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 .
Election/Restrictions
Applicant’s response to the restriction requirement without traverse in the reply mailed 3/18/2026 is acknowledged.
Claims 1-16, 18, and 20-23 remain pending in the current application.
Claim Interpretation
Claim 5 recites the newly amended limitation of “whether the signal value corresponding to the position is greater” which in an interpretation it may be construed as a conditional limitation where the conditional limitations may not be given a full weight in light of the below decisions.
In the recent Ex parte Gopalan decision, the PTAB addressed a claim where all of the features were recited in a conditional manner. A first step of “identifying … an outlier” was performed if “traffic is outside of a prediction interval.” A second step of “identifying” was performed “only when a count of outliers … is greater than or equal to two, and exceeds an anomaly threshold.” These were the only two elements of the independent claim. Thus, if the traffic is never outside Gopalan’s prediction interval, then the steps of the method are never performed.
However, the PTAB distinguished Schulhauser and noted that this construction “would render the entire claim meaningless.” Gopalan at p. 5. The Board went on to state, “Although each of these steps is conditional, they are integrated into one method or path and do not cause the claim to diverge into two methods or paths, as in Schulhauser. Thus, we conclude that the broadest reasonable interpretation of claim 1 requires the performance of both steps…” Id. at p. 6.”
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites extracting identification information. The limitation of extracting identification information as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting processing circuitry nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the processing circuitry language, extracting identification information in the context of this claim encompasses the user manually observing a sonograph. Similarly, the limitation of identifying a local peak, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. For example, but for the processing circuitry language, identifying a local peak in the context of this claim encompasses the user observing a sonograph. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. This judicial exception is not integrated into a practical application. In particular, the claim only recites one additional element – using a processor to perform the steps of identifying. The processor in both steps is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of ranking information based on a determined amount of use) such that it amounts no more than mere instructions to apply the exception using a generic computer component. 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. The claim is directed to an abstract idea. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor to perform both the steps of identifying amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible.
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.
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim 1 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.
Claim 1 recites the limitation ‘a local peak’. It is unclear what this is a local peak to (or local peak of what) and thus the claim is indefinite. Dependent claims are rejected as well by virtue of their dependency.
Claim 9 rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. The limitations of dependent claim 9 have already been recited in the independent claim. Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
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.
Claim(s) 1-16 and 20-23 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Song (US 20200178939 A1).
Regarding claim 1, Song teaches an ultrasonic diagnostic apparatus ([0006] method for super-resolution imaging of microvessels using an ultrasound system)
an ultrasonic probe configured to transmit an ultrasonic wave to a subject, and receive the ultrasonic wave reflected by the subject ([0094] When energized by a transmitter 1806, each transducer element 1802 produces a burst of ultrasonic energy. The ultrasonic energy reflected back to the transducer array 1802 from the object or subject under study (e.g., an echo) is converted to an electrical signal (e.g., an echo signal) by each transducer element 1804 and can be applied separately to a receiver 1808 through a set of switches 1810)
and processing circuitry configured to acquire first ultrasonic data of the subject ([0094] The transmitter 1806, receiver 1808, and switches 1810 are operated under the control of a controller 1812, which may include one or more processors. As one example, the controller 1812 can include a computer system)
based on the ultrasonic wave received by the ultrasonic probe, extract identification information that identifies a position of a local peak for each predetermined region of a frame represented by the first ultrasonic data ([0056] The center location of each microbubble can then be estimated, as indicated at step 312. In some implementations, the center location can be estimated by identifying the local regional maximum of the thresholded cross-correlation coefficient map. In some other implementations, the center location can be estimated by performing a curve-fitting to the cross-correlation map to find the local maximum location. An example output of the localization is shown in FIG. 6, where the crosses indicate the estimated center locations of microbubbles. The localization process is conducted on each frame of the microbubble data until all microbubble events are identified and localized)
and output second ultrasonic data, based on the extracted identification information, and ultrasonic data representing an object to be processed ([0099] The separate echo signals from each transducer element 1804 can be combined in the receiver 1808 to produce a single echo signal. Images produced from the echo signals can be displayed on a display system 1814).
