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 .
Response to Amendment
Applicant’s amendment filed 10/7/2025 is acknowledged.
In light of the applicant’s arguments, the claim objection raised in the previous office action has been withdrawn.
Claims 1-10, 14, and 16-24 remain pending in the current application.
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(s) 1-10 and 14, and 16-24 are rejected under 35 U.S.C. 103 as being unpatentable over Sato (US 20170086793 A1) in view of Tek (US 20190125295 A1) and Yoo (US 20200357098 A1).
Regarding claim 1, Sato teaches an ultrasound data processor ([0026] ultrasound diagnosis apparatuses and image processing apparatuses)
comprising an input/output for receiving ultrasound data as input ([0028] an input device 3; [0006] input data string; [0027] first data strings that are sets of data generated based on echo signals caused by transmission of ultrasound waves; [0039] output signal)
the ultrasound data comprising at least pulse wave Doppler (PWD) ultrasound data ([0010] FIG. 5 is a block diagram illustrating an exemplary configuration of PWD processing circuitry)
the ultrasound data processor configured to apply a first analysis procedure to the ultrasound data, or data derived therefrom, to generate a first set of one or more analysis parameters ([0027] Based on a result of a principal component analysis using first data strings that are sets of data generated based on echo signals caused by transmission of ultrasound waves on the same scan line, the filter coefficient acquiring circuitry obtains a filter coefficient that suppresses clutter components)
the first analysis procedure comprising a Fourier spectral analysis of the ultrasound data or the data derived therefrom ([0045] the PWD processing circuitry 14b performs frequency analysis based on the fast Fourier transform (FFT) method)
apply a second analysis procedure to the ultrasound data, or the data derived therefrom, to generate a second set of one or more analysis parameters ([0027] a second data string that is a set of data derived from echo signals based on a moving body present in the region of interest)
Sato fails to teach the second analysis procedure comprising wavelet decomposition adapted to derive wavelet coefficients to provide parameters used to distinguish reliable data from non-reliable data; input the first and second sets of analysis parameters to a classifier, wherein the classifier is configured to determine, based on the input analysis parameters, at least one reliability classification for the input ultrasound data indicative of reliability of at least a portion of the input data for determining patient blood flow measurements using the ultrasound data or the data derived therefrom.
However, Tek teaches input the first and second sets of analysis parameters to a classifier ([0037] A machine-learnt classifier uses input features from both the B-mode and flow-mode data of the patient to detect the representations of the valve of the patient)
wherein the classifier is configured to determine, based on the input analysis parameters, at least one reliability classification for the input ultrasound data indicative of reliability of at least a portion of the input data for determining patient blood flow measurements using the ultrasound data or the data derived therefrom ([0007] An image processor is configured to fit a model of a heart valve over a heart cycle to the B-mode data with a machine-learnt classifier, to use the model to locate a cardiac flow area, and to calculate the cardiac flow from the Doppler flow data for the cardiac flow area. A display is configured to generate a visualization of the model over time as fit to the B-mode data, highlight the cardiac flow area, and indicate a value of the calculated cardiac flow. The location of the cardiac flow area is based, in part, on a confidence of the fit output by the machine-learnt classifier, and/or the display is configured to indicate a value of the confidence; [0004] Quantifying transvalvular blood flow directly provides additional cues via the flow over time. In addition, 3D flow quantification is potentially more accurate, as blood flow intensity may spatially vary)
Sato and Tek are considered analogous because both disclose ultrasonic imaging devices. Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the current invention to use a machine learning classification algorithm to make determinations regarding blood flow in order to resolve inaccuracies in calculating cardiac flow (Tek [0004]).
Sato in view of Tek fails to teach the second analysis procedure comprising wavelet decomposition adapted to derive wavelet coefficients to provide parameters used to distinguish reliable data from non-reliable data.
