DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This final office action is in response to the amendment filed 24 June 2026.
Claims 1-16 are pending. Claims 14-16 are newly added. Claims 1, 2, and 13 are independent claims.
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.
Claim 15 is 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.
With respect to claim 15, the term “clearly different from noise” in line 2 is a relative term which renders the claim indefinite. The term “clearly different from noise” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
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 1-13 remain rejected and claims 14-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
When considering subject matter eligibility under 35 USC 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter (Step 1; MPEP 2106.03). If the claim falls within one of the statutory categories, the second step in the analysis is to determine whether the claim is directed toward a judicial exception (Step 2A; MPEP 2106.04). This step is broken into two prongs.
The first prong (Step 2A, Prong 1) determines whether or not the claims recite a judicial exception (e.g., mathematical concepts, mental processes, certain methods of organizing human activity). If it is determined at Step 2A, Prong 1 that the claims recite a judicial exception, the analysis proceeds to the second prong (Step 2A, Prong 2; MPEP 2106.04). The second prong (Step 2A, Prong 2) determines whether the claims integrate the judicial exception into a practical application. If the claims do not integrate the judicial exception into a practical application, the analysis proceeds to determine whether the claim is a patent-eligible exception (Step 2B; MPEP 2106.05).
If an abstract idea is present int the claim, in order to recite statutory subject matter, any element or combination of elements in the claim must be sufficient to ensure that the claim integrates the judicial exception into a practical application or amounts to significantly more than the abstract idea itself (see: 2019 PEG).
Step 1:
According to Step 1 of the two Step analysis, claim 1 is are directed toward a system (machine). Claims 2-12 are directed toward a method (process). Therefore, each of these claims falls within one of the four statutory categories.
According to Step 1 of the two Step analysis, claim 13 is directed toward a computer program. A computer program fails to define a process, machine, manufacture, or composition of matter. For the purpose of examination under Step 2A, Prong 1; Step 2A, Prong 2; and Step 2B, the examiner will treat claim 13 as though it recites a computer program product (manufacture).
Claim 1:
Step 2A, Prong 1:
Following the determination that the claims fall within one of the statutory categories (Step 1), it must be determined if the claims recite a judicial exception (Step 2A, Prong 1). In this instance, the claims are determined to recite a judicial exception (abstract idea; mental process).
With respect to claim 1, the claim recites:
testing a quality of the image processing model… to make a quality statement on a quality of the image processing model from learned model parameter values of the image processing model (mental process; As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses an evaluation of the quality of a trained image processing model based upon testing)
Step 2A, Prong 2:
Accordingly, after determining that a claim recites a judicial exception in Step 2A Prong One, examiners should evaluate whether the claim as a whole integrates the recited judicial exception into a practical application of the exception in Step 2A Prong Two. A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception (MPEP 2106.04(d)).
The claims disclose the following additional elements:
a microscope for image capture
a computing device that is configured
a…program… wherein the… program is configured
These additional claim elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
The claims disclose the following additional elements:
train, using training data, an image processing model to calculate an image processing result from at least one microscope image
In this instance, training is recited at a high-level of generality with no detail of the training process and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B:
Based on the determination in Step 2A of the analysis that the claims are directed toward a judicial exception, in must be determined if any claims contain any element or combination of elements sufficient to ensure that the claims amount to significantly more than the judicial exception (Step 2B).
The claims disclose the following additional elements:
a microscope for image capture
a computing device that is configured
a…program… wherein the… program is configured
These additional claim elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
The claims disclose the following additional elements:
train, using training data, an image processing model to calculate an image processing result from at least one microscope image
In this instance, training is recited at a high-level of generality with no detail of the training process and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
In this instance, after considering all claim elements individually and as an ordered combination, it is determined that the claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 2:
Step 2A, Prong 1:
Following the determination that the claims fall within one of the statutory categories (Step 1), it must be determined if the claims recite a judicial exception (Step 2A, Prong 1). In this instance, the claims are determined to recite a judicial exception (abstract idea; mental process).
With respect to claim 2, the claim recites:
testing a quality of a… model configured to calculate an image processing result from at least one microscope image (mental process; As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses an evaluation of the quality of a trained image processing model based upon testing)
inputting learned model parameter values of the image processing model… to make a quality statement on a quality of the image processing model from input model parameter values (mental process; As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses an evaluation of the quality of a trained image processing model based upon testing)
calculate a quality statement regarding a quality of the image processing model based on the learned model parameter values (mental process; As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses an evaluation to calculate a quality statement)
Step 2A, Prong 2:
Accordingly, after determining that a claim recites a judicial exception in Step 2A Prong One, examiners should evaluate whether the claim as a whole integrates the recited judicial exception into a practical application of the exception in Step 2A Prong Two. A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception (MPEP 2106.04(d)).
