processor” that performs the limitations encompassing mental processes, this simply represents implementing the abstract ideas with a computer. The additional limitations in relation to the computer, computer product, or computer system does not offer a meaningful limitation beyond generally linking the use of the method to a computer (see ALICE CORP. v. CLS BANK INT’L 573 U. S. ____ (2014)). The claim does not recite a particular machine applying or being used by the abstract idea. See also subsection I of the cited section and MPEP § 2106.05(f) which indicates that instructions to implement the abstract idea on a computer or that “using a computer as a tool to perform the abstract idea” are not sufficient to integrate a judicial exception into a “practical application” as interpreted by the courts.
Furthermore, the claim does not include additional elements which are sufficient to amount to significantly more than the abstract idea. The claim limitation of “receive first patient image data indicative of a patient anatomy in which an implant is to be placed” is directed to extra solution activity of gathering data and does not include additional elements which are sufficient to amount to significantly more than the abstract idea.
In consideration of each of the relevant factors and the claim elements both individually and in combination, claim 17 is directed to an abstract ideas without sufficient integration into a practical application and without significantly more.
Regarding claim 18, the clam further recites limitation (i.e., the selecting and generate steps) which are directed to an abstract because the claim limitations can be performed via mathematical concepts and mental process, with assistance of basic physical aids or with pen paper.
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.
Claims 1-10 and 17-18 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claim 1, the claim limitation “an implant-related parameter” in line 8 is indefinite because it is unclear if this implant-related parameter is the same implant-related parameter that is already reacted in line 2.
Furthermore for claim 1, the claim limitation “the user” in line 10 is indefinite because it is unclear if this user is same as the “dedicated user” that is recited in line 9.
Regarding claim 2, the claim limitation “the user” is indefinite because it is unclear if this user is same as the “dedicated user” that is recited in claim 1.
Regarding claim 3, the claim limitation “the model” in line 3 is indefinite because it is unclear if this model is related to the first model, a model that is recited in preamble of claim 1 or different model.
Furthermore for claim 3, the claim limitations “some of the models” in line 4 is indefinite because it is unclear if these models related to the trained models that is recited in claim 1.
Regarding claim 4, the claim limitation “each of the models from the model set” in line 4 is indefinite because it is unclear what models and model set the claim is referring to.
Furthermore for claim 4, the claim limitation “the adapted implant-related parameter” in lines 6-7 is indefinite because it is unclear if this adapted implant-related parameter is related to the adaption of the suggested implant-related parameter or a separated adapted implant-related parameter.
Regarding claim 7, the claim limitation “the user” in line 8 is indefinite because it is unclear if this user is same as the “dedicated user” that is recited in claim 1.
Regarding claim 17, the claim limitation “an implant-related parameter” in line 8 is indefinite because it is unclear if this implant-related parameter is the same implant-related parameter that is already reacted in line 2.
Furthermore for claim 17, the claim limitation “the user” in line 10 is indefinite because it is unclear if this user is same as the “dedicated user” that is recited in line 9.
Regarding claim 18, the claim limitation “the user” is indefinite because it is unclear if this user is same as the “dedicated user” that is recited in claim 17.
Claims 5-6, 8-10 are rejected as they depend from rejected claim 1.
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 1-10 and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over Roh et al. (US 2021/0382457; hereinafter Roh), in view of Metcalfe et al. (US 2022/0226044; hereinafter Metcalfe).