Regarding claim 2, Song teaches the processing circuitry is configured to extract the identification information, by identifying a position where a signal value is relatively high as the position of the local peak for each local region of the frame represented by the first ultrasonic data ([0056] The center location of each microbubble can then be estimated, as indicated at step 312. In some implementations, the center location can be estimated by identifying the local regional maximum of the thresholded cross-correlation coefficient map. In some other implementations, the center location can be estimated by performing a curve-fitting to the cross-correlation map to find the local maximum location. An example output of the localization is shown in FIG. 6, where the crosses indicate the estimated center locations of microbubbles. The localization process is conducted on each frame of the microbubble data until all microbubble events are identified and localized)
Regarding claim 3, Song teaches the processing circuitry is configured to acquire a plurality of the first ultrasonic data within a predetermined time, extract the identification information that identifies the position of the local peak, for each frame represented by the first ultrasonic data, and output the second ultrasonic data, based on the identification information extracted for each of the frames, and the ultrasonic data ([0058] As one example, microbubble tracking can be implemented by locally tracking a single microbubble's movement. As shown in FIG. 7, this local tracking method typically uses a local window 702 to track a single microbubble's movement through time. As one example, two-dimensional cross-correlation can be used to track the microbubble's movement through time. The original microbubble signal in frame n 704 is tracked in frames n+1, n+2, n+3, and n+4, as indicated by dashed circles 706. The true microbubble movement trajectory is indicated by 708).
Regarding claim 4, Song teaches at each position in the frame, the processing circuitry is configured to extract information that identifies a magnitude relation between a signal value corresponding to the position and a signal value corresponding to a surrounding area of the position, as the identification information ([0045] denoising can be implemented using an intensity-based thresholding method. Such methods are more accurate when it can be assumed that the microbubble signals are stronger than the background noise signals. For example, by suppressing pixels with intensity values less than a selected value (e.g., −30 dB to the maximum intensity value in the current field-of-view), a significant amount of background noise can be suppressed).
Regarding claim 5, Song teaches at each position in the frame, the processing circuitry is configured to extract information that identifies whether the signal value corresponding to the position is greater than the signal value corresponding to the surrounding area of the position, as the identification information ([0045] denoising can be implemented using an intensity-based thresholding method. Such methods are more accurate when it can be assumed that the microbubble signals are stronger than the background noise signals. For example, by suppressing pixels with intensity values less than a selected value (e.g., −30 dB to the maximum intensity value in the current field-of-view), a significant amount of background noise can be suppressed).
Regarding claim 6, Song teaches the surrounding area is a position in a spatial direction and range with respect to the position, or a position in a temporal direction and range with respect to the position ([0046] As another example, the microbubble signals can be denoised based at least in part on the spatiotemporal information contained in the microbubble signals. Because microbubbles move with blood flow, the microbubble movements are deterministic events that can be continuously tracked in multiple acquisition frames, while noise events are random and will not show any track-like features across multiple acquisition frames).
Regarding claim 7, Song teaches in a predetermined range of the frame, the processing circuitry is configured to extract information that identifies a position having a higher signal value than that of a surrounding area, as the identification information ([0045] denoising can be implemented using an intensity-based thresholding method. Such methods are more accurate when it can be assumed that the microbubble signals are stronger than the background noise signals. For example, by suppressing pixels with intensity values less than a selected value (e.g., −30 dB to the maximum intensity value in the current field-of-view), a significant amount of background noise can be suppressed).
Regarding claim 8, Song teaches the surrounding area is a position in a spatial direction and range with respect to the position, or a position in a temporal direction and range with respect to the position ([0046] As another example, the microbubble signals can be denoised based at least in part on the spatiotemporal information contained in the microbubble signals. Because microbubbles move with blood flow, the microbubble movements are deterministic events that can be continuously tracked in multiple acquisition frames, while noise events are random and will not show any track-like features across multiple acquisition frames).
