Detailed Action
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 12/19/2025 has been considered by the examiner.
Response to Amendment
Claims 1, 4, 6, 8, 10, 13-14, and 17-20 remain pending, with claims 10 and 17-20 withdrawn, in the application in response to the applicant’s amendments to the rejections previously set forth in the Non-Final Office Action mailed 10/22/2025.
Response to Arguments
Applicant's arguments filed 01/22/2026 have been fully considered but they are not persuasive.
For claim 1, the applicant argues that “Naidu does not disclose or suggest to display the position of the reflector” (see pg. 6, para. 4 of applicant’s remarks), and the examiner disagrees. Naidu teaches displaying cysts (reflectors) and identifying corresponding shadow artifacts 502 in an ultrasound image (Fig. 5A-5B). Therefore, under broadest reasonable interpretation, Naidu teaches “give a notification of a position of a reflector in the subject related to the artifact in the ultrasound image… by displaying the notification on the monitor…”.
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, 4, 6, 8, and 13-14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1 is an apparatus claim that recites a judicial exception (abstract idea). The “determine whether or not the artifact has occurred in the ultrasound image…” and “give a notification of a position of a reflector” steps in claim 1 does not specify how to determine whether or not the artifact has occurred in the ultrasound image, or how to give a notification of a position of a reflector. The physician can print and view an ultrasound image, view (determine) the presence of an artifact in the image, and give notification (write out or speak) of the position of a reflector related to the artifact in the image using their mind and a pen (see MPEP 2106, section III, step 2A of subject matter eligibility test flowchart). This judicial exception is not integrated into a practical application because the step in the claim can be considered as processes that can be performed in the human mind (see MPEP 2106.04(a)(2)(III)).
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because no details are given surrounding the step (see MPEP 2106, section III, step 2B of subject matter eligibility test flowchart). Therefore, the claim is not eligible subject matter under 35 US.C. 101.
General system elements (i.e., probe, monitor or speaker, memory, processor, trained model) related to the insignificant extra solution activity steps that do not integrate the abstract idea into a practical application as it does not impose any meaningful limits on practicing the abstract idea.
Claim 4 merely recites a diagnostic apparatus. General system elements (i.e., “diagnostic apparatus”) related to the insignificant extra solution activity steps that do not integrate the abstract idea into a practical application as it does not impose any meaningful limits on practicing the abstract idea.
Claim 6 merely recites a diagnostic apparatus, a server, and a network. General system elements (i.e., diagnostic apparatus, server, network) related to the insignificant extra solution activity steps that do not integrate the abstract idea into a practical application as it does not impose any meaningful limits on practicing the abstract idea.
Claim 8 is an apparatus claim that recites a judicial exception (abstract idea). The “determine whether or not the artifact has occurred in the ultrasound image” and “give a notification of a position of a reflector and the occurrence cause of the artifact” steps in claim 8 does not specify how to determine whether or not the artifact has occurred in the ultrasound image, or how to give a notification of a position of a reflector and the occurrence cause of the artifact. The physician can print and view an ultrasound image, view (determine) the presence of an artifact in the image, and give notification (write out or speak) of the position of a reflector and the occurrence cause of the artifact in the image using their mind and a pen (see MPEP 2106, section III, step 2A of subject matter eligibility test flowchart). This judicial exception is not integrated into a practical application because the step in the claim can be considered as processes that can be performed in the human mind (see MPEP 2106.04(a)(2)(III)).
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because no details are given surrounding the step (see MPEP 2106, section III, step 2B of subject matter eligibility test flowchart). Therefore, the claim is not eligible subject matter under 35 US.C. 101.
General system elements (i.e., processors, diagnostic apparatus, server, network, memory) related to the insignificant extra solution activity steps that do not integrate the abstract idea into a practical application as it does not impose any meaningful limits on practicing the abstract idea.
Claims 13-14 is an apparatus claim that recites a judicial exception (abstract idea). The “designate a region of interest” and “determine whether or not the artifact has occurred” steps in claims 13-14 does not specify how to designate a region of interest, or how to determine whether or not the artifact has occurred. The physician can print and view an ultrasound image, draw around (designate) the region of interest in the image, and view (determine) the presence of an artifact in the region of interest using their mind and a pen (see MPEP 2106, section III, step 2A of subject matter eligibility test flowchart). This judicial exception is not integrated into a practical application because the step in the claim can be considered as processes that can be performed in the human mind (see MPEP 2106.04(a)(2)(III)).
