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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 04/20/2026 has been entered.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-23, 27-28 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
Claim(s) 1-11, 13-23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wiemker et al. (US2023/0144823) in view of Yeh et al. (US2022/0096030).
To claim 1. Wiemker teach a system for transforming computed tomography data, the system comprising:
at least one hardware processor configured to:
receive input indicative of a particular X-ray energy level at which to generate a virtual monoenergetic image (VMI) of a subject that includes a plurality of target materials with improved contrast (paragraphs 0009-0010, 0022, user chooses a special image data to generate base image/virtual monoenergetic image at 200 keV; paragraphs 0005, 0016, 0020-0021, 0052-0053, contrast-boosted; Fig. 3, paragraphs 0044, 0051, image chosen with a particular energy level keV, which shows that the spectral image data user selected to input is with a particular X-ray energy level, which obviously render inputting with an indicative of a particular X-ray energy level) and;
receive computed tomography (CT) data of a subject; generate, from the received CT data (paragraph 0051), a VMI version of the CT data at the particular X-ray energy; the VMI being generated based on contributions to the CT data from the plurality of target materials at the particular X-ray energy by processing the CT data to produce image values corresponding to the particular X-ray energy (paragraphs 0011, 0020-0021); and cause the VMI version of the CT data to be presented (paragraph 0051, spectral CT imaging system generate a number of spectral channels/special image data that can be converted into various representations, such as virtual monoenergetic image).
In furthering said obviousness, Yeh teach generating VMI with a plurality of target materials with improved contrast at selected energy level (Figs. 4-6, paragraphs 0014, 0044-0046, 0091-0092, 0106).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate teaching of Yeh into the system of Wiemker, in order to further energy level selection on target materials for improved contrast.
To claim 2, Wiemker and Yeh teach claim 1.
Wiemker teach wherein the at least one hardware processor is further configured to: provide the CT data to a trained model; receive output from the trained model; and generate the VMI version of the CT data based on the output of the trained model (paragraphs 0023, 0050, 0056-0057).
To claim 3, Wiemker and Yeh teach claim 2.
Wiemker teach wherein the trained model is a trained convolutional neural network (CNN) that was trained using CT data of one or more subjects, each representing at least one material of a plurality of materials, and synthesized monoenergetic CT (MCT) images of at least one of the one or more subjects based on X-ray attenuation of the plurality of materials (paragraphs 0008, 0012, 0022, 0048).
To claim 4, Wiemker and Yeh teach claim 3.
Wiemker teach wherein the CT data comprises multi-energy computed tomography (MECT) image data of the one or more subjects (paragraph 0056, multispectral input images).
To claim 5, Wiemker and Yeh teach claim 3.
Wiemker teach wherein the CT data comprises MECT projection domain data of the one or more subjects (despite lack of disclosure, projection domain data is well-known in the art, which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate by design preference, hence Official Notice is taken).
To claim 6, Wiemker and Yeh teach claim 3.
Wiemker teach wherein the CT data comprises a VMI at an energy level of at least 40 kilo-electronvolts (keV) of the one or more subjects (paragraph 0011, 40keV), and the particular X-ray energy is below 40 keV (despite lack of disclosure, having a VMI at a particular is an obvious modification by design preference to one of ordinary skill in the art, hence Official Notice is taken).
To claim 7, Wiemker and Yeh teach claim 3.
Wiemker teach wherein the one or more subjects includes a phantom comprising a plurality of samples, each of the plurality of samples representing at least one material of a plurality of materials (despite lack of disclosure, imaging phantom is well-known in the art, hence Official Notice is taken).
To claim 8, Wiemker and Yeh teach claim 2.
Wiemker teach wherein the trained model is a least squares model (paragraphs 0054-0056, obvious in training linear model).
To claim 9, Wiemker and Yeh teach claim 8.
Wiemker teach wherein the particular X-ray energy is above 40 keV (paragraph 0009, 200keV).
To claim 10, Wiemker and Yeh teach claim 8.
Wiemker teach wherein the CT data is MECT image data (paragraph 0056, multispectral input images).
To claim 11, Wiemker and Yeh teach claim 1.
Wiemker teach wherein the input indicative of the particular X-ray energy level at which to generate the VMI of the subject comprises input explicitly indicating the plurality of target materials (obvious as explained in response to claim 1 above).
To claim 13, Wiemker and Yeh teach claim 1.
Wiemker teach wherein the input indicative of the particular X-ray energy level at which to generate the VMI of the subject comprises input explicitly indicating a task associated with the CT data (obvious as explained in response to claim 1 above).
To claim 14, Wiemker and Yeh teach claim 13.
Wiemker teach wherein the at least one hardware processor is further configured to: receive, via a user input device, the input explicitly indicating the task associated with the CT data (obvious as explained in response to claim 1 above).
To claim 15, Wiemker and Yeh teach claim 13.
Wiemker teach wherein the at least one hardware processor is further configured to: receive, from an electronic medical record system, the input explicitly indicating the task associated with the CT data (paragraphs 0006-0008, obviously imaging data is retrieved from electronic medical record system).