The claims disclose the following additional elements:
A computer-implemented method
a quality testing program
using the quality testing program
These additional claim elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
The claims disclose the following additional elements:
a machine-learned image processing model
In this instance, training is recited at a high-level of generality with no detail of the training process and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B:
Based on the determination in Step 2A of the analysis that the claims are directed toward a judicial exception, in must be determined if any claims contain any element or combination of elements sufficient to ensure that the claims amount to significantly more than the judicial exception (Step 2B).
The claims disclose the following additional elements:
A computer-implemented method
a quality testing program
using the quality testing program
These additional claim elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
The claims disclose the following additional elements:
a machine-learned image processing model
In this instance, training is recited at a high-level of generality with no detail of the training process and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
In this instance, after considering all claim elements individually and as an ordered combination, it is determined that the claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 3:
With respect to dependent claim 3, the claim depends upon independent claim 2. The analysis of claim 2 is incorporated herein by reference.
Step 2A, Prong 1:
With respect to claim 3, the claim recites:
wherein for the calculation of the quality statement of a quality measure is derived from the learned model parameter values and compared with reference values (mental process; As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses an evaluation by comparing the learned model parameter values with reference values to calculate the quality measure)
Claim 4:
With respect to dependent claim 4, the claim depends upon independent claim 2. The analysis of claim 2 is incorporated herein by reference.
Step 2A, Prong 1:
With respect to claim 4, the claim recites:
wherein the quality testing… makes the quality statement based on evaluation criteria relating to the model parameter values, wherein the evaluation criteria relate to one or more of the following:
a randomness or entropy of a group of model parameter values
a similarity of a group of model parameter values to known or expected distributions
an energy filter weights of a convolutional layer
a presence of inactive filter masks in the image processing model with model parameter values that lie exclusively below a predetermined threshold
an invariability of model parameter values of activation functions over a plurality of training steps
a presence of structures in groups of model parameter values
a memorization of specific structures of training data in filter masks of the image processing model
a color distribution in filter masks of the image processing model (mental process; As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses an evaluation by comparing the learned model parameter values with various criteria to calculate the quality measure)
Step 2A, Prong 2:
Accordingly, after determining that a claim recites a judicial exception in Step 2A Prong One, examiners should evaluate whether the claim as a whole integrates the recited judicial exception into a practical application of the exception in Step 2A Prong Two. A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception (MPEP 2106.04(d)).
The claims disclose the following additional elements:
a quality testing program
These additional claim elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B:
Based on the determination in Step 2A of the analysis that the claims are directed toward a judicial exception, in must be determined if any claims contain any element or combination of elements sufficient to ensure that the claims amount to significantly more than the judicial exception (Step 2B).
The claims disclose the following additional elements:
a quality testing program
These additional claim elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
In this instance, after considering all claim elements individually and as an ordered combination, it is determined that the claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 5:
With respect to dependent claim 5, the claim depends upon dependent claim 4. The analysis of claim 4 is incorporated herein by reference.
Step 2A, Prong 2:
Accordingly, after determining that a claim recites a judicial exception in Step 2A Prong One, examiners should evaluate whether the claim as a whole integrates the recited judicial exception into a practical application of the exception in Step 2A Prong Two. A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception (MPEP 2106.04(d)).
The claims disclose the following additional elements:
wherein the quality testing program comprises a machine-learned model trained to make the quality statement based on one or more of the evaluation criteria
In this instance, training is recited at a high-level of generality with no detail of the training process and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B:
Based on the determination in Step 2A of the analysis that the claims are directed toward a judicial exception, in must be determined if any claims contain any element or combination of elements sufficient to ensure that the claims amount to significantly more than the judicial exception (Step 2B).
The claims disclose the following additional elements:
wherein the quality testing program comprises a machine-learned model trained to make the quality statement based on one or more of the evaluation criteria
In this instance, training is recited at a high-level of generality with no detail of the training process and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
In this instance, after considering all claim elements individually and as an ordered combination, it is determined that the claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 6:
With respect to dependent claim 6, the claim depends upon independent claim 2. The analysis of claim 2 is incorporated herein by reference.
Step 2A, Prong 1:
With respect to claim 6, the claim recites:
wherein the quality testing… evaluations groups of model parameter values together and additionally takes into account information regarding a model parameter position within the image processing model as well as contextual information in order to calculate the quality statement (mental process; As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses an evaluation by comparing the groups of model parameters and account information regarding model parameter position and contextual information to calculate the quality measure)
Step 2A, Prong 2:
Accordingly, after determining that a claim recites a judicial exception in Step 2A Prong One, examiners should evaluate whether the claim as a whole integrates the recited judicial exception into a practical application of the exception in Step 2A Prong Two. A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception (MPEP 2106.04(d)).
