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 Arguments
The reply filed on 10 March 2026 has been entered. Applicant’s arguments with respect to claims 1-13, 20 and 22-25 have been considered and are persuasive, therefore the current rejection is also Non-final.
Claims 1-13, 20 and 22-25 are pending in this application and have been considered below. Claims 14-19 and 21 are canceled by the applicant.
Priority
Receipt is acknowledged that application is a National Stage application of PCT PCT/US21/25421. Priority to 63/006,513 with a priority date of 7 April 2020 is acknowledged under 35 USC 119(e) and 37 CFR 1.78.
Information Disclosure Statement
The IDS dated 14 August 2024 that has been previously considered remains placed in the application file. The IDSs dated 10 March 2026 and 11 March 2026 have been considered and placed in the application file.
1st 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.
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.
Claims 1, 11 and 23-25 (all claims except 2-10, 12-13, 20 and 22) are rejected under 35 U.S.C. 103 as obvious over US Patent Publication 2019 0325618 A1, (Yang et al.) The references are listed in a PTO-892 from the Office Action in which they are first used.
Claim 1
[AltContent: textbox (Yang et al. Fig. 3, showing a hybrid spectral model for reducing beam hardening errors.)]
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Regarding Claim 1, Yang et al. teach a method for reducing a beam-hardening artifact in CT imaging ("directed toward beam hardening correction of tomographic reconstructions," paragraph [0001]), the method comprising:
acquiring polychromatic CT projection data at each X-ray detector in a CT imaging system ("The Alvarez-Macovski (AM) model of X-ray attenuation is a function of two material properties: material density p and atomic number Z. When combined with dual-energy imaging and knowledge of the spectra, the AM model can work with a full polychromatic model for attenuation," paragraph [0029]);
determining a corrected projection value for each of the polychromatic CT projection data using a mapping operator ("reconstructions may not be fully beam hardened corrected due to using low-resolution data or the variance data. However, intermediate parameters obtained from the dual energy reconstruction, such as pZ3 and p, may be used in other methods disclosed herein to determine average parameter values and a simplification to make to the AM model to obtain a BHC reconstruction of a sample," paragraph [0045]) that comprises a hybrid spectral model ("In some embodiments, the AM model may be implemented in the forward projection 207. However, since the AM model has at least two variables, multiple scans and/or separate iterations of the method 201 at different energies may be required to fully solve the AM model. Additionally, the adjoint back projection of the AM model may further complicate the implementation of the method 201," paragraph [0043] where two variables teaches hybrid) that combines an idealized spectral model and empirical data, wherein the empirical data comprises air scan X-ray intensity data acquired at two different effective mean energies ("In either case, an x-ray spectrum for both scans will be used for scaling the forward projections to account for the spectral content of the x-ray beam(s). Although the reconstruction from performing the dual energy iteration reconstruction may be obtained, they obtained reconstructions may not be fully beam hardened corrected due to using low-resolution data or the variance data," paragraph [0045] where the model uses a model (idealized) and iteration reconstruction (empirical data));
and generating an artifact-corrected CT image by combining the corrected projection value of the polychromatic CT projection data ("The end result, however, may be a beam hardened corrected (BHC) reconstruction of a sample," paragraph [0044]).
It is recognized that the citations and evidence provided above are derived from potentially different embodiments of a single reference. Nevertheless, it 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 to employ combinations and sub-combinations of these complementary embodiments, because Yang et al. explicitly motivates doing so at least in paragraphs [0016], [0018] and [0089] including “Those skilled in the art will understand the other myriad ways of how the disclosed techniques may be implemented, which are contemplated herein and are within the bounds of the disclosure.” and otherwise motivating experimentation and optimization.
Claim 11
Regarding claim 11, Yang et al. teach the method of claim 1, wherein the polychromatic CT projection data acquisition is at an energy level of 120 kVp ("With regards to X-ray attenuation, material attenuation of photons in the 5-120 keV energy region for X-rays are mainly due to the effects of Photoelectric effect and Compton scattering," paragraph [0031]).
Claim 23
Regarding claim 11, Yang et al. teach the method of claim 1, wherein the corrected projection value is a monochromatic projection value ("However, we are still able to create a pseudo-adjoint operation which adheres to the concept of adjoint operations, and maintains the consistency of working with monochromatic data in volume space, and polychromatic data in intensity/attenuation space," paragraph [0074]).
Claim 24
Regarding claim 24, Yang et al. teach the method of claim 1, wherein acquiring polychromatic CT projection data comprises acquiring polychromatic CT projection data at each individual X-ray detector in the CT imaging system ("the techniques disclosed herein include a simple and straightforward method to incorporate the physics of polychromatic X-ray attenuation within iterative schemes," paragraph [0030]).
Claim 25
Regarding claim 25, Yang et al. teach the method of claim 1, wherein the polychromatic CT projection data acquisition is at an energy level of 80 kVp ("With regards to X-ray attenuation, material attenuation of photons in the 5-120 keV energy region for X-rays are mainly due to the effects of Photoelectric effect and Compton scattering," paragraph [0031]).