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because no details are given surrounding the step (see MPEP 2106, section III, step 2B of subject matter eligibility test flowchart). Therefore, the claim is not eligible subject matter under 35 US.C. 101.
General system elements (i.e., input device, processor) related to the insignificant extra solution activity steps that do not integrate the abstract idea into a practical application as it does not impose any meaningful limits on practicing the abstract idea.
Claim Rejections - 35 USC § 102
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 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, 4, 6, 8, and 13-14 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by
Naidu et al. (US 20200297318 A1, published September 24, 2020 with a priority date of November 2,
2017), from IDS, hereinafter referred to as Naidu.
Regarding claim 1, Naidu teaches an ultrasound diagnostic system (Fig. 1, ultrasound system 100)
comprising:
an ultrasound probe having a transducer array (see para. 0023 - "The ultrasound data acquisition
unit 110 may include an ultrasound transducer or probe which includes an ultrasound sensor
array 112...");
a monitor or a speaker (Fig. 5A-5B; see para. 0025 - "The user interface 132 [monitor] may be
configured to display the ultrasound images 134 of the region in real time as an ultrasound scan is being
performed, along with the indicator 136.");
a data memory configured to store an occurrence cause of an artifact, and an operation method
the ultrasound probe to eliminate the artifact based on the occurrence cause (see para. 0022 - "For
example, a software-based neural network may be implemented using a processor (e.g., single or multi-
core CPU, a single GPU or GPU cluster, or multiple processors arranged for parallel-processing) configured
to execute instructions, which may be stored in computer readable medium [data memory], and which
when executed cause the processor to perform a machine-trained algorithm for identifying various
artefacts within ultrasound images and, in some examples, output an indication of the presence, absence,
and/or type [occurrence cause] thereof."; see para. 0034 - "Such guidance may be generated by
the neural network 128 in the form of one or more instructions 137 and may be responsive to
the indicator 136 also generated by the neural network 128.");
a processor (Fig. 1, includes signal processor 122 and artefact detection engine 127) configured
to:
transmit and receive an ultrasound beam to and from a subject with the transducer array (see
para. 0023 - "The ultrasound data acquisition unit 110 may include an ultrasound transducer or probe
which includes an ultrasound sensor array 112 configured to transmit ultrasound pulses 114 into a target
region 116 of a subject, e.g., abdomen, and receive echoes 118 responsive to the transmitted pulses.");
acquire an ultrasound image based on a received signal output from the transducer array (see para. 0023 - "As further shown, the ultrasound data acquisition unit 110 may include a beamformer 120 and a signal processor 122, which may be configured to generate a plurality of discrete
ultrasound image frames 124 from the ultrasound echoes 118 received at the array 112.");
determine whether or not the artifact has occurred in the ultrasound image, using a trained model
trained using learning data in which a plurality of ultrasound images including artifacts and occurrence
causes of the artifacts are associated with each other (see para. 0024 - "Each model of the neural
network 128 [trained model] may be pre-trained via a training algorithm to determine a presence
[artifacts] and/or type [occurrence cause] of imaging artefact in image frames 124 [ultrasound images]
acquired during a specific imaging application. Accordingly, each model may be pre-trained with a distinct
set of training data 129 obtained via imaging a distinct target region 116."); and
give a notification of a position of a reflector (Fig. 5A-5B, displaying cysts in ultrasound image as notification of position of reflectors) in the subject related to the artifact in the ultrasound image, the occurrence cause of the artifact, and the operation method of the ultrasound probe to eliminate the artifact, by displaying the notification on the monitor or outputting a voice through the speaker (Fig. 5A-5B and 6; see para. 0025 - "In some examples, the display processor 130 may be configured to generate ultrasound images 134 from the image frames 124 and an indicator 136 that conveys the presence [artifact location] and/or type [occurrence cause] of image artefact(s) within each of the image frames 124 The user interface 132 may also be configured to display one or more instructions 137 based on the detected presence and/or type of artefacts appearing within the image frames 124. The instructions 137 may include directions for adjusting the data acquisition unit 110 [operation method of the ultrasound probe] in a manner that removes the artefact(s) from the image frames 124, thereby improving the quality of the image frames.").
Furthermore, regarding claim 4, Naidu further teaches a diagnostic apparatus including the
processor and the data memory (see para. 0022 - "In some embodiments, the ultrasound images and
tissue information, including information regarding the presence and/or type of artefacts, may be
provided to a storage and/or memory device, such as a picture archiving and communication system
(PACS) [known in the art to include processor and memory] for reporting purposes or future machine
training (e.g., to continue to enhance the performance of the neural network).").