The claims disclose the following additional elements:
a quality testing program
These additional claim elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B:
Based on the determination in Step 2A of the analysis that the claims are directed toward a judicial exception, in must be determined if any claims contain any element or combination of elements sufficient to ensure that the claims amount to significantly more than the judicial exception (Step 2B).
The claims disclose the following additional elements:
a quality testing program
These additional claim elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
In this instance, after considering all claim elements individually and as an ordered combination, it is determined that the claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 7:
With respect to dependent claim 7, the claim depends upon independent claim 2. The analysis of claim 2 is incorporated herein by reference.
Step 2A, Prong 1:
With respect to claim 7, the claim recites:
wherein the quality testing… takes into account contextual information in addition to the model parameter values to calculate the quality statement, wherein the contextual information relates to one or more of the following:
initial values of model parameters of the image processing model at a beginning of training
an evolution of the model parameter values over a training
training data of the image processing model
a model architecture of the image processing model
information regarding an application for which microscope images were captured as training data of the image processing model
information regarding a microscope or microscope settings with which microscope images were captured as training data of the image processing model
a user identification
a specification of a sample type visible in microscope images of the training data of the image processing model (mental process; As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses an evaluation by comparing the groups of model parameters and contextual information to calculate the quality measure)
Step 2A, Prong 2:
Accordingly, after determining that a claim recites a judicial exception in Step 2A Prong One, examiners should evaluate whether the claim as a whole integrates the recited judicial exception into a practical application of the exception in Step 2A Prong Two. A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception (MPEP 2106.04(d)).
The claims disclose the following additional elements:
a quality testing program
These additional claim elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B:
Based on the determination in Step 2A of the analysis that the claims are directed toward a judicial exception, in must be determined if any claims contain any element or combination of elements sufficient to ensure that the claims amount to significantly more than the judicial exception (Step 2B).
The claims disclose the following additional elements:
a quality testing program
These additional claim elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
In this instance, after considering all claim elements individually and as an ordered combination, it is determined that the claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 8:
With respect to dependent claim 8, the claim depends upon independent claim 2. The analysis of claim 2 is incorporated herein by reference.
Step 2A, Prong 1:
With respect to claim 8, the claim recites:
wherein in cases where the quality statement confirms a usability of the image processing model: the image processing model calculates image processing results from microscope images or, subject to a supplemental verification of a model quality, the image processing model calculates image processing results from microscope images (mental process; As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses aa judgement to confirm usability of the image and an evaluation to determine image processing results)
Claim 9:
With respect to dependent claim 9, the claim depends upon independent claim 2. The analysis of claim 2 is incorporated herein by reference.
Step 2A, Prong 1:
With respect to claim 8, the claim recites:
wherein in cases where the quality statement categorizes the image processing model as unsuitable (mental process; As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses aa judgement to determine usability of the image)
Step 2A, Prong 2:
Accordingly, after determining that a claim recites a judicial exception in Step 2A Prong One, examiners should evaluate whether the claim as a whole integrates the recited judicial exception into a practical application of the exception in Step 2A Prong Two. A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception (MPEP 2106.04(d)).
The claims disclose the following additional elements:
a new training of the image processing model is implemented with a change, wherein the change relates to one of the following:
hyperparameters, an optimizer used or a regularization of a training of the image processing model
a removal of model parameters from the image processing model or an addition of model parameters to the image processing model, or a change in architecture, or
a division into training and validation data or a selection of training and validation data
In this instance, training is recited at a high-level of generality with no detail of the training process and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B:
Based on the determination in Step 2A of the analysis that the claims are directed toward a judicial exception, in must be determined if any claims contain any element or combination of elements sufficient to ensure that the claims amount to significantly more than the judicial exception (Step 2B).
The claims disclose the following additional elements:
hyperparameters, an optimizer used or a regularization of a training of the image processing model
a removal of model parameters from the image processing model or an addition of model parameters to the image processing model, or a change in architecture, or
a division into training and validation data or a selection of training and validation data
In this instance, training is recited at a high-level of generality with no detail of the training process and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
In this instance, after considering all claim elements individually and as an ordered combination, it is determined that the claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 10:
With respect to dependent claim 10, the claim depends upon independent claim 2. The analysis of claim 2 is incorporated herein by reference.
Step 2A, Prong 1:
With respect to claim 10, the claim recites:
wherein the quality testing… determines the change based on at least the model parameter values and contextual information regarding the image processing model (mental process; As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses an evaluation by comparing the groups of model parameters and contextual information to calculate the quality measure)
Step 2A, Prong 2:
Accordingly, after determining that a claim recites a judicial exception in Step 2A Prong One, examiners should evaluate whether the claim as a whole integrates the recited judicial exception into a practical application of the exception in Step 2A Prong Two. A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception (MPEP 2106.04(d)).