Regarding claim 1, Roh discloses systems and method for assisting a surgeon and producing patient-specific medical devices. Roh shows a computer-implemented method for a user-specific selection of a model for determining an implant-related parameter (see abstract; fig. 2), with a model being indicative of a dedicated implant- related parameter for a dedicated patient anatomy (see fig. 4; par. [0054) the method comprising: receiving first patient image data indicative of a patient anatomy in which an implant is to be placed (par. [0056] states “surgical assistance system 464 can analyze data (e.g., one or more images) of a patient to identify one or more features of interest. The features of interest can include, without limitation, implantation sites, targeted features, non-targeted features, access paths, anatomical structures, or combinations thereof.”); applying at least one first model on the first patient image data to determine an implant-related parameter (par. [0055] states “The surgical assistance system 464 can convert the implant surgery information, for example, by converting images into arrays of integers or histograms, entering patient information into feature vectors, or extracting values from the pre-operative plan”; par. [0057] states “the surgical assistance system 464 can apply analysis procedures by supplying the converted implant surgery information to a machine learning model trained to select implant configurations. For example, a neural network model can be trained to select pedicle screw configurations for a spinal surgery. The neural network can be trained with training items each comprising a set of images scans (e.g., camera, MRI, CT, x-ray, etc.) and patient information, an implant configuration used in the surgery, and/or a scored surgery outcome resulting from one or more of: surgeon feedback, patient recovery level, recovery time, results after a set number of years”); suggesting the determined implant-related parameter to a dedicated user (par. [0057] states “This neural network can receive the converted surgery information and provide output indicating the pedicle screw configuration. Analysis procedures can be used to select the types of implants, instruments, surgical techniques”); receiving, from the user, feedback on the suggested implant-related parameter, the user feedback comprising one of a confirmation of the suggested implant-related parameter and an adaptation thereof (par. [0118] states “results can be used to provide recommendations during a surgical procedure, e.g., with text or visual annotations provided as overlies on a flat panel display, through auditory or haptic feedback alerts, or using an AR or VR system, e.g., to display an overlay of the implant on the patient anatomy or to display guidance on the suggested insertion point and angle. In some implementations, the results can be used to control robotic systems, e.g., causing a robotic arm to align itself according to the recommended insertion point and angle, which may be first confirmed by a surgeon”; par. [0139] states “The training data input can be paired with results to create training items. The results can be, for example, human annotated medical imaging data (as a comparison for identifications such as boundaries and insertion points identified by a model), human feedback to model outputs, surgeons' post-operative suggestion feedback (e.g., whether the surgeon accepted model provided recommendations completely, or made certain changes, or disregarded), surgeons post-operative operation outcome success score, post-operative images that can be analyzed to determine results”).
But, Roh fails to explicitly state wherein a set of different models is provided, picking one first model from the set of models, and selecting, based on the user feedback, at least one second model from the set of models that is to be applied on second patient image data.
Metcalfe discloses a orthopedic planning systems and method of repaid. Metcalfe teaches wherein a set of models is provided and picking one first model from the set of models (par. [0006] states “The memory may be configured to store one or more implant models and one or more bone models” and “The display module may be configured to display in a first display window of a graphical user interface a selected one of the implant models”; par. [0007] states “selecting an implant model from a plurality of implant models by interacting with the graphical user interface”), and selecting, based on the user feedback, at least one second model from the set of models that is to be applied on second patient image data (par. [0007] states “selecting an implant model from a plurality of implant models by interacting with the graphical user interface”; par. [0067] states “The memory 148 may be configured to access, load, edit and/or store instances of one or more bone models 138, implant models 140 and/or surgical plans 142 in response to one or more commands from the data module 150”; par. [0094] and [0096] state picking a second implant model 440 accordingly to a different bone model).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing of the claimed invention, to have utilized the teaching of wherein a set of different models is provided and picking one first model from the set of models, and selecting, based on the user feedback, at least one second model from the set of models that is to be applied on second patient image data in the invention of Roh, as taught by Metcalfe, to provide a more accurate planning system for orthopedic procedure by having multiple of different specific implant model for different cortical area of an associated bone.
Regarding claim 2, Roh and Metcalfe disclose the invention substantially as described in the 103 rejection, furthermore, Roh shows selecting the at least one first model based on at least one first historical data item associated with the user (see par. [0054], [0055], [0118], [0139]) and Metcalfe teaches indicative of at least one third model of the set of models; and generating at least one second historical data item associated with the user and indicative of the at least one second model (see par. [0006], [0007], [0067], [0094], [0096], [0099], [0100]). Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing of the claimed invention, to have utilized the teaching of indicative of at least one third model of the set of models; and generating at least one second historical data item associated with the user and indicative of the at least one second model in the invention of Roh, as taught by Metcalfe, to provide a more accurate planning system for orthopedic procedure by having multiple of different specific implant model for different cortical area of an associated bone.
Regarding claim 3, Roh and Metcalfe disclose the invention substantially as described in the 103 rejection, furthermore, Roh shows wherein there exist multiple first historical data items, and wherein selecting the at least one first model comprises at least one of: determining the model most often indicated in the multiple first historical data items (see par. [0054], [0055], [0118], [0139]).
Regarding claim 4, Roh and Metcalfe disclose the invention substantially as described in the 103 rejection, furthermore, Roh shows wherein the user feedback comprises an adaptation of the suggested implant-related parameter (see par. [0054], [0055], [0118], [0139]), and Metcalfe teaches utilizing each of the models from the model set to determine (see par. [0006], [0007], [0067], [0094], [0096], [0099], [0100]), based on the first patient image data (see par. [0006], [0007], [0067], [0094], [0096], [0099], [0100]), a respective implant-related parameter; determining, for each respective implant-related parameter, a respective fit to the adapted implant-related parameter (see par. [0006], [0007], [0067], [0094], [0096], [0099], [0100]); and generating the at least one second historical data item based on one or more of the respective fits (see par. [0006], [0007], [0067], [0094], [0096], [0099], [0100]). Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing of the claimed invention, to have utilized the teaching of utilizing each of the models from the model set to determine, based on the first patient image data, a respective implant-related parameter; determining, for each respective implant-related parameter, a respective fit to the adapted implant-related parameter, and generating the at least one second historical data item based on one or more of the respective fits in the invention of Roh, as taught by Metcalfe, to provide a more accurate planning system for orthopedic procedure by having multiple of different specific implant model for different cortical area of an associated bone.