However, Yoo teaches wavelet decomposition adapted to derive wavelet coefficients to provide parameters used to distinguish reliable data from non-reliable data ([0016] aspects of the present invention provide a discrete wavelet transform-based noise removal apparatus which can effectively remove noise from an image while preserving details of the image containing useful information)
Sato and Yoo are considered analogous because both disclose image processing methods for ultrasound. Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the pending application to use a wavelet decomposition on the ultrasound image data in order to remove noise from an image while preserving details of the image containing useful information (Yoo [0016]).
Regarding claim 2, Sato fails to teach the ultrasound data processor is configured to generate a data output at the input/output indicative of the reliability classification.
However, Tek teaches the ultrasound data processor is configured to generate a data output at the input/output indicative of the reliability classification ([0006] An image of the cardiac flow value is output. The image indicates the confidence and/or the measurement area surface is placed based on the confidence and the detected heart valves over time).
Sato and Tek are considered analogous because both disclose ultrasonic imaging devices. Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the current invention to output an image which includes an indication of confidence in the calculation in order to resolve inaccuracies in calculating cardiac flow (Tek [0004]).
Regarding claim 3, Sato teaches the ultrasound data processor is configured to receive and process the input ultrasound data in real time ([0138] an FFT waveform has been generated in a real-time examination)
Regarding claim 4, Sato teaches the ultrasound data processor is further configured to process the input PWD ultrasound data to derive one or more blood flow measurements ([0003] The pulse wave Doppler (hereinafter, PWD) method is one method for displaying signals from a blood flow. In the PWD method, a Doppler waveform is generated by performing fast Fourier transform (FFT) on time-series data of signals received from the same location within a range defined by a range gate. In the PWD method, the power of a blood flow, expressed by use of luminance, is displayed with the horizontal axis representing time and the vertical axis representing frequencies)
Regarding claim 5, Sato fails to teach wherein the ultrasound data processor is configured to determine a reliability of each of the one or more blood flow measurements based on the reliability classification(s) for the ultrasound data.
However, Tek teaches wherein the ultrasound data processor is configured to determine a reliability of each of the one or more blood flow measurements based on the reliability classification(s) for the ultrasound data ([0005] A confidence of the detection may be used to indicate confidence of calculated quantities and/or the actual presence of the valve).
Sato and Tek are considered analogous because both disclose ultrasonic imaging devices. Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the current invention to determine a confidence value on multiple measured values in order to resolve inaccuracies in calculating cardiac flow (Tek [0004]).
Regarding claim 6, Sato teaches wherein the input ultrasound data further includes ultrasound echo data and wherein the ultrasound data processor is configured to apply the first and second analysis procedures to the echo data ([0027] first data strings that are sets of data generated based on echo signals caused by transmission of ultrasound waves on the same scan line, the filter coefficient acquiring circuitry obtains a filter coefficient that suppresses clutter components. The deriving circuitry uses the filter coefficient to: obtain, from target data strings contained in a region of interest among the first data strings, a second data string that is a set of data derived from echo signals based on a moving body present in the region of interest)
Sato fails to teach determine a reliability classification for the echo data.
However, Tek teaches determine a reliability classification for the echo data ([0006] quantification of cardiac flow in echocardiography…The image indicates the confidence and/or the measurement area surface is placed based on the confidence and the detected heart valves over time).
Sato and Tek are considered analogous because both disclose ultrasonic imaging devices. Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the current invention to determine a confidence score on the classification of the ultrasound echo data in order to resolve inaccuracies in calculating cardiac flow (Tek [0004]).
Regarding claim 7, Sato teaches wherein the input PWD ultrasound data is representative of a PWD signal over time ([0003] In the PWD method, the power of a blood flow, expressed by use of luminance, is displayed with the horizontal axis representing time)
Sato fails to teach the ultrasound data processor is configured to break the signal into multiple temporal portions and to generate a respective reliability classification for each temporal portion.
