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 19 May 2026 has been entered. Applicant’s arguments with respect to claims 1, 6-16 and 18-20 have been considered but are moot in view of new ground(s) of rejection caused by the amendments.
Applicants amendments and arguments point out the differences between the previously applied references based on determining “reconstruction matrix parameters” and then using those parameters to determine new scanning parameters. However, a search based on “reconstruction matrix parameters” disclosed new reference US 2023 0063828 A1, which maps closely to the current claims.
Claims 1, 6-16 and 18-20 are pending in this application and have been considered below. Claims 2-5 and 17 are canceled by the applicant.
Information Disclosure Statement
The IDS dated 10 May 2024 that has been previously considered remains placed in the application file.
Claim Interpretation
Under MPEP 2143.03, "All words in a claim must be considered in judging the patentability of that claim against the prior art." In re Wilson, 424 F.2d 1382, 1385, 165 USPQ 494, 496 (CCPA 1970). As a general matter, the grammar and ordinary meaning of terms as understood by one having ordinary skill in the art used in a claim will dictate whether, and to what extent, the language limits the claim scope. Language that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives, the prior art teaches the element if one of the alternatives is taught by the prior art. See, e.g., Fresenius USA, Inc. v. Baxter Int’l, Inc., 582 F.3d 1288, 1298, 92 USPQ2d 1163, 1171 (Fed. Cir. 2009).
Claim 9 recites “one or more of.” Since “one or more of” is disjunctive, any one of the elements found in the prior art is sufficient to reject the claim. Claim 15 recites “or.” Since “or” is disjunctive, any one of the elements found in the prior art is sufficient to reject the claim. While citations have been provided for completeness and rapid prosecution, only one element is required. Because, on balance, it appears the disjunctive interpretation enjoys the most specification support and for that reason the disjunctive interpretation (one of A, B OR C) is being adopted for the purposes of this Office Action. Applicant’s comments and/or amendments relating to this issue are invited to clarify the claim language and the prosecution history.
Claim Rejections - 35 USC § 101
Claims 1, 16 and 19 have been amended. The rejection of Claims 1-2 and 6-20 under 35 U.S.C. 101 is withdrawn. The claims now all recite at least determining reconstruction matrix parameters, which is significantly more than an abstract idea and has concrete utility.
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, 6-8, 16 and 18-20 (all claims except claims 9-15) are rejected under 35 U.S.C. 103 as obvious over US Patent Publication 2023 0063828 A1, (Bao et al.) in view of International Patent Publication 2022 251701 A1, (Zhao et al.). The references are listed in a PTO-892 from the Office Action in which they are first used. If a reference is not identifiable (e.g., due to a typo), it can be identified by searching for the quoted text.
Claim 1
Regarding Claim 1, Bao et al. teach a computer-implemented method ("a method and system for image acquisition, image quality evaluation, and medical image acquisition to improve the efficiency and quality of image quality evaluation," paragraph [0004]), comprising:
obtaining, at a processor, a clinical task for a scan of a subject with a computed tomography imaging system ("The imaging device 110 may include digital radiography (DR), computed radiography (CR), digital fluorescence radiography (DF), magnetic resonance scanner, mammography, CT (computed tomography) imaging device PET (Positron Emission Computed Tomography) imaging device, MRI (Magnetic Resonance Imaging) imaging device, SPECT (Single Photon Emission Computed Tomography) imaging device, PET CT imaging device, PET MRI imaging device, etc.)," paragraph [0033]);
obtaining, at the processor, scanning parameters for the scan ("the processing device 140 retrieves the matching imaging protocol from the historical imaging protocol based on the posture information of the subject, and determines the current acquisition parameters based on this," paragraph [0037]);
obtaining, at the processor, initial tomographic data of the subject with the computed tomography imaging system ("In operation 202, an image of the target subject may be obtained. In some embodiments, operation 202 may be performed by the image obtaining module 310," paragraph [0041]); and
automatically determining, via the processor, reconstruction matrix parameters for generating a reconstructed image from tomographic data obtained of the subject with the scan based at least on the clinical task and the scanning parameters ("If it is determined that there is a matching imaging protocol in the historical imaging protocol, operation 7042 may be executed: designating at least a part of acquisition parameters in the matching imaging protocol as one or more current acquisition parameters," paragraph [0162]), wherein automatically determining the reconstruction matrix parameters comprises automatically determining a reconstruction field of view based on the initial reconstructed image ("At least one partial acquisition parameter in the historical imaging protocol may include one or more of the target subject's imaging position, image processing algorithm parameters, positioning parameters, ray source parameters, filter core parameters, image denoising parameters, reconstruction parameters, artifact suppression parameters, and injection parameters. In some embodiments, the processing device may take at least a part of the parameters in the historical imaging protocol that match the acquisition parameters of acquiring the current image as the current acquisition parameters. In some embodiments, the historical imaging protocol may be determined based on the posture information of the target subject (the subject to be imaged)," paragraph [0067]).
