DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Notice to Applicant
2. This communication is in response to the communication filed 7/23/2024. Claims 1-10, 12 and 16-17 are currently amended. Claims 1-20 are currently pending.
Claim Objections
3. Claim 1 is objected to because of the following informalities: the claim recites medical “imagining” instead of medical imaging. This appears to be a typographical error. Appropriate correction is required.
Claim Rejections - 35 USC § 101
4. 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.
4.1. Claims 1-20 are rejected under 35 U.S.C. § 101 because while the claims (1) are to a statutory category (i.e., process, machine, manufacture or composition of matter, the claims (2A1) recite an abstract idea (i.e., a law of nature, a natural phenomenon); (2A2) do not recite additional elements that integrate the abstract idea into a practical application; and (2B) are not directed to significantly more than the abstract idea itself.
In regard to (1), the claims are to a statutory category (i.e., statutory categories including a process, machine, manufacture or composition of matter). In particular, independent claims 1, 10 and 16, and their respective dependent claims are directed, in part, to methods for optimizing protocols for medical imaging scanners to scan a subject.
In regard to (2A1), the claims, as a whole, recite and are directed to an abstract idea because the claims include one or more limitations that correspond to an abstract idea including mental processes because the claims, except for certain limitations (* identified below in bold), under the broadest reasonable interpretation, can be reasonably and practically performed in the human mind and/or with pen and paper using observation, evaluation, judgment and/or opinion. That is, other than reciting the certain additional elements, nothing in the claims precludes the limitations from being practically performed in the mind and/or with pen and paper.
For example, a person can perform the steps of independent claims 1, 10 and 16 in their mind and/or with pen and paper. For example, a person can perform steps of claim 1, that is, receive a planned protocol, receive information specific to hardware and software of the medical imaging scanner, generate suggested protocol parameters to optimize the planned protocol based on the planned protocol and the information specific to the hardware and software of the medical imaging scanner, outputting an optimized protocol for the planned protocol in their mind and/or with pen and paper using observation, evaluation, judgment and/or opinion. The dependent claims include all of the limitations of their respective independent claims and thus are directed to the same abstract idea identified for the independent claims but further describe the elements and/or recite field of use limitations.
CLAIM 1:
A computer-implemented method for optimizing protocols for medical imaging scanners, comprising:
receiving, at a processing system comprising one or more processors, a planned protocol from an organization for a medical imaging scanner;
receiving, at the processing system, information specific to hardware and software of the medical imaging scanner;
utilizing, via the processing system, a vendor-neutral artificial intelligence-based algorithm to generate suggested protocol parameters to optimize the planned protocol based at least on the planned protocol and the information specific to the hardware and software of the medical imaging scanner;
outputting, via the processing system, from the artificial intelligence-based algorithm an optimized protocol for the planned protocol based on one or more of the suggested protocol parameters;
modifying, via the processing system, settings of the medical imaging scanner when the optimized protocol is utilized for a scan of a subject with the medical imaging scanner; and
executing, via the processing system, a scan of the subject with the medical imaging scanner utilizing the optimized protocol.
CLAIM 2:
The computer-implemented method of claim 1, further comprising:
receiving, at the processing system, user input of desired optimization criteria; and
utilizing, via the processing system, the vendor-neutral artificial intelligence-based algorithm to generate suggested protocol parameters to optimize the planned protocol based on the planned protocol, the desired optimization criteria, and the information specific to the hardware and the software of the medical imaging scanner.
CLAIM 3:
The computer-implemented method of claim 2, further comprising:
receiving, at the processing system, additional user input of acceptance of one or more of the suggested protocol parameters and/or rejection of one or more of the suggested protocol parameters; and
outputting, via the processing system, from the vendor-neutral artificial intelligence-based algorithm the optimized protocol for the planned protocol based on the one or more of the suggested protocol parameters accepted via the additional user input.
CLAIM 4
The computer-implemented method of claim 3, further comprising training, via the processing system, the vendor-neutral artificial intelligence-based algorithm based on the one or more of the suggested protocol parameters accepted via the additional user input.