However, Tek teaches the ultrasound data processor is configured to break the signal into multiple temporal portions ([0030] Sets of data representing the volume multiple times during a heart cycle are acquired by scanning)
and to generate a respective reliability classification for each temporal portion ([0114] the image processor 12 is configured to fit a model of a heart valve over a heart cycle to B-mode data with a machine-learnt classifier. Models may be fit to multiple valves over any number of heart cycles or portion of a heart cycle).
Sato and Tek are considered analogous because both disclose ultrasonic imaging devices. Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the current invention to determine perform analysis, which includes a confidence score, for multiple time points, each time point corresponding to a different heart cycle, in order to resolve inaccuracies in calculating cardiac flow (Tek [0004]).
Regarding claim 8, Sato fails to teach the ultrasound data processor is further configured to process each of the temporal portions of the PWD ultrasound signal to derive a respective blood flow measurement based on each temporal portion.
However, Tek teaches the ultrasound data processor is further configured to process each of the temporal portions of the PWD ultrasound signal to derive a respective blood flow measurement based on each temporal portion ([0114] the image processor 12 is configured to fit a model of a heart valve over a heart cycle to B-mode data with a machine-learnt classifier. Models may be fit to multiple valves over any number of heart cycles or portion of a heart cycle).
Sato and Tek are considered analogous because both disclose ultrasonic imaging devices. Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the current invention to determine perform analysis, which includes a blood flow measurement, for multiple time points, each time point corresponding to a different heart cycle, in order to resolve inaccuracies in calculating cardiac flow (Tek [0004]).
Regarding claim 9, Sato fails to teach the ultrasound data processor is further configured to apply a data enhancement procedure to ultrasound data for which the classifier determines a low reliability classification.
However, Tek teaches the ultrasound data processor is further configured to apply a data enhancement procedure to ultrasound data for which the classifier determines a low reliability classification ([0102] The indication of confidence may be used by the physician to aid in diagnosis, prognosis, or planning. Low confidence may be used to indicate further testing or repetition of the scanning is appropriate. Different scanning may be used. Higher confidence may indicate that further scanning or repetition is not needed).
Sato and Tek are considered analogous because both disclose ultrasonic imaging devices. Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the current invention to perform additional testing in the case of a low confidence score in order to resolve inaccuracies in calculating cardiac flow (Tek [0004]).
Regarding claim 10, Sato teaches the processor is adapted to derive a PWD spectrogram based on the input PWD data ([0008] FIG. 3 is a diagram illustrating an example of an FFT display provided when the Doppler frequency of clutter overlaps the Doppler frequency of a blood flow)
and wherein the first and second analysis procedures are applied at least to a representation of the PWD spectrogram ([0027] first data strings that are sets of data generated based on echo signals caused by transmission of ultrasound waves on the same scan line, the filter coefficient acquiring circuitry obtains a filter coefficient that suppresses clutter components. The deriving circuitry uses the filter coefficient to: obtain, from target data strings contained in a region of interest among the first data strings, a second data string that is a set of data derived from echo signals based on a moving body present in the region of interest; and derive waveform information indicating temporal changes of the moving body by performing a frequency analysis on the second data string; it is understood that the FFT display in fig. 3 is a representation of the echo signals)
wherein the processor is adapted to process the input PWD data to derive a PWD spectrogram based on the input PWD data ([0008] FIG. 3 is a diagram illustrating an example of an FFT display provided when the Doppler frequency of clutter overlaps the Doppler frequency of a blood flow)
and to further extract a PWD envelope signal from the spectrogram, the envelope signal being representative of a time series of maximum Doppler frequency or velocity detected at each time point, and wherein the first and second analysis procedures are applied at least to a representation of the PWD envelope signal ([0042] The B-mode processing circuitry 13 reads out echo data (I/Q signals) generated by the transmitter/receiver circuitry 11 from the buffer 12, and performs processing such as logarithmic amplification, envelope detection processing, and logarithmic compression on the echo data thus read out, thereby generating data (B-mode data) in which signal intensity is represented by brightness of luminance).