2nd Claim Rejections - 35 USC § 103
Claims 2-3, 6-10, 12-13, 20 and 22 (all remaining claims not objected to) are rejected under 35 U.S.C. 103 as obvious over US Patent Publication 2019 0325618 A1, (Yang et al.) in view of US Patent Publication 2006 0159223 A1, (Wu et al.). The references are listed in a PTO-892 from the Office Action in which they are first used.
Claim 2
Regarding Claim 2, Yang et al. teach the method of claim 1, as noted above.
Yang et al. is not relied upon to explicitly teach all of air scan data.
However, Wu et al. teach wherein the hybrid spectral model represents the acquired polychromatic CT projection data pp as a function of a corrected projection [AltContent: textbox (Wu et al. Fig. 3, showing using air scans to adjust spectral calibration vectors.)]
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value pm and includes a virtual filter calculated based on the acquired air scan X-ray intensity data ("System detection coefficients Xn(i) are determined from measurements of air scans through known beam filters or through air scans without beam filters, at a plurality of kVp's," paragraph [0044]).
Therefore, taking the teachings of Yang et al. and Wu et al. as a whole, it would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify “X-ray Beam Hardening Correction in Tomographic Reconstruction using the Alvarez-Macovski Attenuation Model” as taught by Yang et al. to use “Method and Apparatus for Correcting for Beam Hardening in CT images” as taught by Wu et al. The suggestion/motivation for doing so would have been that, “The purpose of spectral related calibrations in CT imaging systems is to generate a functional form or table that re-maps measured projection values (normalized and minus logged) to its corresponding x-ray path length.” as noted by the Wu et al. disclosure in paragraph [0005], which also motivates combination because the combination would predictably have a better calibration as there is a reasonable expectation that calibration means will improve over time and be informed by previous work; and/or because doing so merely combines prior art elements according to known methods to yield predictable results.
Claim 3
Regarding claim 3, Yang et al. teach the method of claim 2, as noted above.
Yang et al. is not relied upon to explicitly teach all of lookup tables.
However, Wu et al. teach wherein the mapping operator comprises a lookup table LUT for each X-ray detector in the CT imaging system, wherein each lookup table LUT contains k corrected projection values pm that correspond to discretized values of the acquired polychromatic CT projection data ppdiscrete that are separated by a discretization step size s ("More particularly, a mapping function Proj(i,kv,L)- Ideal(i,kv,L) is the spectral calibration, which can either be in the form of a look-up table or in some functional form," paragraph [0042]).
Yang et al. and Wu et al. are combined as per claim 2.
Claim 6
Regarding claim 6, Yang et al. teach the method of claim 3, as noted above.
Yang et al. is not relied upon to explicitly teach all of lookup tables.
However, Wu et al. teach wherein the lookup table is a first lookup table LUT_1 for a first CT scan energy level and the mapping operator comprises a second lookup table LUT_2 for a second CT scan energy level, wherein the second lookup table LUT_2 contains k' corrected projection values p'm that correspond to discretized values of CT projection data p’pdiscrete that are separated by a discretization step size s' ("calibrations for at least two different materials are used to determine at least one of a multiple-material calibration function or a multiple-material calibration look-up table. Both of these forms (i.e., the function and the table) have a number of input parameters equal to the number of materials. In either form, the multiple-material calibration is useful for providing accurate beam hardening related image artifact corrections," paragraph [0056]).
Yang et al. and Wu et al. are combined as per claim 2.
Claim 7
Regarding claim 7, Yang et al. teach the method of claim 2, wherein determining the corrected projection value pm for the acquired polychromatic CT projection data pp comprises calculating the corrected projection value pm using the hybrid spectral model by iterating though different values of pm to attain a CT projection value that approximates the acquired polychromatic CT projection data pp ("The algorithms are generated by various simplifications of the AM model (to reduce it from two material properties to a single variable) combined with some maximum likelihood iterative reconstruction method," paragraph [0056]).
Claim 8
Regarding claim 8, Yang et al. teach the method of claim 7, as noted above.
Yang et al. is not relied upon to explicitly teach all of Newtons method.
However, Wu et al. teach wherein calculating the corrected projection value pm using the hybrid spectral model comprises iterating though different values of pm using Newton's method to determine the value of pm that results in a projection value that best approximates the acquired polychromatic CT projection data pp ("Steps 114, 116, 118, and 120 can be iterated with different bowtie filter 19 shapes, if bowtie filter 19 ( or another adjustable filter) is present to obtain different mappings for different values of b(E,i)," paragraph [0043] where the interpretation of Newtons method is within the teachings of another adjustable filter).
Yang et al. and Wu et al. are combined as per claim 2.
Claim 9
Regarding claim 9, Yang et al. teach the method of claim 7, as noted above.
Yang et al. is not relied upon to explicitly teach all of second hybrid spectral model.
