DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more.
Claim 1 recites:
A system comprising:
a memory configured to store instructions; and
one or more processors configured to execute the instructions to:
receive a radiology report including unstructured natural language text corresponding to a finding of a radiologist with respect to a region of interest of a subject;
generate, using a first artificial intelligence (AI) model, structured data in a predetermined format including a set of predetermined fields and a set of corresponding text values that are extracted from the radiology report and that correspond to the set of predetermined fields by inputting the radiology report into the first Al model that is configured to extract the set of corresponding text values;
select, using the first Al model, a medical image dataset of the subject corresponding to the radiology report from among a plurality of medical image datasets of the subject stored in a medical image database by inputting the structured data and respective metadata of the plurality of medical image datasets into the first Al model that is configured to match the text values with the respective metadata;
segment, using a second Al model, a set of regions of each medical image of the medical image dataset by inputting each medical image of the medical image dataset into the second Al model that is configured to segment the set of regions of each medical image;
label, using the second Al model, the set of regions of each medical image of the medical image dataset by inputting each medical image of the medical image dataset into the second Al model that is configured to label the set of regions of each medical image;
select, using the first Al model, a medical image of the medical image dataset that depicts the region of interest of the subject by inputting the structured data and the labelled and segmented set of regions into the first Al model that is configured to match the text values with the labelled and segmented set of regions; and
perform an action based on selecting the medical image that depicts the region of interest of the subject.
Step 1:
The claim as a whole falls within at least one statutory category, i.e. a process, machine, manufacture, or composition of matter.
Step 2A Prong One:
The highlighted portion, as drafted, is a process that, under its broadest reasonable interpretation, falls under “Certain methods of organizing human activity” because the steps of reading a patient’s image and performing an action based thereon are traditionally performed by a physician when treating a patient, i.e. managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions). MPEP 2106.04(a)(2)(II)
The highlighted portion, as drafted, is a process that, under its broadest reasonable interpretation, falls under “Mental processes”.
But for a generic computer recited with a high level of generality in a post hoc manner to implement the abstract idea, the steps of processing data may be performed in the human mind either mentally or with pen and paper.
Accordingly, these limitations have been found to be directed towards concepts performed in the human mind (including an observation, evaluation, judgment, opinion). MPEP 2106.04(a)(2)(III)
The different categories of abstract ideas are being considered together as one single abstract idea. MPEP 2106.04(II)(B)
Dependent claim(s) recite(s) additional subject matter which further narrows or defines the abstract idea embodied in the claims (such as claim(s) 3-6 reciting limitations further defining the abstract idea, which may be performed in the mind but for recitation of generic computer components, and/or may be a method of managing relationship or interactions between people).
Step 2A Prong Two:
This judicial exception is not integrated into a practical application. In particular, the claim recites the following additional element(s), if any:
a memory configured to store instructions; and
one or more processors configured to execute the instructions to:
receive a radiology report including unstructured natural language text corresponding to a finding of a radiologist with respect to a region of interest of a subject;
using a first artificial intelligence (AI) model by inputting the radiology report into the first Al model that is configured to extract the set of corresponding text values;
using the first Al model by inputting the structured data and respective metadata of the plurality of medical image datasets into the first Al model that is configured to match the text values with the respective metadata;
segment, using a second Al model, a set of regions of each medical image of the medical image dataset by inputting each medical image of the medical image dataset into the second Al model that is configured to segment the set of regions of each medical image;
using the second Al model by inputting each medical image of the medical image dataset into the second Al model that is configured to label the set of regions of each medical image;
using the first Al model by inputting the structured data and the labelled and segmented set of regions into the first Al model that is configured to match the text values with the labelled and segmented set of regions.
The additional element(s) do(es) not integrate the abstract idea into a practical application, other than the abstract idea per se.
Regarding the memory, the Specification as originally filed discloses generic memory (page 7 paragraph 0027).
Regarding the processor, the Specification as originally filed discloses a generic computer (page 7 paragraph 0025).
Regarding the use of AI models, these limitations amount to invoking a generic computer to implement the abstract idea.
Accordingly, these limitation amount(s) to mere instructions to apply an exception (invoking computers as a tool to perform the abstract idea). MPEP 2106.05(f))
Regarding the step of receiving a radiology report and segmenting an image, this limitation merely add(s) insignificant extra-solution activity to the abstract idea (mere data gathering). MPEP 2106.05(g))
Dependent claim(s) recite(s) additional subject matter which amount to limitation(s) consistent with the additional element(s) in the independent claims (such as claim(s) 2 reciting displaying data on a user interface, claim(s) 3 reciting storing data in a database, claim(s) 7 reciting generating an AI prompt, additional limitation(s) which add(s) insignificant extra-solution activity to 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 and do not impose a meaningful limit to integrate the abstract idea into a practical application.
