Prosecution Insights
Last updated: April 19, 2026
Application No. 18/611,256

Lamella End-Pointing Via Graph-Weighted Neural Networks

Non-Final OA §101§102
Filed
Mar 20, 2024
Examiner
CHU, RANDOLPH I
Art Unit
2667
Tech Center
2600 — Communications
Assignee
Fei Company
OA Round
1 (Non-Final)
80%
Grant Probability
Favorable
1-2
OA Rounds
3y 1m
To Grant
86%
With Interview

Examiner Intelligence

Grants 80% — above average
80%
Career Allow Rate
634 granted / 791 resolved
+18.2% vs TC avg
Moderate +6% lift
Without
With
+5.9%
Interview Lift
resolved cases with interview
Typical timeline
3y 1m
Avg Prosecution
36 currently pending
Career history
827
Total Applications
across all art units

Statute-Specific Performance

§101
17.6%
-22.4% vs TC avg
§103
39.1%
-0.9% vs TC avg
§102
27.8%
-12.2% vs TC avg
§112
9.7%
-30.3% vs TC avg
Black line = Tech Center average estimate • Based on career data from 791 resolved cases

Office Action

§101 §102
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 . DETAILED ACTION 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, 2, 8-10 and 16-17 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The limitations, under their broadest reasonable interpretation, cover mental process (concept performed in a human mind, including as observation, evaluation, judgment, opinion). The claims recite a method of generating cost estimates for a vehicle repair and repainting using an image. This judicial exception is not integrated into a practical application because the steps do not add meaningful limitations to be considered specifically applied to a particular technological problem to be solved. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the steps of the claimed invention can be done mentally and no additional features in the claims would preclude them from being performed as such. According to the USPTO guidelines, a claim is directed to non-statutory subject matter if: STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or STEP 2: the claim recites a judicial exception, e.g., an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis: STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon? STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? Using the two-step inquiry, it is clear that claims directed to an abstract idea as shown below: STEP 1: Do the claims fall within one of the statutory categories? YES. Claim 1 is directed to a system, i.e., a machine, claim 9 is directed to a method, i.e., process. and claim 17 is directed to a CRM, i.e., manufacture STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea? YES, the claims are directed toward a mental process (i.e., abstract idea). With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas: Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations; Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion). The method in claim 1 comprise a mental process that can be practicably performed in the human mind therefore, an abstract idea. Claim 1, 9 and 17 recites: generates a classification label for the cutface, wherein the classification label indicates to which one of a plurality of defined classes the cutface belongs (a human can classifies and label by looking at the image) as a mental process as an abstract idea); Claim 2 and 10 recites: in response to the classification label indicating that the cutface does not belong to a target class of the plurality of defined classes, instructs the scientific instrument to incrementally mill the cutface of the lamella. (a human can instruct machine based on classification result.) as a mental process as an abstract idea); and These limitations, as drafted, is a simple process that, under their broadest reasonable interpretation, covers performance of the limitations in the mind or by a human. The Examiner notes that under MPEP 2106.04(a)(2)(III), the courts consider a mental process (thinking) that “can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same). The courts do not distinguish between mental processes that are performed entirely in the human mind and mental processes that require a human to use a physical aid (e.g., pen and paper or a slide rule) to perform the claim limitation. See, e.g., Benson, 409 U.S. at 67, 65, 175 USPQ at 674-75, 674 (noting that the claimed "conversion of [binary-coded decimal] numerals to pure binary numerals can be done mentally," i.e., "as a person would do it by head and hand."); Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1139, 120 USPQ2d 1473, 1474 (Fed. Cir. 2016) (holding that claims to a mental process of "translating a functional description of a logic circuit into a hardware component description of the logic circuit" are directed to an abstract idea, because the claims "read on an individual performing the claimed steps mentally or with pencil and paper"). Nor do the courts distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer. As the Federal Circuit has explained, "[c]ourts have examined claims that required the use of a computer and still found that the underlying, patent-ineligible invention could be performed via pen and paper or in a person’s mind." Versata Dev. Group v. SAP Am., Inc., 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015). See also Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1318, 120 USPQ2d 1353, 1360 (Fed. Cir. 2016) (‘‘[W]ith the exception of generic computer-implemented steps, there is nothing in the claims themselves that foreclose them from being performed by a human, mentally or with pen and paper.’’); Mortgage Grader, Inc. v. First Choice Loan Servs. Inc., 811 F.3d 1314, 1324, 117 USPQ2d 1693, 1699 (Fed. Cir. 2016) (holding that computer-implemented method for "anonymous loan shopping" was an abstract idea because it could be "performed by humans without a computer"). Because both product and process claims may recite a "mental process", the phrase "mental processes" should be understood as referring to the type of abstract idea, and not to the statutory category of the claim. The courts have identified numerous product claims as reciting mental process-type abstract ideas, for instance the product claims to computer systems and computer-readable media in Versata Dev. Group. v. SAP Am., Inc., 793 F.3d 1306, 115 USPQ2d 1681 (Fed. Cir. 2015). As such, a person could perform classify image content