DETAILED ACTION
This action is in response to the remarks and amendments filed on February 1st, 2026. Claims 1-27 are pending and have been examined.
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 “Remarks”, filed February 1st, 2026, with respect to objection to the specification, objections to the claims, the invocation of 35 U.S.C. 112(f), and the rejections under 35 U.S.C. 112(a) and 112(b) have been fully considered and are persuasive. Therefore, the objection to the specification, the objection to claims 1 and 2, the invocation of 35 U.S.C. 112(f) to claims 14 and 27, and the 35 U.S.C. 112(a) and 112(b) rejections to claims 14-27 are withdrawn.
Applicant's arguments with respect to the 35 U.S.C. 103 rejections of claim 1-2, 14-15, and 27 have been fully considered but they are not persuasive.
Applicant alleges that “Hsieh fails to teach or suggest, inter alia, ‘a standard deviation calculation step of calculating a noise standard deviation in the radiographic image of the subject, by substituting the count number in the subject area into the basic noise deviation function.’… Figure 3 in Hsieh merely shows a relation between a value of the count number and a value of the noise in image. And ‘a value of the noise’ is clearly different from ‘a value of the noise standard deviation.’ Thus, Hsieh does not show a relationship between a value of the count number and a value of the noise standard deviation. Therefore, Hsieh does not disclose ‘a basic noise deviation function’ that is a function that indicates a relation between a value of the count number and a value of the noise standard deviation. Hsieh merely discloses a function that indicates a relation between a value of the count number and a value of the noise.” Examiner respectfully disagrees.
Hsieh teaches, in figure 3, that “total counts” are correlated with “pixel value std”, which can best be understood to mean x-ray photon counts are correlated with pixel value standard deviation. Furthermore, section III paragraph 3 reads “Figure 3 shows image noise response to x-ray photon counts.” These portions together show that figure 3 can best be understood to be showing a relationship between image noise value standard deviation and x-ray photon counts. Therefore, the rejection is maintained.
Claim Interpretation
In the independent claims, the claim language of calculating “a count number” can be understood broadly to mean any count of any number. However, in this context, the count number refers to a count of particles (in this case, a pair of y-rays, also known as “Line of Response”) which were detected while a PET scan. The broadest reasonable interpretation of this term, in this context, is then understood to mean a count number of particles which are used to perform a tomographic scan. Evidence for this can be found in the specification, paragraph [0046] and [0051].
The claim term “NLM” is not well defined by the claims. However, this term can be best understood to mean “Non-Local Means”, and therefore will be interpreted as such.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-2, 14-15, and 27 are rejected under 35 U.S.C. 103 as being unpatentable over “Compound Poisson Noise Verification for X-ray Flat Panel Imager” (herein after referred to by its primary author, Hsieh) in view of “Non-Local Means Denoising of Dynamic PET Images” (herein after referred to by its primary author, Dutta).
In regards to claim 1, Hsieh teaches an image processing method comprising: a step of acquiring a plurality of function calculation radiographic images (Hsieh Figure 1; Section II B, Paragraph 2 “Object-free noisy images were then measured under the FPD radiography mode, with 427×427 mm2 full field-of-view, 1 frame-per-second (fps), 1×1 pixel binning and 3072×3072 image size”); a step of calculating a count number in the plurality of function calculation radiographic images and a noise standard deviation in the plurality of function calculation radiographic images (Hsieh Section II C, Paragraph 1 “To verify the compound-Poisson noise property in the FPD images, central 80% area of x-ray field-of-view in FPD images were selected as region-of-interest (ROI) for standard deviation measurements. Measured data were compared with entrance FPD air dose, x-ray photon counts and the Poisson std-index.”); a step of preparing a basic noise deviation function that indicates a relation between a count number and a noise standard deviation based on the count number in the plurality of function calculation radiographic images and the noise standard deviation in the plurality of function calculation radiographic images; a step of storing the basic noise deviation function (Hsieh Figure 3; Figure 3 description “Solid line with error bars in the right plot are the result and error of second-order polynomial fit, MSE of the fitting points is 21.9985.”); a reconstruction step of reconstructing a radiographic image of a subject by performing reconstruction processing on radiological data of the subject (Hsieh Section II B, Paragraph 2 “Object-free noisy images were then measured under the FPD radiography mode, with 427×427 mm2 full field-of-view, 1 frame-per-second (fps), 1×1 pixel binning and 3072×3072 image size”); a count number calculation step of calculating a count number in a subject area in the radiographic image of the subject (Hsieh Section II C, Paragraph 1 “To verify the compound-Poisson noise property in the FPD images, central 80% area of x-ray field-of-view in FPD images were selected as region-of-interest (ROI) for standard deviation measurements. Measured data were compared with entrance FPD air dose, x-ray photon counts and the Poisson std-index.”); and a standard deviation calculation step of calculating a noise standard deviation in the radiographic image of the subject, by substituting the count number in the subject area into the basic noise deviation function (Hsieh Figure 3; Section II C, Paragraph 3 “Figure 3 shows image noise response to x-ray photon counts…The overall response is presented as a second-order polynomial fit, that the fitting line is better correlated to the measured data. Mean square error of the fitting points is decrease to 21.9985, or 4.82% error.”)