Bao et al. is not relied upon to explicitly teach all of full field of view.
However, Zhao et al. teach performing, via the processor, full field of view reconstruction on the initial tomographic data to generate an initial reconstructed image ("In one configuration, such an apparatus and method of measurements and tomographic imaging system may be combined with another imaging system configuration, for example, existing system configurations such as a ceiling mounted x ray system and or O-arm or 0 ring and or helical imaging geometry, to provide ease of access to a part or the entire VOI or field of view or a varied orientation of imaging source and detector pair, and better visibility and or flexibility of spatial configuration to provide better imaging angle. Measurements or datapoints from any x ray position may be used in tomographic reconstruction and or spectral imaging for improved material decomposition and or better density measurements," page 18, 2nd paragraph),
wherein the initial reconstructed image has a lower resolution than the reconstructed image of the tomographic data generated utilizing the reconstruction matrix parameters ("Reconstruction from distributed location of the detector or low resolution 3D image may be taken as the first 3D image. And at least one additional 3D image of the same or different resolution is reconstructed at a different time," page 28, paragraph 8).
Therefore, taking the teachings of Bao et al. and Zhao 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 “Image Quality Evaluation and Medical Image Acquisition” as taught by Bao et al. to use “X-Ray Imaging System” as taught by Zhao et al., showing that Bao et al. and Zhao et al. are analogous art because both are medical image acquisition references. The suggestion/motivation for combination is that, “In one configuration, such an apparatus and method of measurements and tomographic imaging system may be combined with another imaging system configuration, for example, existing system configurations such as a ceiling mounted x ray system and or O-arm or 0 ring and or helical imaging geometry, to provide ease of access to a part or the entire VOI or field of view or a varied orientation of imaging source and detector pair, and better visibility and or flexibility of spatial configuration to provide better imaging angle. Measurements or datapoints from any x ray position may be used in tomographic reconstruction and or spectral imaging for improved material decomposition and or better density measurements.” as noted by the Zhao et al. disclosure on page 18, 2nd paragraph, which also motivates combination because the combination would predictably have a higher flexibility as there is a reasonable expectation that x-ray machines have complex sets of scanning parameters and adjusting those parameters for best efficiency is useful; and/or because doing so merely combines prior art elements according to known methods to yield predictable results.
Claim 6
Regarding claim 6, Bao et al. teach the computer-implemented method of claim 2, wherein automatically determining the reconstruction matrix parameters comprises automatically determining, via the processor, a matrix size based at least on the clinical task, the scanning parameters, and the reconstruction field of view ("acquisition parameters may include the imaging position of the target subject (for example, head, chest, whether the imaging position is located in the scanning or imaging center, etc.), algorithm parameters of image processing (for example, the type of image reconstruction algorithm, for example, iterative reconstruction algorithm, depth learning method, multi-plane reconstruction, etc.), positioning parameters (for example, adjusting the body position of the target subject, etc.) One or more of the ray source parameters (e.g., scanning dose, scanning angle, etc.), filter kernel parameters ( e.g., convolution kernel parameters of the filter), image denoising parameters, reconstruction parameters (e.g., size of the reconstruction matrix), artifact suppression parameters ( e.g., artifact suppression method), injection parameters (e.g., whether to use contrast agent or tracer, a dose of injection, injection time, etc.)," paragraph [0058]).
Claim 7
Regarding claim 7, Bao et al. teach the computer-implemented method of claim 6, as noted above.
Bao et al. is not relied upon to explicitly teach all of determining the matrix size using a look up table.
However, Zhao et al. teach wherein automatically determining the matrix size comprises utilizing, via the processor, a lookup table to determine the matrix size ("In addition to on the fly calculations of intersection of voxels and x ray beams, a look up table may be established for varied dimensions of region of interest, varied dimensions of voxels and or varied location of x ray emitting positions, and or varied x ray emitting positions of first positions as well as second positions to speed up the reconstruction method," page 37, paragraph 6).
Bao et al. and Zhao et al. are combined as per claim 1.