The claims disclose the following additional elements:
a quality testing program
These additional claim elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B:
Based on the determination in Step 2A of the analysis that the claims are directed toward a judicial exception, in must be determined if any claims contain any element or combination of elements sufficient to ensure that the claims amount to significantly more than the judicial exception (Step 2B).
The claims disclose the following additional elements:
a quality testing program
These additional claim elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
In this instance, after considering all claim elements individually and as an ordered combination, it is determined that the claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 11:
With respect to dependent claim 11, the claim depends upon independent claim 2. The analysis of claim 2 is incorporated herein by reference.
Step 2A, Prong 2:
Accordingly, after determining that a claim recites a judicial exception in Step 2A Prong One, examiners should evaluate whether the claim as a whole integrates the recited judicial exception into a practical application of the exception in Step 2A Prong Two. A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception (MPEP 2106.04(d)).
The claims disclose the following additional elements:
performing the quality testing of the image processing model during an ongoing training of the image processing model
continuing or reinitiating the training with changes as a function of the quality statement
In this instance, training is recited at a high-level of generality with no detail of the training process and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B:
Based on the determination in Step 2A of the analysis that the claims are directed toward a judicial exception, in must be determined if any claims contain any element or combination of elements sufficient to ensure that the claims amount to significantly more than the judicial exception (Step 2B).
The claims disclose the following additional elements:
performing the quality testing of the image processing model during an ongoing training of the image processing model
continuing or reinitiating the training with changes as a function of the quality statement
In this instance, training is recited at a high-level of generality with no detail of the training process and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
In this instance, after considering all claim elements individually and as an ordered combination, it is determined that the claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 12:
With respect to dependent claim 12, the claim depends upon independent claim 2. The analysis of claim 2 is incorporated herein by reference.
Step 2A, Prong 1:
With respect to claim 12, the claim recites:
wherein the image processing model is configured to calculate a processing result in the form of at least one of the following from at least one microscopic image:
a statement regarding whether certain objects are present in the microscopic image
geometric specification relating to depicted objects
an identification, a number, or characteristics of depicted objects
a warning regarding analysis conditions, microscope settings, sample characteristics, or image characteristics
a control command for controlling the microscope or for a subsequent image evaluation or a recommendation of a control command for controlling the microscope or for a subsequent image evaluation
a classification result that specifies a categorization into at least one of a plurality of possible classes as a function of depicted image content
a semantic segmentation or detection of certain structures
(mental process; As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses an evaluation by comparing the groups of model parameters and contextual information to calculate a processing result)
Step 2A, Prong 2:
Accordingly, after determining that a claim recites a judicial exception in Step 2A Prong One, examiners should evaluate whether the claim as a whole integrates the recited judicial exception into a practical application of the exception in Step 2A Prong Two. A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception (MPEP 2106.04(d)).
The claims disclose the following additional elements:
an output image in which depicted objects are more clearly visible or are depicted in a higher image quality or in which a depiction of certain structures is suppressed
These additional claim elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B:
Based on the determination in Step 2A of the analysis that the claims are directed toward a judicial exception, in must be determined if any claims contain any element or combination of elements sufficient to ensure that the claims amount to significantly more than the judicial exception (Step 2B).
The claims disclose the following additional elements:
an output image in which depicted objects are more clearly visible or are depicted in a higher image quality or in which a depiction of certain structures is suppressed
These additional claim elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
In this instance, after considering all claim elements individually and as an ordered combination, it is determined that the claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 13:
With respect to independent claim 13, the claim recites the limitations substantially similar to those in claim 2. The analysis of claim 2 is incorporated herein.
Step 2A, Prong 2:
Accordingly, after determining that a claim recites a judicial exception in Step 2A Prong One, examiners should evaluate whether the claim as a whole integrates the recited judicial exception into a practical application of the exception in Step 2A Prong Two. A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception (MPEP 2106.04(d)).
The claims disclose the following additional elements:
a computer program, comprising commands stored on a non-transitory computer-readable medium, and which when executed by the computer, causes the execution of the method
These additional claim elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B:
Based on the determination in Step 2A of the analysis that the claims are directed toward a judicial exception, in must be determined if any claims contain any element or combination of elements sufficient to ensure that the claims amount to significantly more than the judicial exception (Step 2B).
The claims disclose the following additional elements:
a computer program, comprising commands stored on a non-transitory computer-readable medium, and which when executed by the computer, causes the execution of the method
These additional claim elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
In this instance, after considering all claim elements individually and as an ordered combination, it is determined that the claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 14:
With respect to claim 14, the claim depends upon claim 2. The analysis of claim 2 is incorporated herein by reference.