However, Wu et al. teach wherein the hybrid spectral model is a first hybrid spectral model for a first CT scan energy level and the mapping operator comprises a second hybrid spectral model for a second CT scan energy level ("Thus, an ideal spectral effect is modeled by simulation of an x-ray beam spectrum and its interaction with materials such as filters in the beam path and water phantoms. Deviation from the ideal model is determined from the measurements at multiple kVp's. Detector detection efficiency as a function of photon energy and any additional filtration in the beam path is modeled as a polynomial function directly as shown herein, or two distinct materials plus a polynomial, or any other smooth functional form," paragraph [0044]), and
wherein determining the corrected projection value pm for the acquired polychromatic CT projection data pp comprises identifying the CT scan energy level at which the polychromatic CT projection data was acquired, and calculating the corrected projection value pm using the hybrid spectral model corresponding to the identified CT scan energy level ("Thus, an ideal spectral effect is modeled by simulation of an x-ray beam spectrum and its interaction with materials such as filters in the beam path and water phantoms. Deviation from the ideal model is determined from the measurements at multiple kVp's. Detector detection efficiency as a function of photon energy and any additional filtration in the beam path is modeled as a polynomial function directly as shown herein, or two distinct materials plus a polynomial, or any other smooth functional form," paragraph [0044] ).
Yang et al. and Wu et al. are combined as per claim 2.
Claim 10
Regarding claim 10, Yang et al. teach the method of claim 1, as noted above.
Yang et al. is not relied upon to explicitly teach all of second effective mean energy.
However, Wu et al. teach wherein the air scan X-ray intensity data is acquired at a first effective mean energy and at a second effective mean energy ("System detection coefficients Xn(i) are determined from measurements of air scans through known beam filters or through air scans without beam filters, at a plurality of kVp's," paragraph [0044]).
Yang et al. and Wu et al. are combined as per claim 2.
Claim 12
Regarding claim 12, Yang et al. teach the method of claim 2, as noted above.
Yang et al. is not relied upon to explicitly teach all of air scans.
However, Wu et al. teach further comprising calculating the virtual filter for each X-ray detector of the CT imaging system using the air scan X-ray intensity data acquired at two different effective mean energies, wherein each virtual filter is made of a selected material and has a thickness ("Thus, an ideal spectral effect is modeled by simulation of an x-ray beam spectrum and its interaction with materials such as filters in the beam path and water phantoms. Deviation from the ideal model is determined from the measurements at multiple kVp's. Detector detection efficiency as a function of photon energy and any additional filtration in the beam path is modeled as a polynomial function directly as shown herein, or two distinct materials plus a polynomial, or any other smooth functional form," paragraph [0044] and "System detection coefficients Xn(i) are determined from measurements of air scans through known beam filters or through air scans without beam filters, at a plurality of kVp's," paragraph [0044]).
Yang et al. and Wu et al. are combined as per claim 2.
Claim 13
Regarding claim 13, Yang et al. teach the method of claim 12, wherein calculating the virtual filter for each X-ray detector comprises calculating the thickness of the virtual filter ("at energy E, attenuation by a single material with attenuation coefficient μ(E) and thickness t is modeled according to the Beer-Lambert law (equation (1) below)," paragraph [0023] where modeling is a virtual filter).
Claim 20
Regarding claim 20, Yang et al. teach the method of claim 1, as noted above.
Yang et al. is not relied upon to explicitly teach all of gantries.
However, Wu et al. teach wherein the CT imaging system comprises a rotatable gantry, an imaging X-ray source mounted to the gantry ("the x-ray source and the detector array are rotated with a gantry within the imaging plane and around the object to be imaged such that the angle at which the x-ray beam intersects the object constantly changes," paragraph [0016]), and the X-ray detectors are mounted to the gantry opposite the imaging X-ray source ("x-ray source projects a fan-shaped beam which is collimated to lie within an X-Y plane of a Cartesian coordinate system and generally referred to as an "imaging plane". The x-ray beam passes through an object being imaged, such as a patient," paragraph [0015]), and wherein the method further comprises acquiring the air scan X-ray intensity data at two different effective mean energies by rotating the gantry during a first air scan at a first mean energy and rotating the gantry during a second air scan at a second mean energy ("System detection coefficients Xn(i) are determined from measurements of air scans through known beam filters or through air scans without beam filters, at a plurality of kVp's," paragraph [0044]).
Yang et al. and Wu et al. are combined as per claim 2.
Claim 22
Regarding claim 22, Yang et al. teach the method of claim 20, as noted above.
Yang et al. is not relied upon to explicitly teach all of the first mean energy is 80 kVp.
However, Wu et al. teach wherein the first mean energy is 80 kVp and the second mean energy is 140 kVp ("With regards to X-ray attenuation, material attenuation of photons in the 5-120 keV energy region for X-rays are mainly due to the effects of Photoelectric effect and Compton scattering," paragraph [0031] where a range of values teaches 80 and 140 kVp).
Yang et al. and Wu et al. are combined as per claim 2.
Allowable Subject Matter
Claims 4 and 5 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.
Reference Cited
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Non Patent Publication “Robust Beam Hardening Artifacts Reduction for Computed Tomography Using Spectrum Modeling” to Zhao et al. discloses a fast and accurate beam hardening correction method by modeling physical interactions between X-ray photons and materials for computed tomography (CT) imaging.
Conclusion
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/Heath E. Wells/Examiner, Art Unit 2664
Date: 25 April 2026
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