Accordingly, the additional elements do not integrate the judicial exception into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Accordingly, the claim recites an abstract idea.
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. 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 an exception, add insignificant extra-solution activity to the abstract idea, and/or generally link the abstract idea to a particular technological environment or field of use.
The additional elements, as discussed above and incorporated herein, amount to no more than mere instructions to apply an exception, add insignificant extra-solution activity to the abstract idea, and/or generally link the abstract idea to a particular technological environment or field of use, as discussed above and incorporated herein.
Mere instructions to apply an exception, insignificant extra-solution activity, and linking to a particular technological environment using a generic computer component cannot provide an inventive concept.
Regarding the step of receiving a radiology report, this limitation amount(s) to element(s) that have been recognized as well-understood, routine, and conventional (WURC) activity in particular fields (e.g., receiving or transmitting data over a network, Symantec, MPEP 2106.05(d)(II)(i)). MPEP 2106.05(d)(II)(ii))
Regarding the step of segmenting an image, Rao (20030120134) discloses that image segmentation amounts to element(s) that have been recognized as well-understood, routine, and conventional (WURC) activity in particular fields (page 4 paragraph 0041).
Dependent claims recite additional subject matter which amount to limitations consistent with the additional elements in the independent claims (such as claim(s) claim(s) 2 reciting displaying data on a user interface, Knoplioch (20200311912) discloses displaying data in a manner that is WURC (page 1 paragraph 0003); claim(s) 3 reciting storing data in a database, e.g., electronic recordkeeping, Alice Corp., MPEP 2106.05(d)(II)(iii); e.g., storing and retrieving information in memory, Versata Dev. Group, MPEP 2106.05(d)(II)(iv);; claim 7 reciting an AI prompt, Singh (20240296316) disclosing that an AI prompt is WURC (page 4 paragraph 0040)). MPEP 2106.05(d)(II)(ii))
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.
The claim is not patent eligible.
Claim(s) 8-20 recite(s) substantially similar limitations as those of claim(s) 1-7 above, and are therefore rejected for substantially similar rationale as applied above, and incorporated herein.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(1) and (a)(2) as being anticipated by Chang (20230343454).
Claim 1: Chang discloses:
A system (Title illustrating a system) comprising:
a memory configured to store instructions (page 16 paragraph 0168 illustrating a memory containing software thereon); and
one or more processors configured to execute the instructions (page 16 paragraph 0168 illustrating a processor) to:
receive a radiology report including unstructured natural language text corresponding to a finding of a radiologist with respect to a region of interest of a subject (page 5 paragraph 0055 illustrating a radiology report with radiologist annotated text regarding findings [considered to be a “region of interest”]);
generate, using a first artificial intelligence (AI) model, structured data in a predetermined format including a set of predetermined fields and a set of corresponding text values that are extracted from the radiology report and that correspond to the set of predetermined fields by inputting the radiology report into the first Al model that is configured to extract the set of corresponding text values (Figure 2A illustrating processing the natural language of the radiology report to generate a plurality of patient data values with an AI model);
select, using the first Al model, a medical image dataset of the subject corresponding to the radiology report from among a plurality of medical image datasets of the subject stored in a medical image database by inputting the structured data and respective metadata of the plurality of medical image datasets into the first Al model that is configured to match the text values with the respective metadata (page 6 paragraph 0060 illustrating using AI to select the patient’s images);
segment, using a second Al model, a set of regions of each medical image of the medical image dataset by inputting each medical image of the medical image dataset into the second Al model that is configured to segment the set of regions of each medical image (page 6 paragraph 0060 illustrating processing the image to classify the image [considered to be a form of “segment”]);
label, using the second Al model, the set of regions of each medical image of the medical image dataset by inputting each medical image of the medical image dataset into the second Al model that is configured to label the set of regions of each medical image (page 6 paragraph 0060 illustrating generating text findings of the image);
select, using the first Al model, a medical image of the medical image dataset that depicts the region of interest of the subject by inputting the structured data and the labelled and segmented set of regions into the first Al model that is configured to match the text values with the labelled and segmented set of regions (page 6 paragraph 0060 illustrating generating annotated patient images based on the AI’s findings); and
perform an action based on selecting the medical image that depicts the region of interest of the subject (page 6 paragraph 0060 illustrating performing a follow up action as deemed necessary by the AI).