Step 2A, Prong 1:
Following the determination that the claims fall within one of the statutory categories (Step 1), it must be determined if the claims recite a judicial exception (Step 2A, Prong 1). In this instance, the claims are determined to recite a judicial exception (abstract idea; mental process).
With respect to claim 14, the claim recites:
wherein the learned model parameters values include weights of filters of convolutional layers of the image processing model (mental process; As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses an evaluation of the quality of a trained image processing model based upon testing, using parameter values including weights of filters of layers)
Step 2A, Prong 2:
There are no additional elements considered under Step 2A, Prong 2.
Step 2B:
There are no additional elements considered under Step 2B.
Claim 15:
With respect to claim 15, the claim depends upon claim 2. The analysis of claim 14 is incorporated herein by reference.
Step 2A, Prong 1:
Following the determination that the claims fall within one of the statutory categories (Step 1), it must be determined if the claims recite a judicial exception (Step 2A, Prong 1). In this instance, the claims are determined to recite a judicial exception (abstract idea; mental process).
With respect to claim 15, the claim recites:
wherein the quality testing… determines whether the weights of the filters manifest a structure clearly different from noise (mental process; As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses an evaluation of the quality of a trained image processing model based upon testing to determine whether the weights of the filters result in content different from noise)
Step 2A, Prong 2:
There are no additional elements considered under Step 2A, Prong 2.
Step 2B:
There are no additional elements considered under Step 2B.
Claim 16:
With respect to claim 16, the claim depends upon claim 2. The analysis of claim 2 is incorporated herein by reference.
Step 2A, Prong 1:
Following the determination that the claims fall within one of the statutory categories (Step 1), it must be determined if the claims recite a judicial exception (Step 2A, Prong 1). In this instance, the claims are determined to recite a judicial exception (abstract idea; mental process).
With respect to claim 16, the claim recites:
wherein the quality of the image processing model is further analyzed based on the image processing result (mental process; As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses an evaluation of the quality of a model based on the image processing result)
Step 2A, Prong 2:
There are no additional elements considered under Step 2A, Prong 2.
Step 2B:
There are no additional elements considered under Step 2B.
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 1-5, 7-8, 10, and 12-13 remain rejected and claim 16 is rejected under 35 U.S.C. 102(a)(1) as being anticipated by Amthor et al. (US 2020/0371333, published 26 November 2020, hereafter Amthor).
As per independent claim 1, Amthor discloses a microscopy system, comprising:
a microscope for image capture (paragraphs 0003-0004: Here, a microscope, such as a light microscope or X-ray microscope, may be used to capture an image)
a computing device (paragraph 0003: Here, a computer is used for the image processing algorithm) that is configured to train, using the training data, an image processing model to calculate an image processing result from at least one microscope image (paragraph 0010: Here, a verification algorithm is used to process image data. This verification algorithm is trained using reference images and reference verification results)
wherein the computing device comprises a quality testing program for testing a quality of the image processing model (paragraph 0010: Here, a verification algorithm is a quality testing program for testing the quality of the image processing algorithm (model)), wherein the quality testing program is configured to make a quality statement on a quality of the image processing model from learned model parameter values of the image processing model (paragraph 0016: Here, the image, output from the image processing algorithm, is assigned a quality of “correct” or “incorrect” image processing results)
As per independent claim 2, Amthor discloses a computer-implemented method for testing a quality of a machine-learned image processing model, configured to calculate an image processing result from at least one microscope image, the method including:
inputting learned model parameter values of the image processing model into a quality testing program which is configured to make a quality statement on a quality of the image processing model from input model parameter values (paragraphs 0010 and 0016: Here, a verification algorithm is a quality testing program for testing the quality of the image processing algorithm (model). The image, output from the image processing algorithm, is assigned a quality of “correct” or “incorrect” image processing results)
using the quality testing program to calculate a quality statement regarding a quality of the image processing model based on the learned model parameter values (paragraph 0010: Here, a verification algorithm is used to process image data. This verification algorithm is trained using reference images and reference verification results. The image, output from the image processing algorithm, is assigned a quality of “correct” or “incorrect” image processing results (paragraph 0016))
As per dependent claim 3, Amthor discloses wherein for the calculation of the quality statement a quality measure is derived from the learned model parameter values and compared with reference values (paragraphs 0017-0018: Here, the verification algorithm compares image processing results outputs with references images to determine whether the image processing algorithm has operated correctly).