To claim 16, Wiemker and Yeh teach claim 1.
Wiemker teach wherein the plurality of target materials comprises at least two of: gray matter;
white matter; an iodine contrast-media; calcium; a mixture of blood and iodine; adipose tissue; hydroxyapatite; lung; liver; muscle; or blood (paragraphs 0008, 0011, 0035, 0045-0046, iodine-based contrast agent, soft tissue comprising adipose tissue is well-known in the art, hence Official Notice is taken)
To claim 17, Wiemker and Yeh teach claim 1.
Wiemker teach wherein the VMI version of the CT data is a 40 keV VMI (paragraph 0011).
To claim 18, Wiemker and Yeh teach claim 1.
Wiemker teach wherein the at least one hardware processor is further configured to: generate a second VMI version of the CT data at a second particular X-ray energy (paragraph 0022, the spectral image comprises a virtual monoenergetic image generated for an energy of 40 keV and a virtual monoenergetic image generated for an energy of 200 keV).
To claim 19, Wiemker and Yeh teach claim 18.
Wiemker teach wherein the second VMI version of the CT data is a 50 keV VMI (despite lack of disclosure, having a VMI at a particular is an obvious modification by design preference to one of ordinary skill in the art, hence Official Notice is taken).
To claim 20, Wiemker and Yeh teach claim 18.
Wiemker teach wherein the second VMI version of the CT data is a VMI at an energy below 40 keV (despite lack of disclosure, having a VMI at a particular is an obvious modification by design preference to one of ordinary skill in the art, hence Official Notice is taken).
To claim 21, Wiemker and Yeh teach claim 1.
Wiemker teach wherein the at least one hardware processor is further configured to:
receive the CT data from at least one of a CT scanner, a CT scanner over a wide area network, or memory (paragraph 0007).
To claim 22, Wiemker and Yeh teach claim 21.
Wiemker teach wherein the CT scanner is a dual-energy computed tomography scanner that is configured to generate the CT data (paragraph 0035).
To claim 23, Wiemker and Yeh teach claim 22.
Wiemker teach wherein the CT scanner is a photon counting detector computed tomography (PCD-CT) scanner that is configured to generate the CT data (paragraph 0008, photon counting detector technology).
Claim(s) 12, 27 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wiemker et al. (US2023/0144823) in view of Yeh et al. (US2022/0096030) and Lee et al. (US2021/0110583).
To claim 12, Wiemker and Yeh teach claim 11.
Wiemker teach wherein the at least one hardware processor is further configured to: identify the particular X-ray energy as an X-ray energy at which contrast between the plurality of target materials is substantially maximized (obvious in paragraph 0042).
Lee further teach wherein the at least one hardware processor is further configured to: identify the particular X-ray energy as an X-ray energy at which contrast between the plurality of target materials is substantially maximized (Fig. 6, 12, 15-16, paragraphs 0024-0029, 0034, 0037, 0043, 0144-0145, 0162-0168), which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate into the system of Wiemker and Yeh, in order to further optimize presentation.
To claim 27, Wiemker and Yeh teach claim 1.
Wiemker and Yeh teach wherein the particular X-ray energy level is identified from within a range of candidate X-ray energy levels as an energy level that provides the largest difference in attenuation coefficient between at least two of the plurality of materials (Yeh, Fig. 4, paragraphs 0107-0108, composite low and high X-ray attenuation material particles provide by far the largest difference in 80:140 kVp CT number ratios compared to soft tissue, water, and iodinated/barium contrast material of any compound, obviously either 80kVp or 140kVp provides the largest difference as shown in Fig. 4).
Lee further teach wherein the at least one hardware processor is further configured to: identify the particular X-ray energy as an X-ray energy at which contrast between the plurality of target materials is substantially maximized (Fig. 6, 12, 15-16, paragraphs 0024-0029, 0034, 0037, 0043, 0144-0145, 0162-0168), which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate into the system of Wiemker and Yeh, in order to further optimize presentation.
Claim(s) 28 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wiemker et al. (US2023/0144823) in view of Yeh et al. (US2022/0096030) and Persson et al. (US2024/0193827).
To claim 28, Wiemker and Yeh teach claim 1.
Wiemker and Yeh teach wherein the at least one hardware processor is further configured to automatically identify one or more VMIs to generate based on a prediction of target materials included in the CT data (Yeh, obvious in paragraphs 0041).
Persson teach using neural network to automatically identify one or more VMIs (paragraphs 0169, 0226) to generate based on a prediction of target materials included in the CT data (paragraphs 0030-0031, 0096, 0169, 0184, 0193), which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate into the system of Wiemker and Yeh, in order to further automated imagery analysis.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ZHIYU LU whose telephone number is (571)272-2837. The examiner can normally be reached Weekdays: 8:30AM - 5:00PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Stephen R Koziol can be reached at (408) 918-7630. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
ZHIYU . LU
Primary Examiner
Art Unit 2669
/ZHIYU LU/Primary Examiner, Art Unit 2665 June 10, 2026
Prosecution Insights