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 .
Drawings
The drawings were received on 12/2/2024. These drawings are accepted.
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.
Claims 1, 3-4, 7, 16-18 and 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Beckers et al. (US20180256042, hereinafter “Beckers”)
(Claims 1, 3-4 and 7 are listed after 16-18 and 20)
Claim 16. Beckers teaches A post-processing system configured for use with a magnetic resonance imaging (MRI) based medical imaging system, ([0006] “magnetic resonance imaging (MRI) based medical imaging system”) wherein the MRI based medical imaging system is operable to generate a velocity data set ([0042] “The captured information includes … phase information which is indicative of velocity.”) and a magnitude data set ([0042] “The captured information includes … magnitude information, which is indicative of anatomical structure,” is understood to be the same as the claimed magnitude data set in light of instant specifications [0007]) representative of a fluid flow, ([0042] “atrial blood flow from venous blood flow. This may advantageously allow automated or even autonomous generation of flow visualization information,”) the system comprising:
(a) at least one non-transitory processor-readable storage medium ([0049] “non-transitory computer- or processor-readable memory,”) that stores at least one of processor-executable instructions or data; ([0072] “Program modules can be stored in the system memory 214, such as an operating system 236, one or more application programs 238, other programs or modules 240 and program data 242. Application programs 238 may include instructions that cause the processor(s) 212 to perform image processing and analysis on MRI image data sets.”) and
(b) at least one processor communicably coupled to the at least one non- transitory processor-readable storage medium, ([0049] “non-transitory computer- or processor-readable memory, drive circuitry and/or interface components to interface with the MRI machine 108.”) the at least one processor configured to:
(i) receive the velocity data set from the imaging system; ([0044] “Image acquisition may include determining, defining, generating or otherwise setting one or more pulse sequences, which are used to run the MRI machine (e.g., control magnets) and acquire raw MRI. Use of a 4D flow pulse sequence allows capture of not only anatomical structure, which is represented by magnitude, but of velocity”)
(ii) calculate a phase variation data set ([0103] “Automatic Phase Aliasing Correction Using Time Domain” The claimed phase variation dataset is understood to be the same as Beckers et al Phase aliasing correction using Time domain in light of instant specifications [0046] which states that phase variation is estimated by using temporal variation to correct for phase aliasing ) from a wrapped phase field data set associated with the velocity data set; ([0104] “Phase aliasing occurs when the VENC that was set for the 4D-Flow scan was too low causing the velocity values to “wrap”; ” phase aliasing is a synonym for phase wrapping or a wrapped phase https://onelook.com/thesaurus/?s=phase%20aliasing)
(iii) calculate a phase difference uncertainty data set ([0141] “Automatic Background Phase Error Correction” and [0142] “Determining eddy current correction (ECC) is done by examining the velocity signal in static (non-moving) tissue.” Error correction specifically eddy current correction is understood to be the same as the claimed calculate a phase difference uncertainty dataset in light of [0055] which details that the uncertainty is an error/noise calculation) from the magnitude data set; ([0142] “Determining eddy current correction (ECC) is done by examining the velocity signal in static (non-moving) tissue. This requires the masking of all moving tissue, blood and air.” And [0143] “Air is masked by masking out regions with anatomy image values below a set threshold.” The anatomy images are being used to calculate the error correction which is understood to be the same as the claimed calculate a phase difference uncertainty data set from the magnitude data set)
(iv) use the phase variation data set and the phase difference uncertainty data set, performing a computational reconstruction of the phase field data set to generate an unwrapped phase data set; ([0103] “Automatic Phase Aliasing Correction Using Time Domain” is previously stated to be the same as the claimed phase variation dataset. Aliasing correction is understood to be the same as the claimed generate unwrapped phase dataset. In regards to the claimed phase difference uncertainty dataset: [0141] “phase error correction” and [0142] “Accurate measurement of velocity in flow-4D MRI scans requires the application of corrections for the false signal introduced by eddy currents. Determining eddy current correction (ECC) is done by examining the velocity signal in static (non-moving) tissue.” Having an accurate velocity measurement after error correction is understood to be the same as the claimed use the phase difference uncertainty data to generate an unwrapped phase dataset. )
(v) convert the unwrapped phase ([0072] “correct for phase aliasing.” Correcting for phase aliasing is understood to be the same as the claimed convert the unwrapped phase as stated above ) to a velocity field data set; ([0109] “iv) When aliasing is detected the wrap count for that point is either incremented if observed velocity reduced by more than VENC or decremented if the observed velocity increased by more than VENC. And [0110] “v) At each point in time the velocity is altered according to the current accumulated wrap count for that point” Altering the velocity according to the wrap count is understood by the examiner to be the same as the claimed converting the unwrapped phase to a velocity field dataset ) and
(vi) output a resultant velocity field set based upon the velocity field data set; ([0237] “display 3 orthogonal views to the user …In addition to showing the anatomic images, the blood velocity images (with or without vectors)” Displaying is a type of output) and
(c) a display device ([0050] “An MRI operator's system 128 may include a …monitor or display 132,”) configured to receive and display the resultant velocity field set. ([0237] “display 3 orthogonal views to the user …In addition to showing the anatomic images, the blood velocity images (with or without vectors) can be overlaid onto the anatomic images to further clarify where the blood pool boundary is during the interactive 3D volume segmentation process.”)