As per dependent claim 4, Amthor discloses wherein the quality testing program makes the quality statement based on evaluation criteria relating to the model parameter values, wherein the evaluation criteria relate to one or more of the following:
a randomness or entropy of a group of model parameter values
a similarity of a group of model parameter values to known or expected distributions (paragraph 0023: Here, the frequency of distribution of expected objects are used)
an energy of filter weights of a convolutional layer
a presence of inactive filter masks in the image processing model with model parameter values that lie exclusively below a predetermined threshold
an invariability of model parameter values of activation functions over a plurality of training steps
a presence of structures in groups of model parameter values (paragraph 0024: Here, the image processing algorithm identifies artefacts. These are structures within the calculated image that do not represent object structures)
a memorization of specific structures of training data in filter masks of the image processing model
a color distribution in filter masks of the image processing model
As per dependent claim 5, Amthor discloses wherein the quality testing program comprises a machine-learned model trained to make the quality statement based on one or more of the evaluation criteria (paragraphs 0010, 0016, and 0024: Here, the verification is performed based upon identifying that the artefact errors are contained within the image).
As per dependent claim 7, Amthor discloses wherein the quality testing program takes into account contextual information in addition to the model parameter values to calculate the quality statement, wherein the contextual information relates to one or more of the following:
initial values of model parameters of the image processing model at a beginning of training
an evolution of the model parameter values over a training
training data of the image processing model (paragraphs 0016-0017)
a model architecture of the image processing model
information regarding an application for which microscope images were captured as training data of the image processing model
information regarding a microscope or microscope settings with which microscope images were captured as training data of the image processing model
a user identification (paragraph 0017: Here, verification results are provided by a user)
a specification of a sample type visible in microscope images of the training data of the image processing model
As per dependent claim 8, Amthor discloses wherein in cases where the quality statement confirms a usability of the image processing model: the image processing model calculates image processing results from microscope image (paragraph 0027: Here, based upon a determination that the verification results are correct, additional images are collected and sampled) or subject to a supplemental verification of a model quality, the image processing mode calculates image processing results from microscope images.
As per dependent claim 10, Amthor discloses wherein the quality testing program determines the change based on at least the model parameter values and contextual information regarding the image processing model (paragraphs 0017-0018: Here, the contextual information is training data of the image processing model).
As per dependent claim 12, Amthor discloses wherein the image processing model is configured to calculate a processing result in the form of at least one of the following from the microscope image:
a statement regarding whether certain objects are present in the microscope image
geometric specifications relating to depicted objects
an identification, a number, or characteristics of depicted objects
a warning regarding analysis conditions, microscope settings, sample characteristics, or image characteristics
a control command for controlling the microscope or for a subsequent image evaluation or a recommendation of a control command for controlling the microscope or for a subsequent image evaluation
an output image in which depicted objects are more clearly visible or are depicted in a higher image quality or in which a depiction of certain structures is suppressed
a classification result that specifies a categorization into at least one of a plurality of possible classes as a function of a depicted image content
a semantic segmentation or detection of certain structures (paragraph 0016: Here, biological cells are identified by identifying cell walls/membranes having a regular shape. Based upon the examples having an oval or circular cross section, the results are verified)
With respect to claim 13, Amthor discloses the limitations similar to those in claim 2, and the same rejection is incorporated herein. Amthor further discloses a computer program, comprising commands stored on a non-transitory computer-readable medium, and which, when the program is executed by a computer, cause a method to be performed (claim 17).
As per dependent claim 16, Amthor discloses wherein the quality of the image processing model is further analyzed based on the image processing result (paragraph 0035: Here, the machine learning algorithm derives from an image processing result a quality factor).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim 6 remains rejected under 35 U.S.C. 103 as being unpatentable over Amthor and further in view of Iso-Sipila et al. (US 2022/0188520, published 16 June 2022, hereafter Iso-Sipila).
As per dependent claim 6, Amthor discloses the limitations similar to those in claim 2, and the same rejection is incorporated herein. Amthor discloses wherein the quality testing program evaluates groups of model parameter values together and additionally takes into account information regarding a model parameter as well as contextual information in order to calculate a quality statement (paragraphs 0017-0018: Here, the contextual information is training data of the image processing model).
Amthor fails to specifically disclose taking into account information regarding a model parameter position. However, Iso-Sipila, which is analogous to the claimed invention because it is directed toward validating a model, discloses taking into account information regarding a model parameter position (paragraph 0019 and claim 35: Here, sets of labeled data are generated, including a position of objects. The trained model is validated based upon one or more entities and their position). It would have been obvious to one of ordinary skill in the art at the time of the applicant’s effective filing date to have combined Iso-Sipila with Amthor, with a reasonable expectation of success, as it would have allowed for validating a trained model based on a plurality of data items, including position data of objects (Iso-Sipila: claim 35).
Claims 9 and 11 remain rejected under 35 U.S.C. 103 as being unpatentable over Amthor and further in view of Donderici (US 2023/0382407, filed 31 May 2022).
