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 .
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
Use of the word “means” (or “step for”) in a claim with functional language creates a rebuttable presumption that the claim element is to be treated in accordance with 35 U.S.C. § 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph). The presumption that § 112(f) (pre-AIA § 112, sixth paragraph) is invoked is rebutted when the function is recited with sufficient structure, material, or acts within the claim itself to entirely perform the recited function.
Absence of the word “means” (or “step for”) in a claim creates a rebuttable presumption that the claim element is not to be treated in accordance with 35 U.S.C. § 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph). The presumption that § 112(f) (pre-AIA § 112, sixth paragraph) is not invoked is rebutted when the claim element recites function but fails to recite sufficiently definite structure, material or acts to perform that function.
Claim elements in this application that use the word “means” (or “step for”) are presumed to invoke § 112(f) except as otherwise indicated in an Office action. Similarly, claim elements that do not use the word “means” (or “step for”) are presumed not to invoke § 112(f) except as otherwise indicated in an Office action.
Each claim limitation “unit” (a data acquisition unit, an estimation processing unit, an image display unit, the k-space estimation processing unit, and the image-space estimation processing unit) has/have been interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because it uses/they use a generic placeholder “unit” coupled with functional language without reciting sufficient structure to achieve the function. Furthermore, the generic placeholder is not preceded by a structural modifier.
Since the claim limitation(s) invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, claim(s) 1-9 has/have been interpreted to cover the corresponding structure described in the specification that achieves the claimed function, and equivalents thereof.
A review of the specification shows that the following appears to be the corresponding structure described in the specification for the 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph limitation: a computer that is programmed to perform all claim functions as described in paragraph [0025].
If applicant wishes to provide further explanation or dispute the examiner’s interpretation of the corresponding structure, applicant must identify the corresponding structure with reference to the specification by page and line number, and to the drawing, if any, by reference characters in response to this Office action.
If applicant does not intend to have the claim limitation(s) treated under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112 , sixth paragraph, applicant may amend the claim(s) so that it/they will clearly not invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, or present a sufficient showing that the claim recites/recite sufficient structure, material, or acts for performing the claimed function to preclude application of 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
For more information, see M.P.E.P. § 2173 et seq. and Supplementary Examination Guidelines for Determining Compliance With 35 U.S.C. 112 and for Treatment of Related Issues in Patent Applications, 76 FR 7162, 7167 (Feb. 9, 2011).
Claim 10 is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because they are all method claims.
Claim 11 is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because it is an article of manufacture claim.
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 5-6 are 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 recites the limitation “the k-space estimation processing unit” in line 4 and “the image-space estimation processing unit” in line 8. There is insufficient antecedent basis for this limitation in the claim.
Regarding claim 6 depends on claim 5 and thus is rejected for the same reasons as above.
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, 4 and 10-11 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Takeshima (U.S. Pat. App. Pub. No. 2013/0285662 A1, referred as Takeshima hereinafter).
Regarding claim 1 as a representative claim, Takeshima teaches an image processing apparatus comprising:
a data acquisition unit configured to acquire lower-density sampling k-space raw data obtained by imaging a subject by thinning-out measurement points by an MRI apparatus and output input data based on the lower-density sampling k-space raw data (see figure 1 (MRI apparatus 100; acquiring unit 126a; k-space data generating unit 126c; patient P as a subject); paras. [0033] (k-space data acquired by the acquiring unit 126a), [0038] (sampling density in the central part of the k-space is higher than the sampling density in the peripheral part), [0040] (less dense sampling k-space data; thinned-out k-space data), [0037] (MRI apparatus acquires k-space data by performing down-sampling process at regular interval and estimates the thinned-out data), [0041] (MRI apparatus 100 acquires the pieces of data that are thinned) and [0045] (a k-space data is thinned-out);
an estimation processing unit configured to perform estimation processing by inputting the input data into a learned model and output recovered image data whose image quality reduced by the thinned-out measurement points has been recovered (see para. [0036] (MRI apparatus acquires k-space data for a training purpose in advanced (learned model) and performs a reconstructing process on the acquired k-space data); and
an image display unit configured to display the recovered image data (see para. [0027] (display unit 125).
Regarding claim 4, Takeshima further teaches wherein the data acquisition unit outputs image data obtained by performing inverse Fourier transform on the lower-density sampling k-space raw data to the estimation processing unit as the input data (see para. [0003] (inverse Fourier transform), and
the estimation processing unit is configured as an image-space estimation unit configured to perform estimation processing by inputting the transformed image data into the learned model and to output the recovered image data whose image quality reduced by the thinned-out measurement points has been recovered (see para. [0036] (MRI apparatus acquires k-space data for a training purpose in advanced (learned model) and performs a reconstructing process on the acquired k-space data).