Regarding claim 9, Song teaches at each position in the frame represented by the first ultrasonic data, the processing circuitry is configured to extract the identification information ([0056] The center location of each microbubble can then be estimated, as indicated at step 312)
Regarding claim 10, Song teaches the ultrasonic data representing the object to be processed is, at least one of a plurality of the first ultrasonic data, or ultrasonic data obtained by performing a predetermined process on the first ultrasonic data ([0015] FIG. 6 is an example of center locations of microbubbles identified on the microbubble signal data of FIG. 5, where the center locations were determined by identifying local regional maxima in the two-dimensional cross-correlation map of FIG. 4).
Regarding claim 11, Song teaches the processing circuitry is configured to generate filter information corresponding to each position in the frame, based on the identification information extracted from each of a plurality of the first ultrasonic data, and output the second ultrasonic data, based on the filter information and the ultrasonic data representing the object to be processed ([0071] In such instances when the microvessel image (e.g., microbubble location map, blood flow map) is spatially sparse, the image can be processed to recover data, as indicated at step 116. As one example, a two-dimensional spatial low-pass filter (e.g., a 2D Gaussian smoothing filter) can be used to “fill” or “inpaint” the blank regions among detected microbubble locations. FIG. 14 shows an example of using a 2D Gaussian smoothing filter on a sparse microbubble location map. After filtering, the sparse microvessel pixels are better connected, which makes it easier to interpret the microvessel structure. Other spatial filters such as the median filter or a weighted averaging filter based on pixel intensity can also be used to obtain similar results)
Regarding claim 12, Song teaches the processing circuitry is configured to assign weight information defined according to each of the first ultrasonic data to the identification ([0071] weighted averaging filter based on pixel intensity can also be used to obtain similar results)
Regarding claim 13, Song teaches the surrounding area with which the magnitude relation between the signal values is identified by the processing circuitry, is a position in a certain spatial direction and distance with respect to the position, or a position in a certain temporal direction and distance with respect to the position, and the processing circuitry is configured to assign weight information defined according to at least one of the direction and distance, to the identification information ([0046] As another example, the microbubble signals can be denoised based at least in part on the spatiotemporal information contained in the microbubble signals. Because microbubbles move with blood flow, the microbubble movements are deterministic events that can be continuously tracked in multiple acquisition frames, while noise events are random and will not show any track-like features across multiple acquisition frames. These differences between microbubbles and noise can be exploited in the spatiotemporal domain for robust noise suppression. As an example, a non-local means (“NLM”) denoising filter can be applied to the original, noisy microbubble data)
Regarding claim 14, Song teaches the processing circuitry is configured to acquire addition data that is obtained by performing ultrasonic scanning on a subject, and that is obtained by performing addition processing of a plurality of frame data continuous in a temporal direction, as the first ultrasonic data ([0046] As another example, the microbubble signals can be denoised based at least in part on the spatiotemporal information contained in the microbubble signals. Because microbubbles move with blood flow, the microbubble movements are deterministic events that can be continuously tracked in multiple acquisition frames, while noise events are random and will not show any track-like features across multiple acquisition frames. These differences between microbubbles and noise can be exploited in the spatiotemporal domain for robust noise suppression. As an example, a non-local means (“NLM”) denoising filter can be applied to the original, noisy microbubble data).