Furthermore, regarding claim 6, Naidu further teaches a diagnostic apparatus including the
processor; and a server being connected to the diagnostic apparatus through a network and including the
data memory (see para. 0022 - "In some embodiments, the ultrasound images and tissue information,
including information regarding the presence and/or type of artefacts, may be provided to a storage
and/or memory device, such as a picture archiving and communication system (PACS) [known in the art
to include processors, memory, a network, and a server] for reporting purposes or future machine training
(e.g., to continue to enhance the performance of the neural network).").
Furthermore, regarding claim 8, Naidu further teaches wherein the processor is composed of a first processor (artefact detection engine 127) configured to generate the ultrasound image and determine whether or not the artifact has occurred in the ultrasound image (see para. 0024 - "The system may also include an artefact detection engine 127, e.g., a computational module or circuitry (e.g., application specific integrated circuit (ASIC), configured to implement a neural network 128. The neural network 128 may be configured to receive the image frames 124 and determine a presence and/or type of an imaging artefact within each frame."), and
a second processor (display processor 130) configured to give the notification of the occurrence
location and the occurrence cause of the artifact in the ultrasound image (see para. 0033 - "The display
processor 130 communicatively coupled with the neural network 128 may be configured to generate
an indicator 136 based on the determinations made by the neural network 128. In some implementations, the indicator 136 may indicate the presence, absence, and/or type of artefact within an image frame 124."),
the ultrasound diagnostic system further comprises: a diagnostic apparatus including the second processor; and a server being connected to the diagnostic apparatus through a network, and including the first processor and the data memory (see para. 0022 - "In some embodiments, the ultrasound images and tissue information, including information regarding the presence and/or type of artefacts, may be
provided to a storage and/or memory device, such as a picture archiving and communication system
(PACS) [known in the art to include processors, memory, a network, and a server] for reporting purposes
or future machine training (e.g., to continue to enhance the performance of the neural network).").
Furthermore, regarding claim 13, Naidu further teaches an input device configured to designate
a region of interest in response to an input operation of a user on the ultrasound image (see para. 0025 -
"The user interface 132 [input device] may also be configured to receive a user input 138 at any time
before, during, or after an ultrasound scan. In some examples, the user input 138 can include a preset
imaging modality selection that specifies operational parameters for imaging particular bodily features
[region of interest], e.g., bladder, lungs, kidneys, etc. The operational parameters can include pre-
specified focal depths, pulse frequencies, scan line numbers, scan line densities, or other settings."),
wherein the processor is further configured to determine whether or not an artifact has occurred
in the region of interest (see para. 0025 - "The particular model of the neural network 128 applied to the
acquired image frames 124 may depend on the preset imaging modality selected by a user. For example,
the neural network model 128 applied during cardiac imaging may be different than the neural network
model applied when imaging the bladder or a kidney. Each model of the neural network 128 may thus be
pre-trained to identify artefacts in specific types of image frames 124 acquired from a specific target
region 116.").
Furthermore, regarding claim 14, Naidu further teaches an input device configured to designate a region of interest in response to an input operation of a user on the ultrasound image (see para. 0025 - "The user interface 132 [input device] may also be configured to receive a user input 138 at any time before, during, or after an ultrasound scan. In some examples, the user input 138 can include a preset imaging modality selection that specifies operational parameters for imaging particular bodily features [region of interest], e.g., bladder, lungs, kidneys, etc. The operational parameters can include pre-specified focal depths, pulse frequencies, scan line numbers, scan line densities, or other settings."),
wherein the processor is further configured to determine whether or not an artifact has occurred
in the region of interest (see para. 0025 - "The particular model of the neural network 128 applied to the
acquired image frames 124 may depend on the preset imaging modality selected by a user. For example,
the neural network model 128 applied during cardiac imaging may be different than the neural network
model applied when imaging the bladder or a kidney. Each model of the neural network 128 may thus be
pre-trained to identify artefacts in specific types of image frames 124 acquired from a specific target
region 116.").
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Takamizawa et al. (US 5421333 A, published June 6, 1995) discloses an image artifact which is displayed superimposed upon an ultrasonic image indicating the reflector.
Venkataramani et al. (US 20220160334 A1, published May 26, 2022 with a priority date of November 23, 2020) discloses recognizing the location of detected ribs by their acoustic shadow.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Nyrobi Celestine whose telephone number is 571-272-0129. The examiner can normally be reached on Monday - Thursday, 7:00AM - 5:00PM EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Pascal Bui-Pho can be reached on 571-272-2714. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Nyrobi Celestine/Examiner, Art Unit 3798
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