Claim 8
Regarding claim 8, Bao et al. teach the computer-implemented method of claim 6, further comprising obtaining, at the processor, additional selected parameters that influence the matrix size, wherein the matrix size is automatically determined based on the clinical task, the scanning parameters, the reconstruction field of view, and the additional selected parameters ("acquisition parameters may include the imaging position of the target subject (for example, head, chest, whether the imaging position is located in the scanning or imaging center, etc.), algorithm parameters of image processing (for example, the type of image reconstruction algorithm, for example, iterative reconstruction algorithm, depth learning method, multi-plane reconstruction, etc.), positioning parameters (for example, adjusting the body position of the target subject, etc.) One or more of the ray source parameters (e.g., scanning dose, scanning angle, etc.), filter kernel parameters ( e.g., convolution kernel parameters of the filter), image denoising parameters, reconstruction parameters (e.g., size of the reconstruction matrix), artifact suppression parameters ( e.g., artifact suppression method), injection parameters (e.g., whether to use contrast agent or tracer, a dose of injection, injection time, etc.)," paragraph [0058]).
Claim 16
Regarding claim 16, Bao et al. teach a system ("the present disclosure describes a system and apparatus for developing patient- and task specific imaging protocols," paragraph [0004] and "a system, apparatus, method, and non-transitory computer-readable storage medium for patient-specific imaging protocol optimization." paragraph [0006]), comprising:
a memory encoding processor-executable routines ("The software part may be stored in the memory and executed by an appropriate instruction execution system, such as a microprocessor or specially designed hardware," paragraph [0189]); and
a processor configured to access the memory and to execute the processor-executable routines, wherein the processor-executable routines, when executed by the processor ("The software part may be stored in the memory and executed by an appropriate instruction execution system, such as a microprocessor or specially designed hardware," paragraph [0189]), cause the processor to:
obtain a clinical task for a scan of a subject with a computed tomography imaging system ("The imaging device 110 may include digital radiography (DR), computed radiography (CR), digital fluorescence radiography (DF), magnetic resonance scanner, mammography, CT (computed tomography) imaging device PET (Positron Emission Computed Tomography) imaging device, MRI (Magnetic Resonance Imaging) imaging device, SPECT (Single Photon Emission Computed Tomography) imaging device, PET CT imaging device, PET MRI imaging device, etc.)," paragraph [0033]);
obtain scanning parameters for the scan ("the processing device 140 retrieves the matching imaging protocol from the historical imaging protocol based on the posture information of the subject, and determines the current acquisition parameters based on this," paragraph [0037]); and
automatically determine reconstruction matrix parameters for generating a reconstructed image from tomographic data obtained of the subject with the scan based at least on the clinical task and the scanning parameters ("If it is determined that there is a matching imaging protocol in the historical imaging protocol, operation 7042 may be executed: designating at least a part of acquisition parameters in the matching imaging protocol as one or more current acquisition parameters," paragraph [0162]), wherein automatically determining the reconstruction matrix parameters comprises automatically determining a reconstruction field of view based on the surface map ("At least one partial acquisition parameter in the historical imaging protocol may include one or more of the target subject's imaging position, image processing algorithm parameters, positioning parameters, ray source parameters, filter core parameters, image denoising parameters, reconstruction parameters, artifact suppression parameters, and injection parameters. In some embodiments, the processing device may take at least a part of the parameters in the historical imaging protocol that match the acquisition parameters of acquiring the current image as the current acquisition parameters. In some embodiments, the historical imaging protocol may be determined based on the posture information of the target subject (the subject to be imaged)," paragraph [0067]).
Bao et al. is not relied upon to explicitly teach all of a LiDAR scanning system coupled to a gantry.
However, Zhao et al. teach obtain light detection and ranging (LiDAR) data of the subject acquired with a LiDAR scanning system coupled to a gantry of the computed tomography imaging system("When the dimension of the phantom is known, for example, height at each xy position, the thickness measurement or the height measurement by the lidar may be compared to known dimensions the phantom for accuracy checking," page 230, paragraph 5); and
generate a surface map of the subject based on the LiDAR data ("Time of flight sensor, or Lidar may be used to measure height map of ROI or thickness of the sample, for either exposure setting or for estimation of number of projections needed for 3D tomography," page 230, paragraph 1).
Bao et al. and Zhao et al. are combined as per claim 1.