Regarding claim 14, Sato teaches an ultrasound processing method ([0026] ultrasound diagnosis apparatuses and image processing apparatuses)
comprising receiving ultrasound data as input ([0028] an input device 3; [0006] input data string; [0027] first data strings that are sets of data generated based on echo signals caused by transmission of ultrasound waves; [0039] output signal)
the ultrasound data comprising at least pulse wave Doppler (PWD) ultrasound data ([0010] FIG. 5 is a block diagram illustrating an exemplary configuration of PWD processing circuitry)
the ultrasound data processor configured to apply a first analysis procedure to the ultrasound data, or data derived therefrom, to generate a first set of one or more analysis parameters ([0027] Based on a result of a principal component analysis using first data strings that are sets of data generated based on echo signals caused by transmission of ultrasound waves on the same scan line, the filter coefficient acquiring circuitry obtains a filter coefficient that suppresses clutter components)
the first analysis procedure comprising a Fourier spectral analysis of the ultrasound data ([0045] the PWD processing circuitry 14b performs frequency analysis based on the fast Fourier transform (FFT) method)
apply a second analysis procedure to the ultrasound data to generate a second set of one or more analysis parameters ([0027] a second data string that is a set of data derived from echo signals based on a moving body present in the region of interest)
Sato fails to teach input the first and second sets of analysis parameters to a classifier, wherein the classifier is configured to determine, based on the input analysis parameters, at least one reliability classification for the input ultrasound data indicative of reliability of at least a portion of the input data for determining patient blood flow measurements using the ultrasound data or the data derived therefrom.
However, Tek teaches input the first and second sets of analysis parameters to a classifier ([0037] A machine-learnt classifier uses input features from both the B-mode and flow-mode data of the patient to detect the representations of the valve of the patient)
wherein the classifier is configured to determine, based on the input analysis parameters, at least one reliability classification for the input ultrasound data indicative of reliability of at least a portion of the input data for determining patient blood flow measurements using the ultrasound data ([0007] An image processor is configured to fit a model of a heart valve over a heart cycle to the B-mode data with a machine-learnt classifier, to use the model to locate a cardiac flow area, and to calculate the cardiac flow from the Doppler flow data for the cardiac flow area. A display is configured to generate a visualization of the model over time as fit to the B-mode data, highlight the cardiac flow area, and indicate a value of the calculated cardiac flow. The location of the cardiac flow area is based, in part, on a confidence of the fit output by the machine-learnt classifier, and/or the display is configured to indicate a value of the confidence; [0004] Quantifying transvalvular blood flow directly provides additional cues via the flow over time. In addition, 3D flow quantification is potentially more accurate, as blood flow intensity may spatially vary)
Sato and Tek are considered analogous because both disclose ultrasonic imaging devices. Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the current invention to use a machine learning classification algorithm to make determinations regarding blood flow in order to resolve inaccuracies in calculating cardiac flow (Tek [0004]).
Sato in view of Tek fails to teach the second analysis procedure comprising wavelet decomposition adapted to derive wavelet coefficients to provide parameters used to distinguish reliable data from non-reliable data.
However, Yoo teaches wavelet decomposition adapted to derive wavelet coefficients to provide parameters used to distinguish reliable data from non-reliable data ([0016] aspects of the present invention provide a discrete wavelet transform-based noise removal apparatus which can effectively remove noise from an image while preserving details of the image containing useful information)
Sato and Yoo are considered analogous because both disclose image processing methods for ultrasound. Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the pending application to use a wavelet decomposition on the ultrasound image data in order to remove noise from an image while preserving details of the image containing useful information (Yoo [0016]).
Regarding claim 16, Sato teaches the ultrasound echo data comprises B-mode ultrasound data ([0032] a B-mode image)
Regarding claim 17, Sato teaches PWD data and echo data ([0034] PWD processing circuitry, [0027] sets of data generated based on echo signals)
Sato fails to teach an overall classification for the ultrasound data based on a combination of the reliability classifications.