Regarding claim 10, it is noted that this claim recites similar claim limitations called for in the counterpart claim 1 and thus is rejected for the same reasons as above.
Regarding claim 11, it is noted that this claim recites similar claim limitations called for in the counterpart claim 1. Thus, the advanced statements as applied to claim 1 above is incorporated hereinafter. Takeshima further teaches a non-transitory computer-readable medium, program, and a computer (see para. [0095] (computer program, computer system, medium)).
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.
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Takeshima in view of Suzuki et al. (U.S. Pat. App. Pub. No. 2003/0194124 A1, referred as Suzuki hereinafter).
The advanced statements as applied to claim 1, 4, and 10-11 above are incorporated hereinafter.
Regarding claim 9, Takeshima does not teach claim limitations “wherein the learned model is a network constructed by inputting learning data and teacher data into a network configured as a MTANN (Massive-Training Artificial Neural Network) to perform learning”.
However, such claim limitations are well known in the art as evidenced by Suzuki.
Suzuki, in the same field of endeavor that of medical image processing, teaches Massive Training Artificial Neural Network (see figure 1, MTANN 100).
The motivation for doing so is to improve image quality as suggested by Suzuki (see para. [0233]).
Therefore, before the effective filing date of the instant claim invention, it would have been obvious to one of ordinary skill in the art to incorporate such claim limitations as taught by Suzuki in combination with Takeshima for that reasons.
Allowable Subject Matter
Claims 2-3, and 7-8 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Claims 5-6 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding claim 2 as a representative claim, the cited prior art does not teach or suggest claim limitations “wherein the data acquisition unit converts the lower-density sampling k-space raw data into interpolated k-space raw data by interpolating the thinned-out measurement points and outputs the interpolated k-space raw data to the estimation processing unit as the input data, and the estimation processing unit is configured as a k-space estimation processing unit configured to perform estimation processing by inputting the interpolated k-space raw data into the learned model, output estimated k-space raw data whose image quality reduced by the thinned-out measurement points has been recovered, and output the recovered image data reconstructed by performing inverse Fourier transform on the estimated k-space raw data”.
Claim 3 depends on claim 2 and thus is allowable for the same reasons.
Regarding claim 5 as a representative claim, the cited prior art does not teach or suggest claim limitations “wherein in the estimation processing unit, one or more k-space estimation processing units and one or more image-space estimation processing units are arranged in series, the k-space estimation processing unit performs estimation processing by inputting k-space raw data, which is input data, into the learned model, outputs the k-space raw data whose image quality has been recovered, and outputs second image data reconstructed by performing inverse Fourier transform on the k-space raw data, the image-space estimation processing unit performs estimation processing by inputting the image data, which is input data, into the learned model, and outputs image data whose image quality has been recovered, when the k-space estimation processing unit is arranged in the latter stage of the image space estimation processing unit, an inverse image reconstruction unit is provided between the image-space estimation processing unit and the k-space estimation processing unit to output k-space raw data, which is inversely reconstructed by performing inverse Fourier transform on image data output from the image-space estimation processing unit in the former stage, to the k-space estimation processing unit in the latter stage, and image data output from the end of serial array of the k-space estimation processing unit and the image-space estimation processing unit is output as the recovered image data”.
Claim 6 depends on claim 5 and thus is allowable for the same reasons.
Regarding claim 7 as a representative claim, the cited prior art does not teach or suggest claim limitations “wherein the data acquisition unit reads learning data that is lower-density sampling k-space raw data obtained in advance by imaging the subject with thinning-out the measurement points by the MRI apparatus and teacher data that is high-density sampling k-space raw data obtained in advance by imaging the subject without thinning-out the measurement points by the MRI apparatus, and outputs learning input data based on the learning data and the teacher data that have been read to the estimation processing unit, and the estimation processing unit constructs the learned model by performing supervised learning according to the learning input data”.
Regarding claim 8 as a representative claim, the cited prior art does not teach or suggest claim limitations “wherein the data acquisition unit reads learning data obtained by reconstructing lower-density sampling k-space raw data obtained in advance by imaging the subject with thinning-out the measurement points by the MRI apparatus and teacher data obtained by reconstructing high density sampling k-space raw data obtained in advance by imaging the subject without thinning-out the measurement points by the MRI apparatus, and outputs learning input data based on the learning data and the teacher data that has been read to the estimation processing unit, and the estimation processing unit constructs the learned model by performing supervised learning based on the learning input data”.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Nayak et a;. (U.S. Pat. App. Pub. No. 2017/0325709 A1) teaches k-space raw data (paras. 0045], [0064]),.
Itou (U.S. Pat. App. Pub. No. 2020/0142016 Al) teaches an MRI apparatus (100 of figures 1 and 10).
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DMD
3/2026
/DUY M DANG/Primary Examiner, Art Unit 2662