Claim 18
Regarding claim 18, Bao et al. teach the system of claim 17, wherein automatically determining the reconstruction matrix parameters comprises automatically determining a matrix size based at least on the clinical task, the scanning parameters, and the reconstruction field of view ("acquisition parameters may include the imaging position of the target subject (for example, head, chest, whether the imaging position is located in the scanning or imaging center, etc.), algorithm parameters of image processing (for example, the type of image reconstruction algorithm, for example, iterative reconstruction algorithm, depth learning method, multi-plane reconstruction, etc.), positioning parameters (for example, adjusting the body position of the target subject, etc.) One or more of the ray source parameters (e.g., scanning dose, scanning angle, etc.), filter kernel parameters ( e.g., convolution kernel parameters of the filter), image denoising parameters, reconstruction parameters (e.g., size of the reconstruction matrix), artifact suppression parameters ( e.g., artifact suppression method), injection parameters (e.g., whether to use contrast agent or tracer, a dose of injection, injection time, etc.)," paragraph [0058]).
Claim 19
Regarding claim 19 Bao et al. teach a non-transitory computer-readable medium, the non-transitory computer-readable medium comprising processor-executable code that when executed by a processor ("a method and system for image acquisition, image quality evaluation, and medical image acquisition to improve the efficiency and quality of image quality evaluation," paragraph [0004]), causes the processor to:
obtain a clinical task for a scan of a subject with a computed tomography imaging system ("The imaging device 110 may include digital radiography (DR), computed radiography (CR), digital fluorescence radiography (DF), magnetic resonance scanner, mammography, CT (computed tomography) imaging device PET (Positron Emission Computed Tomography) imaging device, MRI (Magnetic Resonance Imaging) imaging device, SPECT (Single Photon Emission Computed Tomography) imaging device, PET CT imaging device, PET MRI imaging device, etc.)," paragraph [0033]);
obtain scanning parameters for the scan ("the processing device 140 retrieves the matching imaging protocol from the historical imaging protocol based on the posture information of the subject, and determines the current acquisition parameters based on this," paragraph [0037]); and
automatically determine reconstruction matrix parameters for generating a reconstructed image from tomographic data obtained of the subject with the scan based at least on the clinical task and the scanning parameters ("If it is determined that there is a matching imaging protocol in the historical imaging protocol, operation 7042 may be executed: designating at least a part of acquisition parameters in the matching imaging protocol as one or more current acquisition parameters," paragraph [0162]), wherein automatically determining the reconstruction matrix parameters comprises automatically determining a reconstruction field of view based on the body contour ("At least one partial acquisition parameter in the historical imaging protocol may include one or more of the target subject's imaging position, image processing algorithm parameters, positioning parameters, ray source parameters, filter core parameters, image denoising parameters, reconstruction parameters, artifact suppression parameters, and injection parameters. In some embodiments, the processing device may take at least a part of the parameters in the historical imaging protocol that match the acquisition parameters of acquiring the current image as the current acquisition parameters. In some embodiments, the historical imaging protocol may be determined based on the posture information of the target subject (the subject to be imaged)," paragraph [0067].
Bao et al. is not relied upon to explicitly teach all of a three dimensional camera.
However, Zhao et al. teach obtain imaging data of the subject acquired with a three-dimensional camera ("non radiating sensor such as optical sensor such as time of flight sensor or a camera can be used to assess surface position of ROI or the object and or thickness of VOI, or for example in a whole body imaging, to assess the starting point of 2D imaging. And distance from ROI, for example top layer of ROI, calculate thickness, and exposure needed and or where to move x ray source and detector to have the VOI in field of view," page 152, paragraph 3) coupled to a gantry of the computed tomography imaging system ("At least one camera may be mounted on gantry C or Gantry B for visualization of the patient," page 73, paragraph 4); and
generate a body contour of the subject based on the imaging data ("non radiating sensor such as optical sensor such as time of flight sensor or a camera can be used to assess surface position of ROI or the object and or thickness of VOI, or for example in a whole body imaging, to assess the starting point of 2D imaging," page 152, paragraph 3, where assess surface position teaches contours).
Bao et al. and Zhao et al. are combined as per claim 1.