However, Tek teaches an overall classification for the ultrasound data based on a combination of the reliability classifications ([0054] Each detector not only provides a binary decision for a given sample, but also a confidence value associated with the decision. The nodes in the tree are constructed by a combination of simple classifiers using boosting techniques).
Sato and Tek are considered analogous because both disclose ultrasonic imaging devices. Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the current invention to determine confidence based on a combination of data, in this case PWD and echo data, in order to resolve inaccuracies in calculating cardiac flow (Tek [0004]).
Regarding claim 18, Sato fails to teach the processor is configured to determine a reliability of each of the respective blood flow measurements based on the reliability classification determined for the respective temporal portion.
However, Tek teaches the processor is configured to determine a reliability of each of the respective blood flow measurements based on the reliability classification determined for the respective temporal portion ([0114] the image processor 12 is configured to fit a model of a heart valve over a heart cycle to B-mode data with a machine-learnt classifier. Models may be fit to multiple valves over any number of heart cycles or portion of a heart cycle).
Sato and Tek are considered analogous because both disclose ultrasonic imaging devices. Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the current invention to determine perform analysis, which includes a blood flow measurement, for multiple time points, each time point corresponding to a different heart cycle, in order to resolve inaccuracies in calculating cardiac flow (Tek [0004]).
Regarding claim 19, Sato teaches application of one or more filters ([0004] In the PWD method, it is often the case that a high pass filter (HPF) of the infinite impulse response (IIR) type is applied to time-series data before FFT is performed thereon).
Regarding claim 20, Sato teaches a non-transitory computer readable medium that stores computer executable program code ([0135] All or some of processing functions executed by the devices may be implemented by a central processing unit (CPU) and a computer program analyzed and executed by the CPU, or implemented as hardware using wired logic)
apply a first analysis procedure to the ultrasound data, or data derived therefrom, to generate a first set of one or more analysis parameters ([0027] Based on a result of a principal component analysis using first data strings that are sets of data generated based on echo signals caused by transmission of ultrasound waves on the same scan line, the filter coefficient acquiring circuitry obtains a filter coefficient that suppresses clutter components)
the first analysis procedure comprising a Fourier spectral analysis of the ultrasound data or the data derived therefrom ([0045] the PWD processing circuitry 14b performs frequency analysis based on the fast Fourier transform (FFT) method)
apply a second analysis procedure to the ultrasound data, or the data derived therefrom, to generate a second set of one or more analysis parameters ([0027] a second data string that is a set of data derived from echo signals based on a moving body present in the region of interest)
Sato fails to teach the second analysis procedure comprising wavelet decomposition adapted to derive wavelet coefficients to provide parameters used to distinguish reliable data from non-reliable data; input the first and second sets of analysis parameters to a classifier, wherein the classifier is configured to determine, based on the input analysis parameters, at least one reliability classification for the input ultrasound data indicative of reliability of at least a portion of the input data for determining patient blood flow measurements using the ultrasound data or the data derived therefrom.
However, Tek teaches input the first and second sets of analysis parameters to a classifier ([0037] A machine-learnt classifier uses input features from both the B-mode and flow-mode data of the patient to detect the representations of the valve of the patient)
wherein the classifier is configured to determine, based on the input analysis parameters, at least one reliability classification for the input ultrasound data indicative of reliability of at least a portion of the input data for determining patient blood flow measurements using the ultrasound data or the data derived therefrom ([0007] An image processor is configured to fit a model of a heart valve over a heart cycle to the B-mode data with a machine-learnt classifier, to use the model to locate a cardiac flow area, and to calculate the cardiac flow from the Doppler flow data for the cardiac flow area. A display is configured to generate a visualization of the model over time as fit to the B-mode data, highlight the cardiac flow area, and indicate a value of the calculated cardiac flow. The location of the cardiac flow area is based, in part, on a confidence of the fit output by the machine-learnt classifier, and/or the display is configured to indicate a value of the confidence; [0004] Quantifying transvalvular blood flow directly provides additional cues via the flow over time. In addition, 3D flow quantification is potentially more accurate, as blood flow intensity may spatially vary)
Sato and Tek are considered analogous because both disclose ultrasonic imaging devices. Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the current invention to use a machine learning classification algorithm to make determinations regarding blood flow in order to resolve inaccuracies in calculating cardiac flow (Tek [0004]).