Claim 2: Chang discloses:
The system of claim 1, as discussed above and incorporated herein.
Chang further discloses:
wherein the performing the action comprises displaying the radiology report and the medical image that depicts the region of interest of the subject via a user interface of a user device (page 16-17 claim 4 illustrating displaying the image’s classification for the radiologist’s review).
Claim 3: Chang discloses:
The system of claim 1, as discussed above and incorporated herein.
Chang further discloses:
wherein the performing the action comprises generating a data entry that correlates the radiology report with the medical image that depicts the region of interest of the subject, and storing the data entry in a database (page 6 paragraph 0060 illustrating storing the patient’s annotated record into the computerized patient records database).
Claim 4: Chang discloses:
The system of claim 1, as discussed above and incorporated herein.
Chang further discloses:
wherein the selecting the medical image dataset of the subject comprises selecting the medical image dataset based on a text value of an imaging modality field included in the structured data (Figure 2A illustrating selecting the patient’s image based on the AI’s processing of the text annotations).
Claim 5: Chang discloses:
The system of claim 1, as discussed above and incorporated herein.
Chang further discloses:
wherein the selecting the medical image dataset of the subject comprises selecting the medical image dataset based on a text value of a date field included in the structured data (page 11 paragraph 0119 illustrating selecting the image based on the value of a date).
Claim 6: Chang discloses:
The system of claim 1, as discussed above and incorporated herein.
Chang further discloses:
wherein the selecting the medical image of the medical image dataset that depicts the region of interest comprises selecting the medical image of the medical image dataset that depicts the region of interest based on a finding field included in the structured data and a label associated with the labelled and segmented set of regions (page 6 paragraph 0060 illustrating using AI to select the patient’s image based on the annotated findings found on the patient’s radiology report).
Claim 7: Chang discloses:
The system of claim 1, as discussed above and incorporated herein.
Chang further discloses:
wherein the selecting the medical image dataset of the subject comprises selecting the medical image dataset based on generating a prompt for the first AI model that identifies the plurality of medical image datasets (Figure 2A-D, page 1 paragraph 0008 illustrating prompts used to instruct the AI to perform the operations as discussed above, and incorporated herein).
Claim(s) 8-20 recite(s) substantially similar limitations as those of claim(s) 1-7 above, and are therefore rejected for substantially similar rationale as applied above, and incorporated herein.
Response to Arguments
In the Remarks filed on 08 April 2026, Applicant makes numerous arguments. Examiner will address these arguments in the order presented.
On page 12-13 Applicant argues that the claims are not directed towards Certain Methods of Human Activity.
While Applicant’s arguments have been carefully considered, they are not persuasive because Applicant does not state why the highlighted portions are not directed towards managing personal behavior/relationships/interactions between people.
Instead, Examiner maintains that processing a radiology report is traditionally performed by a radiologist when treating a patient.
On page 13-14 Applicant argues that the claims are not directed towards mental processes.
While Applicant’s arguments have been carefully considered, they are not persuasive because Applicant does not state why the highlighted portions cannot be practically performed in the human mind either mentally or with pen and paper.
Instead, Examiner maintains that the highlighted portions can be implemented in the human mind either mentally or with pen and paper, and specifically because the AI has been invoked with a high level of generality in a post hoc manner to implement the abstract idea (the AI limitations have been found to be directed towards additional elements, as discussed above and incorporated herein).
On page 15-17 Applicant argues that the claims provide technical improvement.
While Applicant’s arguments have been carefully considered, they are not persuasive because the portions cited by Applicant provide an improvement in the abstract idea, and do not amount to invoking AI with a high level of generality, as discussed above and incorporated herein.
Applicant’s arguments on page 17 merely rehash arguments previously addressed above, and incorporated herein.
Applicant’s arguments with respect to claim(s) 1 on page 18-19 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Based on the evidence presented above, Applicant’s arguments are not found persuasive.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Shinagawa (20170221204) discloses overlaying text onto an image (Figure 2) in a manner similar to those disclosed in the instant pending Specification as originally filed.
Liu (20170337329) discloses generating annotation for a medical image (Abstract) in a manner similar to those disclosed in the instant pending Specification as originally filed.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 extension fee 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 date of this final action.
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/T.N.N./ Examiner, Art Unit 3685
/KAMBIZ ABDI/Supervisory Patent Examiner, Art Unit 3685
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