and instruct machine either mentally or using a pen and paper. The mere nominal recitation that the various steps are being executed by one or more hardware processors (e.g. processing unit) does not take the limitations out of the mental process grouping. Thus, the claims recite a mental process. If a claim limitation, under its broadest reasonable interpretation, covers performance of a mental step which could be performed with a simple tool such as a pen and paper, then it falls within the “mental steps” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? NO, the claims do not recite additional elements that integrate the judicial exception into a practical application. With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application: an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field; an additional element that applies or uses a judicial exception to affect a particular treatment or prophylaxis for a disease or medical condition; an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim; an additional element effects a transformation or reduction of a particular article to a different state or thing; and an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application: an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea; an additional element adds insignificant extra-solution activity to the judicial exception; and an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use. Claims 1, 2, 8-10 and 16-17 do not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application. Claim 1 and 17 recites: a processor that executes computer-executable components stored in a non-transitory computer-readable memory, wherein the computer-executable components comprise , an access component and a model component (instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea). claims 1, 9 and 17 recite: an access component that accesses an image captured by a scientific instrument, wherein the image depicts a cutface of a lamella (adding insignificant extra-solution activity to the judicial exception, e.g., mere data gathering in conjunction with a law of nature or abstract idea); claims 1, 9 and 17 recite: a graph-weighted neural network the one or more trained machine learning models represent no more than mere instructions to apply the judicial exception on a computer OR merely uses the computer as a tool to perform an abstract idea. See MPEP 2106.05(f)). The “one or more machine learning models” which appears as recited in the claims further stands in to automate a human mental process using a generic machine learning models that has not been improved by the applicant. These limitations are recited at a high level of generality (i.e. as a general action or change being taken based on the results of the acquiring step) and amounts to mere post solution actions, which is a form of insignificant extra-solution activity. Further, the claims are claimed generically and are operating in their ordinary capacity such that they do not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. Accordingly, even in combination, these 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. STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, that examiners should continue to consider whether an additional element or combination of elements: adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present. With regard to (2b) the Guidance provided the following examples of limitations that may be enough to qualify as “significantly more" when recited in a claim with a judicial exception: Improvement to another technology or technical field Improvement to functioning of computer itself and/or applying the judicial exception with, or by use of, a particular machine Effecting a transformation or reduction of a particular article to a different state or thing. Adding a specific limitation other that what is well understood, routine and conventional in the field, or adding unconventional steps that confine the claim to a particular useful application Meaningful limitation beyond generally linking the use of an abstract idea to a particular technological environment. The Guidance further set forth limitations that were found not to be enough to qualify as “significantly more” when recited in a claim with a judicial exception include: Adding words to “apply it” (or an equivalent) with the judicial exception or mere instructions to implement abstract ideas on a computer Simply appending well-understood, routine and conventional activities previously known to the industry specified at a high level of generality to the judicial exception, e.g. a claim to an abstract idea requiring no more than a generic Computer to perform generic computer functions that are well -understood, routine and conventional activities previously known to the industry. Adding insignificant extra-solution activity to the judicial exception, e.g. mere data gathering in conjunction with a law of nature or abstract idea Generally linking the use of the judicial exception to a particular technological environment or field of use. Claims 1, 2, 8-10 and 16-17 do not recite any additional elements that are not well-understood, routine or conventional. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The above identified additional computer components, using instructions to apply the judicial exception, are merely generic computer components that are well-known, routine, and conventional as is evidenced by Bancorp Services v. Sun Life (Fed. Cir. 2012) and Alice Corp. v. CLS Bank (2014). claims 1, 9 and 17 recite: an access component that accesses an image captured by a scientific instrument, wherein the image depicts a cutface of a lamella (adding insignificant extra-solution activity to the judicial exception, e.g., mere data gathering in conjunction with a law of nature or abstract idea); claims 1, 9 and 17 recite: a graph-weighted neural network the one or more trained machine learning models represent no more than mere instructions to apply the judicial exception on a computer OR merely uses the computer as a tool to perform an abstract idea. See MPEP 2106.05(f)). The “a graph-weighted neural network” which appears as recited in the claims further stands in to automate a human mental process using a generic machine learning models that has not been improved by the applicant. The “a graph-weighted neural network” is further routine, well- understood and conventional by the virtue of the factual evidence of the record as follows: Paragraph [0083] of 2023/ 0154101 discloses “At least one technical advantage of the disclosed techniques relative to the prior art is the disclosed techniques can be used to generate photorealistic images of objects, such as images of heads that include non-skin regions in addition to skin regions. In particular, the disclosed machine learning model can generate images of multiple different heads from various viewpoints, while requiring less data to train than is required by conventional machine learning models that generate images of heads. In addition, the disclosed machine learning model can be adapted to generate images of a new target head (or other object) by fitting the machine learning model to one or more images of the new target head (or other object). These technical advantages represent one or more technological improvements over prior art approaches”. Paragraph [0033] of 2023/ 0014490 discloses “The endoscope 100 shown in FIG. 1 has a visualization element, implemented as a charge-coupled device (“CCD”) 101, at a forward end of the endoscope 100. The CCD 101 is connected to an endoscope system 102 that may include a monitor 104. Alternatively, CCD 101 may be replaced by any other suitable visualization element. The endoscope system 102 may be configured with artificial-intelligence-based image analysis functionality, such as a conventional machine learning model 103 that has been trained based on images of natural (non-mechanically-enhanced) tissue. Once a machine learning model that has been trained on images of mechanically-enhanced tissue is available, such as the machine learning model 818 trained using the training processes described herein, the model 818 may be used by the endoscope system 102 during endoscopy procedures. Paragraph [0030] of 2021/ 0201474 discloses “In a typical manufacturing environment, a component manufacturer needs to be able to identify defective components, including components having various abnormalities such as cracks, dents, foreign material, etc. An example manufactured component is shown in FIG. 10. Referring to FIG. 10, sample images illustrate a representative component (e.g., a pinion gear) that needs to be checked for defects, wherein an acceptable “good” flank surface of the sample component is shown and a “defective” flank surface with a large pit in the sample component is shown. In some cases, conventional component manufacturers use trained machine learning models to assist in the detection of these component defects. However, these machine learning models are typically trained with actual images of defective physical components. The difficulty in using the conventional approach of collecting actual images of defective physical components for use as training data is that it takes a long time to collect a sufficiently large set of images of defective components that represents the variety of component defects and the variability in the sizes, orientations, and locations of the defects on the components. As a result, the conventional machine learning models are not sufficiently trained with a robust set of defective component images, which results in an inefficient trained machine learning model”. Thus, since claims 1, 9 and 17 are: (a) directed toward an abstract idea, (b) do not recite additional elements that integrate the judicial exception into a practical application, and (c) do not recite additional elements that amount to significantly more than the judicial exception, claims 1, 9 and 17 are not eligible subject matter under 35 U.S.C 101. Similar analysis is made for the dependent claims 2, 8, 10 and 16 and the dependent claims are similarly identified as: being directed towards an abstract idea, not reciting additional elements that integrate the judicial exception into a practical application, and not reciting additional elements that amount to significantly more than the judicial exception. 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. Claims 1, 9 and 17 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Sun et al. (CN 113592008). With respect to claim 1, Sun et al. teach a processor that executes computer-executable components stored in a non-transitory computer-readable memory, wherein the computer-executable components comprise ( page 6, An electronic device, comprising a processor and a memory for storing a computer program capable of running on the processor;): an access component that accesses an image captured by a scientific instrument, wherein the image depicts a cut face of a lamella (page 2, extracting the image sample feature (small sample image)); and a model component that generates, via execution of a graph-weighted neural network, a classification label for the cut face, wherein the classification label indicates to which one of a plurality of defined classes the cut face belongs (page 2-3, small sample image classification based on graph neural network mechanism of self-encoder that uses weight matrix to calculate similarity score). With respect to claim 9, please refer to rejection for claim 1. With respect to claim 17, please refer to rejection for claim 1. Allowable Subject Matter 1. Claims 3-8, 11-15 and 18-20 are objected to as being dependent upon a rejected base claim, but would be allowable of rewritten in independent form including all of the limitations of the base claim and any intervening claims. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to Randolph Chu whose telephone number is 571-270-1145. The examiner can normally be reached on Monday to Thursday from 7:30 am - 5 pm. 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. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). /RANDOLPH I CHU/ Primary Examiner, Art Unit 2667
Read full office action

Prosecution Timeline

Mar 20, 2024
Application Filed
Jan 24, 2026
Non-Final Rejection — §101, §102
Apr 14, 2026
Interview Requested

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
80%
Grant Probability
86%
With Interview (+5.9%)
3y 1m
Median Time to Grant
Low
PTA Risk
Based on 791 resolved cases by this examiner. Grant probability derived from career allow rate.

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