Sato in view of Tek fails to teach the second analysis procedure comprising wavelet decomposition adapted to derive wavelet coefficients to provide parameters used to distinguish reliable data from non-reliable data.
However, Yoo teaches wavelet decomposition adapted to derive wavelet coefficients to provide parameters used to distinguish reliable data from non-reliable data ([0016] aspects of the present invention provide a discrete wavelet transform-based noise removal apparatus which can effectively remove noise from an image while preserving details of the image containing useful information)
Sato and Yoo are considered analogous because both disclose image processing methods for ultrasound. Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the pending application to use a wavelet decomposition on the ultrasound image data in order to remove noise from an image while preserving details of the image containing useful information (Yoo [0016]).
Regarding claim 21, Sato fails to teach the ultrasound data processor is configured to generate a data output at the input/output indicative of the reliability classification.
However, Tek teaches the ultrasound data processor is configured to generate a data output at the input/output indicative of the reliability classification ([0006] An image of the cardiac flow value is output. The image indicates the confidence and/or the measurement area surface is placed based on the confidence and the detected heart valves over time).
Sato and Tek are considered analogous because both disclose ultrasonic imaging devices. Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the current invention to output an image which includes an indication of confidence in the calculation in order to resolve inaccuracies in calculating cardiac flow (Tek [0004]).
Regarding claim 22, Sato teaches the ultrasound data processor is configured to receive and process the input ultrasound data in real time ([0138] an FFT waveform has been generated in a real-time examination)
Regarding claim 23, Sato teaches the ultrasound data processor is further configured to process the input PWD ultrasound data to derive one or more blood flow measurements ([0003] The pulse wave Doppler (hereinafter, PWD) method is one method for displaying signals from a blood flow. In the PWD method, a Doppler waveform is generated by performing fast Fourier transform (FFT) on time-series data of signals received from the same location within a range defined by a range gate. In the PWD method, the power of a blood flow, expressed by use of luminance, is displayed with the horizontal axis representing time and the vertical axis representing frequencies)
Regarding claim 24, Sato fails to teach wherein the ultrasound data processor is configured to determine a reliability of each of the one or more blood flow measurements based on the reliability classification(s) for the ultrasound data.
However, Tek teaches wherein the ultrasound data processor is configured to determine a reliability of each of the one or more blood flow measurements based on the reliability classification(s) for the ultrasound data ([0005] A confidence of the detection may be used to indicate confidence of calculated quantities and/or the actual presence of the valve).
Sato and Tek are considered analogous because both disclose ultrasonic imaging devices. Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the current invention to determine a confidence value on multiple measured values in order to resolve inaccuracies in calculating cardiac flow (Tek [0004]).
Response to Arguments
Applicant’s arguments, see pages 8-13, filed 10/7/2025, with respect to the rejection(s) of the independent claims under 35 USC 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of the newly cited Yoo reference. Applicant has filed a supplemental amendment in light of an interview further defining the process of wavelet decomposition as claimed in the current application, changing the scope of the scope of the claims and overcoming the previously issued rejection. However, an updated search has uncovered the newly cited Yoo reference which goes into detail on how the process of wavelet decomposition is used to reduce noise in ultrasonic images. Thus, when taken in their totality, the combination of cited references obviates every limitation of the independent claims to one of ordinary skill in the art. For at least the aforementioned reasons, the claims remain rejected under 35 USC 103.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GABRIEL VICTOR POPESCU whose telephone number is (571)272-7065. The examiner can normally be reached M-F 8AM-5PM.
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/GABRIEL VICTOR POPESCU/Examiner, Art Unit 3798
/PASCAL M BUI PHO/Supervisory Patent Examiner, Art Unit 3798