As per dependent claim 9, Amthor discloses the limitations similar to those in claim 2, and the same rejection is incorporated herein. Amthor further discloses wherein in cases where the quality statement categorizes the image processing model as unsuitable values (paragraphs 0010 and 0016: Here, a verification algorithm is a quality testing program for testing the quality of the image processing algorithm (model). The image, output from the image processing algorithm, is assigned a quality of “correct” or “incorrect” image processing results).
Amthor fails to specifically disclose:
a new training of the image processing model is implemented with a change, wherein the change relates to at least one of the following:
hyperparameters, an optimizer used or a regularization of a training of the image processing model
a removal of model parameters from the image processing model or an addition of model parameters to the image processing model, or a change in architecture
a division into training and validation data or a selection of training and validation data
However, Donderici, which is analogous to the claimed invention because it is directed toward retraining a model, discloses:
a new training of the image processing model is implemented with a change, wherein the change relates to at least one of the following:
hyperparameters, an optimizer used or a regularization of a training of the image processing model (paragraph 0054: Here, a model is retrained based on the optimization module modifying a hyperparameter)
a removal of model parameters from the image processing model or an addition of model parameters to the image processing model, or a change in architecture
a division into training and validation data or a selection of training and validation data
It would have been obvious to one of ordinary skill in the art at the time of the applicant’s effective filing date to have combined Donderici with Amthor, with a reasonable expectation of success, as it would have allowed for retraining a model to update optimize the performance of the model (Donderici: paragraph 0054).
As per dependent claim 11, Amthor discloses the limitations similar to those in claim 2, and the same rejection is incorporated herein. Amthor discloses performing the quality testing of the image processing model (paragraph 0010).
Amthor fails to specifically disclose:
performing testing during an ongoing training of the image processing model
continuing or reinitiating the training with changes as a function of the quality statement
However, Donderici, which is analogous to the claimed invention because it is directed toward optimizing the model via retraining, discloses:
performing testing during an ongoing training of the image processing model (Figure 4; paragraphs 0066 and 0069: Here, a performance evaluator determines a performance score associated with a model and performs additional training (learning adjustment) based upon the performance evaluation)
continuing or reinitiating the training with changes as a function of the quality statement (Figure 4; paragraphs 0066 and 0069: Here, a performance evaluator determines a performance score associated with a model and performs additional training (learning adjustment) based upon the performance evaluation)
It would have been obvious to one of ordinary skill in the art at the time of the applicant’s effective filing date to have combined Donderici with Amthor, with a reasonable expectation of success, as it would have allowed for retraining a model to update optimize the performance of the model (Donderici: paragraph 0054).
Claims 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Amthor and further in view of Liu et al. (US 2023/0206401, filed 29 December 2021, hereafter Liu).
As per dependent claim 14, Amthor discloses the limitations similar to those in claim 2, and the same rejection is incorporated herein. Amthor discloses an image processing convolutional neural network (paragraph 0035, but fails to specifically disclose wherein the learned model parameter values include weights of filters of convolutional layers of the image processing model.
However, Liu, which is analogous to the claimed invention because it is directed toward denoising images, discloses wherein the learned model parameter values include weights of filters of convolutional layers of the image processing model (paragraph 0015: Here, a convolutional layer may include a plurality of convolutional layers having respective weights). It would have been obvious to one of ordinary skill in the art at the time of the applicant’s effective filing date to have combined Liu with Amthor, with a reasonable expectation of success, as it would have allowed for improving denoising of images (Liu: paragraph 0015).
As per dependent claim 15, Amthor and Liu disclose the limitations similar to those in claim 14, and the same rejection is incorporated herein. Liu further discloses wherein the quality testing program determines whether the weights of the filters manifest a structure clearly different from noise (paragraph 0015: Here, the examiner interprets the term “a structure clearly different form noise” as being an up-scaled feature map or vector that may be used to predict pixel values in an output image that are free of certain noise). It would have been obvious to one of ordinary skill in the art at the time of the applicant’s effective filing date to have combined Liu with Amthor, with a reasonable expectation of success, as it would have allowed for improving denoising of images (Liu: paragraph 0015).
Response to Arguments
Applicant’s arguments filed 24 June 2026 with respect to the rejection of claims 4, 7, and 10 under 35 USC 112 have been fully considered and are persuasive in view of the amendment. The rejection has been withdrawn.
Applicant’s arguments filed 24 June 2026 with respect to the rejection of claim 13 under 35 USC 101 as failing under Step 1 have been fully considered and are persuasive in view of the amendment. The rejection has been withdrawn.
Applicant's arguments filed 24 June 2026 with respect to the rejection of claims 1-13 under 35 USC 101 as being directed to an abstract idea without significantly more have been fully considered but they are not persuasive.