Regarding claim 5, Roh and Metcalfe disclose the invention substantially as described in the 103 rejection, furthermore, Roh shows receiving auxiliary information indicative of at least one of a patient-related parameter (see par. [0054], [0055], [0118], [0139]) and a user-related parameter (see par. [0054], [0055], [0118], [0139]), and wherein at least the first model is also determined based on the received auxiliary information (see par. [0054], [0055], [0118], [0139]).
Regarding claim 6, Roh and Metcalfe disclose the invention substantially as described in the 103 rejection, furthermore, Roh shows wherein the auxiliary information is reflected in the model (see par. [0054], [0055], [0118], [0139]), and Metcalfe teaches the set of models (see par. [0006], [0007], [0067], [0094], [0096], [0099], [0100]). Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing of the claimed invention, to have utilized the teaching of set of models in the invention of Roh, as taught by Metcalfe, to provide a more accurate planning system for orthopedic procedure by having multiple of different specific implant model for different cortical area of an associated bone.
Regarding claim 7, Roh and Metcalfe disclose the invention substantially as described in the 103 rejection, furthermore, Roh shows receiving auxiliary information indicative of at least one of a patient-related parameter and a user-related parameter (see par. [0054], [0055], [0118], [0139]), and wherein: at least the first model is also determined based on the received auxiliary information (see par. [0054], [0055], [0118], [0139]), each historical data item is indicative of the auxiliary information (see par. [0054], [0055], [0118], [0139]), and the at least one first model is selected based on the at least one first historical data item that is associated with the user (see par. [0054], [0055], [0118], [0139]) and of the auxiliary information(see par. [0054], [0055], [0118], [0139]), and Metcalfe teaches the at least one third model of the set of models (see par. [0006], [0007], [0067], [0094], [0096], [0099], [0100]).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing of the claimed invention, to have utilized the teaching at least one third models of the set of models in the invention of Roh, as taught by Metcalfe, to provide a more accurate planning system for orthopedic procedure by having multiple of different specific implant model for different cortical area of an associated bone.
Regarding claim 8, Roh and Metcalfe disclose the invention substantially as described in the 103 rejection, furthermore, Roh shows wherein the implant is a bone screw and the dedicated implant-related parameter is indicative of at least one of a dedicated orientation of the screw relative to the patient's anatomy (see fig. 5A-B, 6A, 8A and 12A; par. [0121]-[0123], [0131]), a dedicated position of a head of the screw relative to the patient's anatomy (see fig. 5A-B, 6A, 8A and 12A; par. [0121]-[0123], [0131]), a dedicated position of a tip of the screw relative to the patient's anatomy, a dedicated screw length, and a dedicated screw diameter (see fig. 5A-B, 6A, 8A and 12A; par. [0121]-[0123], [0131]).
Regarding claim 9, Roh and Metcalfe disclose the invention substantially as described in the 103 rejection, furthermore, Roh shows wherein the patient anatomy is a spine, wherein there exists a dedicated set of models for each of multiple sets of one or more vertebrae of the spine that are to be treated (see fig. 5A-B, 6A, 8A and 12A; par. [0121]-[0123], [0131]), and further comprising: receiving a user input on a set of one or more vertebrae to be treated (see fig. 5A-B, 6A, 8A and 12A; par. [0121]-[0123], [0131]), wherein model selection is also based on the user input (see fig. 5A-B, 6A, 8A and 12A; par. [0121]-[0123], [0131]).
Regarding claim 10, Roh and Metcalfe disclose the invention substantially as described in the 103 rejection, furthermore, Roh shows wherein the step of suggesting the determined implant-related parameter to the user comprises visualizing the implant-related parameter relative to the first patient image data (see fig. 5A-B, 6A, 8A and 12A; par. [0121]-[0123], [0131]).
