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 Arguments
Applicant’s arguments, see applicant arguments/remarks, filed 02/24/2026, with respect to the previous 112 rejections have been fully considered and are persuasive. The previous 112 rejections have been withdrawn.
Applicant's arguments filed 02/24/2026 regarding the previous prior art rejections have been fully considered but they are not persuasive.
The applicant argues that prior art Ran does not teach calculate consistency data for constraining consistency between data of the frequency domain scan data that has not been optimized and the optimized frequency domain scan data, and optimize the frequency domain scan data, based on (1) the calculated consistency data, (2) the generated image domain corrected data, and (3) the generated frequency domain corrected data, as recited in amended Claim 1. The applicant further argues that the Ran reference merely discloses the use of a k-space consistency module and spatial-domain consistency module in a series of blocks to form a reconstructed image. The Ran reference is silent regarding the specific features recited in amended Claim 1 with respect to the calculated consistency data and the optimization of the frequency domain scan data based on three types of data, for example.
The examiner respectfully disagrees. It is believed that Ran teaches the argued limitations. First, Ran teaches “calculate consistency data for constraining consistency between data of the frequency domain scan data that has not been optimized and the optimized frequency domain scan data” [Fig. 3, see KDC in later blocks (such as third or fourth block) of the pipeline wherein the k-space data has been optimized/corrected by previous CNN in previous blocks and the other data is original undersampled k-space data y. See data consistency. See Pages 3-5. See Fig. 3. See Equation 2-3 and corresponding description. See also rest of reference.]. Ran also teaches optimize the frequency domain scan data, based on (1) the calculated consistency data, (2) the generated image domain corrected data, and (3) the generated frequency domain corrected data [Fig. 3, see last CNN for the k-space branch of the last block of the pipeline. See data consistency. See Fig. 3. See Pages 3-5. See Equation 2-3 and corresponding description. See also rest of reference.].
Therefore, it is believed that prior art Ran still applies to the current amended 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.
Claims 2-6, 9-13, and 16-19 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.
Regarding claim 2, the limitation “wherein optimization is performed a predetermined number of times on the frequency domain scan data” is now considered indefinite because claim 1 discloses two optimize limitations “optimize the frequency domain scan data based on the image domain corrected data and the frequency domain corrected data” and “optimize the frequency domain scan data, based on the calculated consistency data, the generated image domain corrected data, and the generated frequency domain corrected data”. Therefore, it is unclear which optimization is being referred to in claim 2.
Claims 3-6 are rejected for depending on claim 2. Claims 9 and 16 are rejected for the same reasons as claim 2 above. Claims 10-13 and 17-19 are rejected for depending on said claims.
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 1-3, 8-10, and 15-17 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Ran (“MD-Recon-Net: A Parallel Dual-Domain Convolutional Neural Network for Compressed Sensing MRI”).
Regarding claim 1, Ran teaches a magnetic resonance imaging apparatus, comprising:
a sequence controlling circuit configured to acquire undersampled frequency domain scan data by executing a pulse sequence while carrying out an undersampling process the frequency domain scan data being undersampled data[See undersampled k-space data. See also rest of reference.]; and
a processing circuit configured to
generate image domain corrected data of the frequency domain scan data, by correcting the frequency domain scan data in an image domain [See Fig. 3 and corresponding description. In Fig. 3, for instance, after the SF in the first block of the pipeline, the initial k-space data is corrected in by a CNN in the second block of the pipeline. Page 4. See also rest of reference.],
generate frequency domain corrected data of the frequency domain scan data by correcting the frequency domain scan data in a frequency domain [See Fig. 3 and corresponding description. In Fig. 3, see each CNN for each k-space branch. Page 4. See also rest of reference.,
optimize the frequency domain scan data based on the image domain corrected data and the frequency domain corrected data [See Pages 3-5. See Equation 2-3 and corresponding description. Fig. 3, see the CNN in the later blocks of the pipeline, where because of the fusing of data from different branches, the k-space data in the later blocks is corrected based on previous blocks’ k-space corrected data and image space corrected data. See also rest of reference.], and
reconstruct image data by using performing an inverse Fourier transform on the optimized frequency domain scan data to generate image domain data and by generating the image data based on the image domain data [Fig. 3, see IFT in later blocks of the pipeline. See also rest of reference.], wherein the processing circuit is configured to
calculate consistency data for constraining consistency between data of the frequency domain scan data that has not been optimized and the optimized frequency domain scan data [Fig. 3, see KDC in later blocks (such as third or fourth block) of the pipeline wherein the k-space data has been optimized/corrected by previous CNN in previous blocks and the other data is original undersampled k-space data y. See data consistency. See Pages 3-5. See Fig. 3. See Equation 2-3 and corresponding description. See also rest of reference.], and
optimize the frequency domain scan data, based on the calculated consistency data, the generated image domain corrected data, and the generated frequency domain corrected data [Fig. 3, see last CNN for the k-space branch of the last block of the pipeline. See data consistency. See Fig. 3. See Pages 3-5. See Equation 2-3 and corresponding description. See also rest of reference.].