Hsieh does not teach a noise reduction processing step of performing NLM filter processing on the radiographic image of the subject, using the noise standard deviation calculated in the standard deviation calculation step.
However, Dutta teaches a reconstruction step of reconstructing a radiographic image of a subject by performing reconstruction processing on radiological data of the subject (Dutta Methods, Paragraph 1 “In order to generate a realistic simulation environment for testing the NLM denoising technique for dynamic PET images, we constructed a dynamic digital mouse phantom”); and a noise reduction processing step of performing NLM filter processing on the radiographic image of the subject, using the noise standard deviation calculated in the standard deviation calculation step (Dutta Methods, Paragraph 5 “In order to assess the performance of NLM relative to other denoising techniques for dynamic PET, we compare the denoising capability of this method with four other denoising approaches” Examiner note: This section teaches that NLM denoising is performed on a radiographic (PET) image, and then the performance is compared to other denoising techniques. The NLM of this reference could be performed using the standard deviation calculated before, as Dutta teaches that NLM is performed using a smoothing parameter, which relies on the noise standard deviation (See Dutta Theory, Paragraph 11 “Smoothing Parameter”)).
Dutta is considered to be analogous to the claimed invention because they are both in the same field of denoising PET images. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Hsieh to include the teachings of Dutta, to provide the advantage of an increase noise to contrast ratio, resulting in clearer images with detail and low noise. (Dutta Abstract Results “The simulation study revealed significant improvement in bias-variance performance achieved using our NLM technique relative to all the other methods. The experimental data analysis revealed that our technique leads to clear improvement in contrast-to-noise ratio in Patlak parametric images generated from denoised preclinical and clinical dynamic images, indicating its ability to preserve image contrast and high intensity details while lowering the background noise variance.”)
In regards to claim 2, Hsieh in view of Dutta teaches the image processing method as recited in claim 1, wherein a basic noise standard deviation σt in the basic noise deviation function is calculated by a following
σt = a1 * Na2 + a3
using the count number N in the subject area, and a first count model coefficient at, a second count model coefficient a2, and a third count model coefficient a3, the first count model coefficient at, the second count model coefficient a2, and the third count model coefficient a3 being obtained from a relation between the count number in each of the plurality of function calculation radiographic images and the noise standard deviation in each of the plurality of function calculation radiographic images, and wherein the noise standard deviation σ in the noise reduction processing step satisfies a condition of σ = σt. (Hsieh Figure 3 Description “The left plot is measured standard deviations of incident x-ray photon count with kVp settings, line of the responses has slight differences on its slope. Solid line with error bars in the right plot are the result and error of second-order polynomial fit, MSE of the fitting points is 21.9985.” Examiner note: A second order polynomial fit uses the equation y = a3 + a4 * x + a1 * x2. In this scenario, a1 and a3 are found in the same form, and a2 is equal to 2.)
In regards to claim 14, Hsieh in view of Dutta renders obvious the claim limitations as in the consideration of claim 1.
In regards to claim 15, Hsieh in view of Dutta renders obvious the claim limitations as in the consideration of claim 2.
In regards to claim 27, Hsieh in view of Dutta teaches a radiation detector configured to detect radiation transmitted through a subject and output radiation data (Hsieh Section II B “A laboratory x-ray imaging system consisting of an x-ray source, filter stage, and a FPD was constructed to verify the FPD image noise property in planar radiography.”) and renders obvious the remaining claim limitations as in the consideration of claim 14.
Allowable Subject Matter
Claims 3-13 and 16-26 are 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.
The following is a statement of reasons for the indication of allowable subject matter:
Dependent claims 3 and 16: The limitations of this claim require the standard deviation calculation step as recited in claim 1, and further requires that a standard deviation correction value be calculated from a value used in the reconstruction processing, this standard deviation correction value is then used to change the original standard deviation calculated in claim 1. While this claim is broad in that it merely requires the changing of the standard deviation by some value, it is also narrow in that the standard deviation must be calculated from a relation between a count number and that the value used to correct the standard deviation must be obtained from a relation between a value used in the reconstruction processing and the correction value, which is obtained from previously acquired images. The prior art of record does not teach these limitations alone or in combination. However, claims 16 is also rejected under 35 U.S.C. 112(a) and 112(b). These deficiencies must be overcome before allowability.
Dependent claims 4-13 and 17-26: These claims are dependent upon a claim which contains allowable subject matter, and therefore contain allowable subject matter not taught by the prior art of record. However, claims 17-26 are also rejected under 35 U.S.C. 112(a) and 112(b). These deficiencies must be overcome before allowability.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
“Information-Adaptive Denoising for Iterative PET Reconstruction” teaches a method of denoising PET images. Specifically, in figure 9, images with different counts/acquisition times are compared, with more counts showing less noise.
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.
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/CALEB L ESQUINO/Examiner, Art Unit 2677
/ANDREW W BEE/Supervisory Patent Examiner, Art Unit 2677