Regarding claim 17, Roh discloses systems and method for assisting a surgeon and producing patient-specific medical devices. Roh shows an apparatus (see fig. 2 and abstract) for a user-specific selection of a model for determining an implant-related parameter (see abstract; fig. 2), with a model being indicative of a dedicated implant-related parameter for a dedicated patient anatomy (see fig. 4 and par. [0054]), the apparatus being configured to: receive first patient image data indicative of a patient anatomy in which an implant is to be placed (par. [0056] states “surgical assistance system 464 can analyze data (e.g., one or more images) of a patient to identify one or more features of interest. The features of interest can include, without limitation, implantation sites, targeted features, non-targeted features, access paths, anatomical structures, or combinations thereof.”; apply at least one first model on the first patient image data to determine an implant-related parameter (par. [0055] states “The surgical assistance system 464 can convert the implant surgery information, for example, by converting images into arrays of integers or histograms, entering patient information into feature vectors, or extracting values from the pre-operative plan”; par. [0057] states “the surgical assistance system 464 can apply analysis procedures by supplying the converted implant surgery information to a machine learning model trained to select implant configurations. For example, a neural network model can be trained to select pedicle screw configurations for a spinal surgery. The neural network can be trained with training items each comprising a set of images scans (e.g., camera, MRI, CT, x-ray, etc.) and patient information, an implant configuration used in the surgery, and/or a scored surgery outcome resulting from one or more of: surgeon feedback, patient recovery level, recovery time, results after a set number of years”); suggest the determined implant-related parameter to a dedicated user (par. [0057] states “This neural network can receive the converted surgery information and provide output indicating the pedicle screw configuration. Analysis procedures can be used to select the types of implants, instruments, surgical techniques”); receive, from the user, feedback on the suggested implant-related parameter, the user feedback comprising one of a confirmation of the suggested implant-related parameter and an adaptation thereof (par. [0118] states “results can be used to provide recommendations during a surgical procedure, e.g., with text or visual annotations provided as overlies on a flat panel display, through auditory or haptic feedback alerts, or using an AR or VR system, e.g., to display an overlay of the implant on the patient anatomy or to display guidance on the suggested insertion point and angle. In some implementations, the results can be used to control robotic systems, e.g., causing a robotic arm to align itself according to the recommended insertion point and angle, which may be first confirmed by a surgeon”; par. [0139] states “The training data input can be paired with results to create training items. The results can be, for example, human annotated medical imaging data (as a comparison for identifications such as boundaries and insertion points identified by a model), human feedback to model outputs, surgeons' post-operative suggestion feedback (e.g., whether the surgeon accepted model provided recommendations completely, or made certain changes, or disregarded), surgeons post-operative operation outcome success score, post-operative images that can be analyzed to determine results”).
But, Roh fails to explicitly state picking one first model from the set of models, and select, based on the user feedback, at least one second model from the set of models that is to be applied on second patient image data.
Metcalfe discloses an orthopedic planning systems and method of repaid. Metcalfe teaches picking one first model from the set of models (par. [0006] states “The memory may be configured to store one or more implant models and one or more bone models” and “The display module may be configured to display in a first display window of a graphical user interface a selected one of the implant models”; par. [0007] states “selecting an implant model from a plurality of implant models by interacting with the graphical user interface”), and selecting, based on the user feedback, at least one second model from the set of models that is to be applied on second patient image data (par. [0007] states “selecting an implant model from a plurality of implant models by interacting with the graphical user interface”; par. [0067] states “The memory 148 may be configured to access, load, edit and/or store instances of one or more bone models 138, implant models 140 and/or surgical plans 142 in response to one or more commands from the data module 150”; par. [0094] and [0096] state picking a second implant model 440 accordingly to a different bone model).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing of the claimed invention, to have utilized the teaching of picking one first model from the set of models, and selecting, based on the user feedback, at least one second model from the set of models that is to be applied on second patient image data in the invention of Roh, as taught by Metcalfe, to provide a more accurate planning system for orthopedic procedure by having multiple of different specific implant model for different cortical area of an associated bone.
Regarding claim 18, Roh and Metcalfe disclose the invention substantially as described in the 103 rejection, furthermore, Roh shows selecting the at least one first model based on at least one first historical data item associated with the user (see par. [0054], [0055], [0118], [0139]) and Metcalfe teaches indicative of at least one third model of the set of models; and generating at least one second historical data item associated with the user and indicative of the at least one second model (see par. [0006], [0007], [0067], [0094], [0096], [0099], [0100]). Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing of the claimed invention, to have utilized the teaching of indicative of at least one third model of the set of models; and generating at least one second historical data item associated with the user and indicative of the at least one second model in the invention of Roh, as taught by Metcalfe, to provide a more accurate planning system for orthopedic procedure by having multiple of different specific implant model for different cortical area of an associated bone.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHAHDEEP MOHAMMED whose telephone number is (571)270-3134. The examiner can normally be reached Monday to Friday, 9am to 5pm.
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/SHAHDEEP MOHAMMED/Primary Examiner, Art Unit 3797