Claim 20
Regarding claim 20, Bao et al. teach the non-transitory computer-readable medium of claim 19, wherein automatically determining the reconstruction matrix parameters comprises both automatically determining the reconstruction field of view and automatically determining a matrix size based at least on the clinical task, the scanning parameters, and the reconstruction field of view ("acquisition parameters may include the imaging position of the target subject (for example, head, chest, whether the imaging position is located in the scanning or imaging center, etc.), algorithm parameters of image processing (for example, the type of image reconstruction algorithm, for example, iterative reconstruction algorithm, depth learning method, multi-plane reconstruction, etc.), positioning parameters (for example, adjusting the body position of the target subject, etc.) One or more of the ray source parameters (e.g., scanning dose, scanning angle, etc.), filter kernel parameters ( e.g., convolution kernel parameters of the filter), image denoising parameters, reconstruction parameters (e.g., size of the reconstruction matrix), artifact suppression parameters ( e.g., artifact suppression method), injection parameters (e.g., whether to use contrast agent or tracer, a dose of injection, injection time, etc.)," paragraph [0058]).
1st Claim Rejections - 35 USC § 103
Claims 9-15 (all claims not rejected above) are rejected under 35 U.S.C. 103 as obvious over US Patent Publication 2023 0063828 A1, (Bao et al.) and International Patent Publication 2022 251701 A1, (Zhao et al.) in view of US Patent Publication 2022 0130520 A1, (Xia et al.). The references are listed in a PTO-892 from the Office Action in which they are first used. If a reference is not identifiable (e.g., due to a typo), it can be identified by searching for the quoted text.
Claim 9
Regarding Claim 1, Bao et al. and Zhao et al. teach the computer-implemented method of claim 8, as noted above.
Bao et al. and Zhao et al. are not relied upon to explicitly teach all of automatically determining the matrix size.
However, Xia et al. teach wherein automatically determining the matrix size comprises calculating, via the processor, the matrix size based on one or more of the scanning parameters and the additional selected parameters ("pitch and matrix size (i.e. an image reconstruction parameter) may be modified in accordance with a 2D pitch map, or spatial resolution map, generated from acquired scout scan data," paragraph [0064] where scout scan data is scanning parameters).
Therefore, taking the teachings of Bao et al., Zhao et al. and Xia 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 “Image Quality Evaluation and Medical Image Acquisition” as taught by Bao et al. and “X-Ray Imaging System” as taught by Zhao et al. to use “Radiographic Image Quality Assessment and protocol Optimization” as taught by Xia et al., showing that Bao et al., Zhao et al. and Xia et al. are analogous art because all are medical image acquisition references. The suggestion/motivation for combination is that, “Such considerations of the balance between radiation and image quality, however, are muddled when needs of specific patients are considered. This balance may be complicated by regional variations within different patients and by variations within each imaging volume which might otherwise be addressed by consideration of task-specific needs.” as noted by the Xia et al. disclosure in paragraph [0039], which also motivates combination because the combination would predictably have a higher flexibility as there is a reasonable expectation that x-ray machines have complex sets of scanning parameters and adjusting those parameters for best efficiency is useful; and/or because doing so merely combines prior art elements according to known methods to yield predictable results.
Claim 10
Regarding claim 10, Bao et al. and Zhao et al. teach the computer-implemented method of claim 8, as noted above.
Bao et al. and Zhao et al. are not relied upon to explicitly teach all of where the additional selected parameters are obtained via user input.
However, Xia et al. teach wherein the additional selected parameters are obtained, at the processor, via user input ("In an example, this allows a user to set a needed tube current, or mA, of the simulated scan to compensate for regions with high noise, such as the shoulders and the hips," paragraph [0061]).
Bao et al. and Zhao et al. and Xia et al. are combined as per claim 9.
Claim 11
Regarding claim 11, Bao et al. and Zhao et al. teach the computer-implemented method of claim 8, as noted above.
Bao et al. and Zhao et al. are not relied upon to explicitly teach all of where the additional selected parameters are automatically determined.
However, Xia et al. teach wherein the additional selected parameters are automatically determined, via the processor, based on the obtained clinical task ("In an embodiment, tube current and X-ray beam energy may be modified according to a noise map of the patient generated from the acquired scout scan data," paragraph [0061] where modified according to a noise map is automatically determined).
Bao et al. and Zhao et al. and Xia et al. are combined as per claim 9.
Claim 12
Regarding claim 12, Bao et al. and Zhao et al. teach the computer-implemented method of claim 8, as noted above.
Bao et al. and Zhao et al. are not relied upon to explicitly teach all of where the additional selected parameters include iterative reconstruction.
However, Xia et al. teach wherein the additional selected parameters comprise reconstruction kernel, iterative reconstruction, and post processing filters ("The image reconstruction parameters may include, among others, reconstruction method, reconstruction kernel, noise reduction filter, slice thickness, and a system matrix that simulates the scanning process," paragraph [0069]).