CLAIM 5:
The computer-implemented method of claim 1, further comprising:
receiving, at the processing system, a plurality of planned protocols from the organization for the medical imaging scanner;
receiving, at the processing system, respective scan outcomes for each planned protocol of the plurality of planned protocols;
utilizing, via the processing system, the vendor-neutral artificial intelligence-based algorithm to group the plurality of planned protocols into different protocol sets based on the respective scan outcomes;
outputting, via the processing system, from the vendor-neutral artificial intelligence-based algorithm the different protocol sets;
receiving, via the processing system, user input of acceptance of one or more planned protocols within each protocol set of the different protocol sets and/or rejection of one or more of the planned protocols within each protocol set of the different protocol sets; and
outputting, via the processing system, from the vendor-neutral artificial intelligence-based algorithm optimized protocol sets for the plurality of planned protocols based on the one or more planned protocols within each protocol set of the different protocol sets accepted via the user input.
CLAIM 6:
The computer-implemented method of claim 1, further comprising:
utilizing, via the processing system, the vendor-neutral artificial intelligence-based algorithm to apply changes to all other planned protocols from the organization for the medical imaging scanner based on respective changes to the planned protocol to generate the optimized protocol;
outputting, via the processing system, from the vendor-neutral artificial intelligence-based algorithm the other planned protocols with applied changes;
receiving, via the processing system, user input of acceptance of one or more of the other planned protocols with the applied changes and/or rejection of one or more of the other planned protocols with the applied changes; and
outputting, via the processing system, from the vendor-neutral artificial intelligence-based algorithm respective improved protocols for the other planned protocols where the applied changes are accepted via the user input.
CLAIM 7:
The computer-implemented method of claim 1, further comprising:
receiving, at the processing system, a plurality of performed protocols for the planned protocol, wherein each performed protocol of the plurality of performed protocols was performed during a respective scan with respective protocol parameters;
determining, via the processing system, for each performed protocol of the plurality of performed protocols respective differences in the respective protocol parameters from protocol parameters of the planned protocol;
separating, via the processing system, the respective differences in the respective protocol parameters into different categories; and
utilizing, via the processing system, the vendor-neutral artificial intelligence-based algorithm to generate suggested protocol parameters to optimize the planned protocol based at least on the plurality of performed protocols and the different categories.
CLAIM 8:
The computer-implemented method of claim 1, further comprising:
receiving, at the processing system, a plurality of performed protocols for a plurality of planned protocols from the organization for the medical imaging scanner, wherein each performed protocol of the plurality of performed protocols was performed during a respective scan with respective protocol parameters;
determining, via the processing system, for each performed protocol of the plurality of performed protocols for each respective planned protocol of the plurality of planned protocols respective differences in the respective protocol parameters from protocol parameters of the respective planned protocols;
separating, via the processing system, the respective differences in the respective parameters into different categories for the plurality of performed protocols for each respective planned protocol of the plurality of planned protocols;
utilizing, via the processing system, the vendor-neutral artificial intelligence-based algorithm to generate suggested protocol parameters to optimize the plurality of planned protocols based at least on the plurality of performed protocols and the different categories for the plurality of planned protocols; and
outputting, via the processing system, from the vendor-neutral artificial intelligence-based algorithm respective planned protocols that can be improved with each suggested protocol parameter of the suggested protocol parameters.
CLAIM 9:
The computer-implemented method of claim 8, further comprising: receiving, at the processing system, user input of user preferences for the respective scan; and
utilizing, via the processing system, the vendor-neutral artificial intelligence-based algorithm to generate suggested protocol parameters to optimize the plurality of planned protocols based on the user preferences, the plurality of performed protocols and the different categories for the plurality of planned protocols.
CLAIM 10:
A computer-implemented method for optimizing protocols for medical imaging scanners, comprising:
receiving, at a processing system comprising one or more processors, clinical requirements for a scan using a medical imaging scanner of an organization;
receiving, at the processing system, information specific to hardware and software of the medical imaging scanner;
receiving, at the processing system, user input of one or more desired outcomes for the scan; and
utilizing, via the processing system, a generative artificial intelligence-based model to generate a protocol for performing the scan using the medical imaging scanner based on the clinical requirements and the one or more desired outcomes for the scan, wherein the generative artificial intelligence-based model comprises a radiology large language model (LLM).
CLAIM 11:
The computer-implemented method of claim 10, further comprising:
receiving, at the processing system, additional user input additional one or more desired outcomes for the scan;
receiving, at the processing system, context from the generative artificial intelligence-based model; and
utilizing, via the processing system, the generative artificial intelligence-based model to update the protocol to generate an updated protocol based on the context and the additional user input.
CLAIM 12:
The computer-implemented method of claim 10, wherein the radiology large language model specific is to the organization.