The applicant’s initial argument is that “the Office leaves off “the computing device comprises a quality testing program for…” from the claim” and “a computing device executing a quality testing program configured to make a quality statement is clearly not a mental process under any reasonable interpretation of the claim (page 8).”
While the applicant is correct in asserting that a computing device is not a mental process, the examiner does not allege such. Instead, the claimed computing device is considered under Step 2A, Prong 2 and Step 2B. The claimed computing device is recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
In this particular instance, the claimed invention recites a mental process performed on a generic computer. An example of a case identifying a mental process performed on a generic computer as an abstract idea is Voter Verified, Inc. v. Election Systems & Software, LLC, 887 F.3d 1376, 1385, 126 USPQ2d 1498, 1504 (Fed. Cir. 2018). In this case, the Federal Circuit relied upon the specification in explaining that the claimed steps of voting, verifying the vote, and submitting the vote for tabulation are "human cognitive actions" that humans have performed for hundreds of years. The claims therefore recited an abstract idea, despite the fact that the claimed voting steps were performed on a computer. 887 F.3d at 1385, 126 USPQ2d at 1504. Another example is Versata, in which the patentee claimed a system and method for determining a price of a product offered to a purchasing organization that was implemented using general purpose computer hardware. 793 F.3d at 1312-13, 1331, 115 USPQ2d at 1685, 1699. The Federal Circuit acknowledged that the claims were performed on a generic computer, but still described the claims as "directed to the abstract idea of determining a price, using organizational and product group hierarchies, in the same way that the claims in Alice were directed to the abstract idea of intermediated settlement, and the claims in Bilski were directed to the abstract idea of risk hedging." 793 F.3d at 1333; 115 USPQ2d at 1700-01.
For this reason, this argument is not persuasive.
The applicant further argues that “the claimed invention is clearly directed to a practical application” and “provides a practical solution to a problem with previous approaches of evaluating the quality of learning models (page 8). Specifically, the applicant argues that the “claimed invention is configured to make a quality statement on a quality of the image processing model from learned model parameter values of the image processing model (page 8).”
In this instance, the abstract idea is identified as “testing a quality of the image processing model… to make a quality statement on a quality of the image processing model from learned model parameter values of the image processing model.”
It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements. See the discussion of Diamond v. Diehr, 450 U.S. 175, 187 and 191-92, 209 USPQ 1, 10 (1981)) in subsection II, below. In addition, the improvement can be provided by the additional element(s) in combination with the recited judicial exception. See MPEP § 2106.04(d) (discussing Finjan, Inc. v. Blue Coat Sys., Inc., 879 F.3d 1299, 1303-04, 125 USPQ2d 1282, 1285-87 (Fed. Cir. 2018))
Therefore, the applicant’s alleged improvement is provided by abstract idea. For this reason, this argument is not persuasive.
Applicant's arguments filed 24 June 2026 with respect to the rejection of claims under 35 USC 102 and 35 USC 103 have been fully considered but they are not persuasive.
The applicant’s initial argument is that Amthor fails to disclose providing a quality statement on the quality of the image processing model from learned model parameter values of the image processing model (pages 9-10). The examiner respectfully disagrees.
The applicant acknowledges that Amthor discloses providing a quality statement of “correct” or “incorrect” (Remarks: page 9; Amthor: paragraph 0016). The applicant further argues that “the output of an image processing algorithm is clearly distinct from learned model parameter values of an image processing model (page 10).”
To support this position, the applicant argues that “model parameter values can include weights that are iterative adjusted in the course of training a model (page 10)” and the “image processing model B calculates an image processing result 40 based on the current model parameter values from each image in the training data (page 10).” However, these features are not recited in independent claims 2, 3, and 13. Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
The applicant’s claims require “using the quality testing program to calculate a quality statement regarding a quality of the image processing model based on the learned model parameter values (claim 2, lines 7-9). Amthor discloses using the quality testing program to calculate a quality statement regarding a quality of the image processing model based on the learned model parameter values (paragraph 0010). Specifically, a verification algorithm is used to process image data. This verification algorithm is trained using reference images and reference verification results. The image, output from the image processing algorithm, is assigned a quality of “correct” or “incorrect” image processing results (paragraph 0016). For this reason, this argument is not persuasive.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Chen et al. (US 2023/0367850): Discloses convolutional layers or filters with respective weights for use in denoising image data (paragraph 0017)
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 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 KYLE R STORK whose telephone number is (571)272-4130. The examiner can normally be reached 8am - 2pm; 4pm - 6pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Omar Fernandez Rivas can be reached at 571/272-2589. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/KYLE R STORK/Primary Examiner, Art Unit 2128
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