Regarding claim 2, Ran teaches wherein optimization is performed a predetermined number of times on the frequency domain scan data [Fig. 3, see last CNN for the k-space branch of the last block of the pipeline. See Pages 3-5. See Equation 2-3 and corresponding description. See also rest of reference.], and the processing circuit is further configured to optimize the optimized frequency domain scan data, based on the image domain corrected data of the optimized frequency domain scan data and the frequency domain corrected data of the optimized frequency domain scan data [Fig. 3, see last CNN for the k-space branch of the last block of the pipeline. See data consistency. See Fig. 3. See Pages 3-5. See Equation 2-3 and corresponding description. See also rest of reference.].
Regarding claim 3, Ran further teaches wherein the processing circuit is further configured to generate frequency domain interpolated data by performing an interpolating process on the frequency domain scan data that has not been optimized [See fully sampled k-space data that is estimated. See also rest of reference.], and the processing circuit is further configured to optimize the optimized frequency domain scan data, based on the frequency domain interpolated data, the image domain corrected data of the optimized frequency domain scan data, and the frequency domain corrected data of the optimized frequency domain scan data [See Pages 2-4. See Equation 1-3. See also rest of reference.].
Claims 8 and 15 are rejected for the same reasons as claim 1 above.
Claims 9 and 16 are rejected for the same reasons as claim 2 above.
Claims 10 and 17 are rejected for the same reasons as claim 3 above.
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.
Claims 4-6, 11-13, and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over previously cited Ran, in view of Polak (US 2022/0326330).
Regarding claim 4, Ran teaches the limitations of claim 3, which this claim depends from.
Ran is silent in teaching wherein the processing circuit is further configured to calculate a sensitivity distribution map of a receiver coil, and the processing circuit is further configured to correct the frequency domain scan data based on the calculated sensitivity distribution map.
Polak further teaches wherein the processing circuit is further configured to calculate a sensitivity distribution map of a receiver coil, and the processing circuit is further configured to correct the frequency domain scan data based on the calculated sensitivity distribution map. [¶0031, ¶0069-0070. See also rest of reference.].
It would have been obvious to a person having ordinary skill in the art before the filing date to combine the teachings of Ran and Polak because both references are in the field of optimization processes in MRI and because Polak teaches it is known in the art to use a sensitivity distributions when performing data processing for undersampled k-space data [Polak - ¶0031, ¶0069-0070. See also rest of reference.].
Regarding claim 5, Ran and Polak teach the limitations of claim 4, which this claim depends from.
Ran further teaches wherein the processing circuit includes a neural network [See Fig. 3, which shows a CNN. See also rest of reference.].
Regarding claim 6, Ran and Polak teach the limitations of claim 5, which this claim depends from.
Ran further teaches wherein the neural network is a convolutional neural network [See Fig. 3, which shows a CNN. See also rest of reference.].
Claims 11 and 18 are rejected for the same reasons as claim 4 above.
Claim 12 is rejected for the same reasons as claim 5 above.
Claim 13 is rejected for the same reasons as claim 6 above.
Regarding claim 19, Ran and Polak teach the limitations of claim 18, which this claim depends from.
Ran further teaches wherein a neural network is used for correcting the frequency domain scan data, generating the image domain corrected data, generating the frequency domain corrected data, and generating the frequency domain interpolated data [See Fig. 3, which shows a CNN. See also rest of reference.].
Ran is silent in teaching on the basis of the sensitivity distribution map.
Polak further teaches correcting the frequency domain scan data on the basis of the sensitivity distribution map [¶0031, ¶0069-0070. See also rest of reference.].
It would have been obvious to a person having ordinary skill in the art before the filing date to combine the teachings of Ran and Polak because both references are in the field of optimization processes in MRI and because Polak teaches it is known in the art to use a sensitivity distributions when performing data processing for undersampled k-space data [Polak - ¶0031, ¶0069-0070. See also rest of reference.].
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US 2020/0305806 also teaches a neural network method for correcting image data.
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 RISHI R PATEL whose telephone number is (571)272-4385. The examiner can normally be reached Mon-Thurs 7 a.m. - 5 p.m..
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/RISHI R PATEL/Primary Examiner, Art Unit 2858
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