CLAIM 13:
The computer-implemented method of claim 12, wherein the radiology large language model is fine-tuned based on protocols from the organization for the medical imaging scanner.
CLAIM 14:
The computer-implemented method of claim 13, wherein organization specific fine-tuning of the radiology large language model is isolated from external exposure.
CLAIM 15:
The computer-implemented method of claim 14, wherein, prior to the organization specific fine-tuning, the generative artificial intelligence-based model is pre-trained based on original equipment manufacturer data for different manufacturers and different models of medical imaging scanners similar to the medical imaging scanner and the original equipment manufacturer data for the medical imaging scanner.
CLAIM 16:
A computer-implemented method for optimizing protocols for medical imaging scanners, comprising:
receiving, at a processing system comprising one or more processors, existing planned protocols from an organization for performing a scan with a first medical imaging scanner;
receiving, at the processing system, information specific to hardware and software of the first medical imaging scanner;
receiving, at the processing system, additional information specific to hardware and software of a second medical imaging scanner different from the first medical imaging scanner, wherein the second medical imaging scanner is of a different manufacturer and/or a different model from the first medical imaging scanner;
receiving, at the processing system, user input of one or more desired outcomes for a respective scan with the second medical imaging scanner; and
utilizing, via the processing system, a generative artificial intelligence-based model to generate a protocol for performing the respective scan using the second medical imaging scanner based on the existing planned protocols and the one or more desired outcomes for the respective scan, wherein the generative artificial intelligence-based model comprises a radiology large language model.
CLAIM 17:
The computer-implemented method of claim 16, wherein the radiology large language model specific to the organization.
CLAIM 18:
The computer-implemented method of claim 17, wherein the radiology large language model is fine-tuned based on protocols from the organization for the first medical imaging scanner.
CLAIM 19:
The computer-implemented method of claim 18, wherein organization specific fine-tuning of the radiology large language model is isolated from external exposure.
CLAIM 20:
The computer-implemented method of claim 19, wherein, prior to the organization specific fine-tuning, the generative artificial intelligence-based model is pre-trained based on original equipment manufacturer data for different manufacturers and different models of medical imaging scanners similar to the first medical imaging scanner and the original equipment manufacturer data for the first medical imaging scanner.
* The limitations that are in bold are considered “additional elements” that are further analyzed below in subsequent steps of the 101 analysis. The limitations that are not in bold are abstract and/or can be reasonably and practically performed in the human mind and/or with pen paper.
In regard to (2A2), the claims do not recite additional elements that integrate the abstract idea into a practical application. The additional elements in the claims (i.e., * identified above in bold) do not integrate the abstract idea into a practical application because the additional elements merely add insignificant extra-solution activity to the abstract idea; merely link the use of the judicial exception to a particular technological environment or field of use; and/or simply append technologies and functions, specified at a high level of generality, to the abstract idea (i.e., the additional elements do not amount to more than a recitation of the words “apply it” (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer).
Here, the additional elements (e.g., computer, medical imaging scanners, processing system, one or more processors, artificial intelligence-based algorithm, etc.) are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the abstract idea using generic computer technologies. Moreover, the claims recite “computer-implemented,” “via the processing system”, “an artificial intelligence-based algorithm to”, etc. devoid of any meaningful technological improvement details and thus, further evidence the additional elements are merely being used to leverage generic technologies to automate what otherwise could be done manually. Accordingly, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Furthermore, the additional elements do not recite improvements to the functioning of a computer, or to any other technology or technical field—the additional elements merely recite general purpose computer technology; the additional elements do not recite applying or using a judicial exception to effect a particular treatment or prophylaxis for disease or medical condition—there is no actual administration of a particular treatment; the additional elements do not recite applying the judicial exception with, or by use of, a particular machine—the additional elements merely recite general purpose computer technology; the additional elements do not recite limitations effecting a transformation or reduction of a particular article to a different state or thing—the additional elements do not recite transformation such as a rubber mold process; the additional elements do not recite applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment—the additional elements merely leverage general purpose computer technology to link the abstract idea to a technological environment.
In regard to (2B), the claims, individually, as a whole and in combination with one another, do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements or combination of elements in the claims, other than the abstract idea per se, amount to no more than a recitation of (A) a generic computer structure(s) that serves to perform computer functions that serve to merely link the abstract idea to a particular technological environment (i.e., computers); and/or (B) functions that are well-understood, routine, and conventional activities previously known to the pertinent industry.