Bao et al. and Zhao et al. and Xia et al. are combined as per claim 9.
Claim 13
Regarding claim 13, Bao et al. and Zhao et al. teach the computer-implemented method of claim 6, as noted above.
Bao et al. and Zhao et al. are not relied upon to explicitly teach all of automatically updating the reconstruction prescription to include the reconstruction field of view.
However, Xia et al. teach further comprising: automatically updating, via the processor, a reconstruction prescription to include the reconstruction field of view and the matrix size ("the scan acquisition parameters include, but are not limited to, pitch, rotation speed. X-ray beam energy (i.e., tube voltage), tube current, collimation thickness, calibrated field of view, a bowtie filter, sampling frequency, and whether photon-counting is used. Each of the scan acquisition parameters may be adjusted to a static variable or may be adjusted to a dynamic variable that is adjustable across a volume of a patient according to needs of the patient," paragraph [0060]); and
generating, via the processor, a reconstructed image utilizing the updated reconstruction prescription ("the reconstruction device 1164 can include a CPU and a graphics processing unit (GPU) for processing and generating reconstructed images," paragraph [0135]).
Bao et al. and Zhao et al. and Xia et al. are combined as per claim 9.
Claim 14
Regarding claim 14, Bao et al. and Zhao et al. teach the computer-implemented method of claim 1, as noted above.
Bao et al. and Zhao et al. are not relied upon to explicitly teach all of where the clinical task is obtained via user input.
However, Xia et al. teach wherein the clinical task is obtained, at the processor, via user input ("In an example, this allows a user to set a needed tube current, or mA, of the simulated scan to compensate for regions with high noise, such as the shoulders and the hips," paragraph [0061]).
Bao et al. and Zhao et al. and Xia et al. are combined as per claim 9.
Claim 15
Regarding claim 15, Bao et al. and Zhao et al. teach the computer-implemented method of claim 1, as noted above.
Bao et al. and Zhao et al. are not relied upon to explicitly teach all of where the clinical task is obtained from a hospital information system.
However, Xia et al. teach wherein the clinical task is obtained, at the processor, from a hospital information system or radiology information system ("An apparatus for generating a patient-specific imaging protocol, comprising processing circuitry configured to receive scout scan data that includes scout scan information and scout scan parameters, generate a simulated image based on the received scout scan data, scan acquisition parameters, and image reconstruction parameters, apply a neural network to the generated simulated image to generate at least one probabilistic quality representation, transform the generated at least one probabilistic quality representation to, as a determined image quality, a scalar image quality value, derive a simulated dose map from the received scout scan data and the scan acquisition parameters, evaluate the determined image quality of the generated simulated image relative to a predetermined image quality threshold and the derived simulated dose map relative to a predetermined dosage threshold, and generate, when the determined image quality of the generated simulated image satisfies the predetermined image quality threshold and the derived simulated dose map satisfies the predetermined dosage threshold, imaging protocol parameters based on the scan acquisition parameters and the image reconstruction parameters," paragraph [0188]).
Bao et al. and Zhao et al. and Xia et al. are combined as per claim 9.
Reference Cited
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Non Patent Publication “Effect of Matrix Size Reduction on Textural Information in Clinical Magnetic Resonance Imaging” to Strzelecki et al. discloses selection of the matrix size is an important element of the magnetic resonance imaging (MRI) process, and has a significant impact on the acquired image quality. Signal to noise ratio, often used to assess MR image quality, has its limitations. Thus, for this purpose we propose a novel approach: the use of texture analysis as an index of the image quality that is sensitive for the change of matrix size.
US Patent Publication 2014 0197834 A1 to Porter et al. discloses magnetic resonance (MR) imaging sequence of phase encoding gradient fields and a sequence of readout gradient fields are applied in order to produce a well-defined zigzag-type trajectory for entering raw data into k-space. Zigzag-type trajectories can be achieved that have flanks without curvature, or without significant curvature. Cartesian methods for image reconstruction of parallel MR imaging are applied to echo planar MR imaging with such zigzag-type trajectories.
Conclusion
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 HEATH E WELLS whose telephone number is (703)756-4696. The examiner can normally be reached Monday-Friday 8:00-4:00.
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, Ms. Jennifer Mehmood can be reached on 571-272-2976. 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.
/H.E.W/Examiner, Art Unit 2664
Date: 18 August 2026
/JENNIFER MEHMOOD/Supervisory Patent Examiner, Art Unit 2664
Prosecution Insights