Regarding claim 15, Song teaches at each position in the frame represented by the first ultrasonic data, the processing circuitry is configured to set ultrasonic data obtained by performing a process of extracting a signal value corresponding to the position, based on a magnitude relation between a signal value corresponding to the position and a signal value corresponding to a surrounding area of the position, as the ultrasonic data obtained by performing the predetermined process, and output the second ultrasonic data, based on the ultrasonic data and the identification information ([0045] As one example, denoising can be implemented using an intensity-based thresholding method. Such methods are more accurate when it can be assumed that the microbubble signals are stronger than the background noise signals. For example, by suppressing pixels with intensity values less than a selected value (e.g., −30 dB to the maximum intensity value in the current field-of-view), a significant amount of background noise can be suppressed. However, these methods may not be as accurate in regions where microbubble signals are similar to noise (e.g., deep regions of the tissue). Also, the threshold value has to be carefully chosen to avoid falsely rejecting the microbubble signal or preserving too much noise)
Regarding claim 16, Song teaches at each position in the frame represented by the first ultrasonic data, the processing circuitry is configured to set synthetic data in which ultrasonic data obtained by performing a process of extracting a signal value corresponding to the position, based on a magnitude relation between a signal value corresponding to the position and a signal value corresponding to a surrounding area of the position is synthesized with the first ultrasonic data, as the ultrasonic data obtained by performing the predetermined process, and output the second ultrasonic data, based on the ultrasonic data and the identification information ([0099] The separate echo signals from each transducer element 1804 can be combined in the receiver 1808 to produce a single echo signal. Images produced from the echo signals can be displayed on a display system 1814; [0096] the detection sequence can include … synthetic aperture imaging).
Regarding claim 20, Song teaches at each position in the frame, the processing circuitry is configured to extract information that identifies variance between a signal value corresponding to the position and a signal value corresponding to a surrounding area of the position, as the identification information ([0056] The center location of each microbubble can then be estimated, as indicated at step 312. In some implementations, the center location can be estimated by identifying the local regional maximum of the thresholded cross-correlation coefficient map. In some other implementations, the center location can be estimated by performing a curve-fitting to the cross-correlation map to find the local maximum location. An example output of the localization is shown in FIG. 6, where the crosses indicate the estimated center locations of microbubbles. The localization process is conducted on each frame of the microbubble data until all microbubble events are identified and localized).
Regarding claim 21, Song teaches the processing circuitry is configured to acquire three-dimensional ultrasonic data, for each of the first ultrasonic data of the subject ([0047] full axial-lateral-temporal 3D data can also be used).
Regarding claim 22, Song teaches a mode of extracting the identification information, the processing circuitry is configured to acquire the first ultrasonic data collected by increasing line density ([0088] Vessel density can be calculated by selecting a region-of-interest on the microvessel image, from which the vessel density can be calculated by the total area (or total volume as in 3D imaging) of the vessel signal divided by the total area (or volume) of the region-of-interest).
Regarding claim 23, Song teaches the processing circuitry is configured to extract the identification information, by dividing the first ultrasonic data into a plurality of division data, generating extraction data in which the position of the local peak is extracted for each division data, and allocating each extraction data to a corresponding position on the first ultrasonic data ([0099] The separate echo signals from each transducer element 1804 can be combined in the receiver 1808 to produce a single echo signal. Images produced from the echo signals can be displayed on a display system 1814).
Claim Rejections - 35 USC § 103
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) 18 is rejected under 35 U.S.C. 103 as being unpatentable over Song as applied to claim 1 above, and further in view of Torp (US 20190223828 A1).
Regarding claim 18, Song fails to teach the processing circuitry is configured to acquire the first ultrasonic data obtained by performing ultrasonic scanning in absence of a contrast agent.
However, Torp teaches the processing circuitry is configured to acquire the first ultrasonic data obtained by performing ultrasonic scanning in absence of a contrast agent ([0018] speckle patterns from fluid moving within the living organism are sharpened with a peak-sharpening operation that enhances their effective resolution, and are superimposed across multiple image frames. It is thereby possible to generate an output image showing the fluid path at a resolution (in at least one direction) that can be finer than the resolution limit (in that direction) of the ultrasound transceiver system that generated the data…It also does not require a contrast agent to be injected into the organism).
Song and Torp are considered analogous because both disclose ultrasonic diagnostic systems to be utilized in blood vessels. 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 carry out the diagnosis without the use of a contrast agent so that enhanced-resolution imaging can be carried out much more quickly than the prior approach described above, using a much shorter sequences of images (Torps [0018]).
Conclusion
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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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Anne Kozak can be reached at (571) 270-0552. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/GABRIEL VICTOR POPESCU/ Examiner, Art Unit 3797
/SERKAN AKAR/ Primary Examiner, Art Unit 3797
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