Here, as discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply the exception using generic computer technologies. Mere instructions to apply an exception using generic computer technologies cannot provide an inventive concept.
Moreover, paragraphs [0028]-[0029] of applicant's specification (US 2026/0018276) recites that the system/method is implemented using a computing system such as, a single computer, virtual machine, virtual container, host, server, laptop, and/or mobile device which are well-known general purpose or generic-type computers and/or technologies. The use of generic computer components recited at a high level of generality to process information through an unspecified processor/computer does not impose any meaningful limit on the computer implementation of the abstract idea. Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation.
Furthermore, the additional elements are merely well-known general purpose computers, components and/or technologies that receive, transmit, store, display, generate and otherwise process information which are akin to functions that courts consider well-understood, routine, and conventional activities previously known to the pertinent industry, such as, performing repetitive calculations; receiving or transmitting data over a network; electronic recordkeeping; retrieving and storing information in memory; and sorting information (See, for example, MPEP § 2106).
Therefore, the claims are not patent-eligible under 35 U.S.C. § 101.
Response to Arguments
5. Applicant's arguments filed 7/23/2026 have been fully considered but they are not persuasive. Applicant’s arguments will be addressed hereinbelow in the order in which they appear in the response filed 7/23/2026.
5.1. Applicant argues, on pages 9-16 of the response, that (1) claims 1, 19 and 16 do not fall into any of the enumerated subgroupings of abstract ideas; (2) evening if independent claims 1, 10 and 16 recite a judicial exception, the claims integrate the judicial exception into a practical application; and (3) independent claims 1, 10 and 16 recite an inventive concept.
In regard to (1), Examiner respectfully disagrees and submits that the claims are abstract and fall under the category of mental processes because nothing precludes a person from performing the steps of the claims in their mind and/or with pen and paper. For example, claim 1, under a broad and reasonable interpretation, can be reasonably and practically performed by a person in their mind and /or with pen and paper, that is, a person can receive a planned protocol, receive information specific to hardware and software of the medical imaging scanner, generate suggested protocol parameters to optimize the planned protocol based on the planned protocol and the information specific to the hardware and software of the medical imaging scanner, outputting an optimized protocol for the planned protocol in their mind and/or with pen and paper using observation, evaluation, judgment and/or opinion. Likewise, claim 10, under a broad and reasonable interpretation, can be reasonably and practically performed by a person in their mind and/or with pen and paper, that is, a person can receive clinical requirements for a scan, receive information specific to hardware and software of the medical imaging scanner, receive user input of one or more desired outcomes for the scan, and generate a protocol for performing the scan, in their mind and/or with pen and paper using observation, evaluation, judgment and/or opinion. Lastly, claim 16, under a broad and reasonable interpretation, can be reasonably and practically performed by a person in their mind and/or with pen and paper, that is, a person can receive existing planned protocols, receive information specific to hardware and software of the medical imaging scanner, receive additional information, receive user input, and generate a protocol for performing the respective scan in their mind and/or with pen and paper using observation, evaluation, judgment and/or opinion.
In regard to (2) and (3), the claims do not recite additional elements that integrate the abstract idea into a practical application. For example, the additional elements (e.g., computer, medical imaging scanners, processing system, one or more processors, artificial intelligence-based algorithm, etc.) are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the abstract idea using generic computer technologies; and use well-known technology to receive information (e.g., using a processing system to receive information, etc.). Moreover, the claims recite “computer-implemented,” “via the processing system”, “an artificial intelligence-based algorithm to”, etc. devoid of any meaningful technological improvement details (e.g., technological improvements to the artificial intelligence making it faster, more efficient, etc.) and thus, further evidence the additional elements are merely being used to leverage generic technologies to automate what otherwise could be done manually (e.g., a person can generate an optimized protocol and manually modify settings). In other words, the focus of applicant’s claims is not on an improvement in computers as tools, but on certain abstract ideas that use computers as tools. As such, it is respectfully submitted that the additional elements do not integrate the abstract idea into a practical application.
Conclusion
6. THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Michael Tomaszewski whose telephone number is (313)446-4863. The examiner can normally be reached M-F 5:30 am - 2:30 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Peter H Choi can be reached at (469) 295-9171. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MICHAEL TOMASZEWSKI/Primary Examiner, Art Unit 3681
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