Claim 17. Beckers teaches The system of claim 16, wherein performing the computational reconstruction of the phase field data set to generate the unwrapped phase data set includes performing a weighted least squares operation ([0099] “algorithm that will generate a least squares divergence free approximation of the flow field.”)to generate the unwrapped phase data set. ([0099]“The goal of this pre-processing algorithm is to correct the flow data (segmentation, flow quantification, and background phase error correction). There are 3 flow datasets that need to be corrected: i) x velocity, ii) y velocity, and iii) z velocity.”)
Claim 18. Beckers teaches The system of claim 16, wherein the phase variation data set includes a spatial phase variation component and a temporal phase variation component, wherein the spatial phase variation component is representative of the difference between two or more neighboring voxels ([0097] “a filter or mask may be defined that shows only voxels having vectors in a same direction as the vectors of neighboring voxels, to for instance identify or view high velocity jets. Notably, velocity vectors of neighboring voxels are in different directions may be an indication of noise.” ) and the temporal phase variation component is representative of the difference between two or more consecutive cardiac frames. ([0042] “processing the captured movie to account for relative movement introduced by the pulmonary and cardiac cycles.” And [0189] “first identify the time points corresponding to the main temporal landmarks in the cardiac cycle ” is understood to be the same as the claimed temporal phase variation representative of the difference between cardiac frames)
Claim 20. Beckers teaches The system of claim 16, wherein calculating the phase difference uncertainty data set from the magnitude data set ([0099] “goal of this pre-processing algorithm is to correct the flow data (segmentation, flow quantification, and background phase error correction). There are 3 flow datasets that need to be corrected: i) x velocity, ii) y velocity, and iii) z velocity.”) includes incorporating with the magnitude data set a divergence- free constraint ([0099] “algorithm that will generate a least squares divergence free approximation of the flow field.”) of incompressible flow. ([0099] “the flow entering a stationary volume must match the flow exiting the volume if the fluid is incompressible.”)
Claim 1. The method herein has been executed and performed by the system of claim 16 and is likewise rejected
Claim 3. The method herein has been executed and performed by the system of claim 17 and is likewise rejected
Claim 4. The method herein has been executed and performed by the system of claim 18 and is likewise rejected
Claim 7. The method herein has been executed and performed by the system of claim 20 and is likewise rejected
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 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 2, 5, 8-13 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Beckers et al. (US20180256042, hereinafter “Beckers”) and in view of Mistretta et al (US20060066306, hereinafter “Mistretta”)
Claims 2, 5 and 8 are listed after Claims 9-13 and 15
Claim 9. Beckers teaches A method of processing data generated by an imaging system, ([0006] “magnetic resonance imaging (MRI) based medical imaging system”) wherein the imaging system is operable to generate a velocity data set ([0042] “The captured information includes … phase information which is indicative of velocity.”) and a magnitude data set ([0042] “The captured information includes … magnitude information, which is indicative of anatomical structure,” is understood to be the same as the claimed magnitude data set in light of instant specifications [0007]) representative of a fluid flow, ([0042] “atrial blood flow from venous blood flow. This may advantageously allow automated or even autonomous generation of flow visualization information,”) the method comprising:
(a) receiving the velocity data set from the imaging system; ([0044] “Image acquisition may include determining, defining, generating or otherwise setting one or more pulse sequences, which are used to run the MRI machine (e.g., control magnets) and acquire raw MRI. Use of a 4D flow pulse sequence allows capture of not only anatomical structure, which is represented by magnitude, but of velocity”)
(b) performing an unwrapping routine, including:
(i) calculating a phase variation data set ([0103] “Automatic Phase Aliasing Correction Using Time Domain” The claimed phase variation dataset is understood to be the same as Beckers et al Phase aliasing correction using Time domain in light of instant specifications [0046] which states that phase variation is estimated by using temporal variation to correct for phase aliasing ) from a wrapped phase field data set associated with the velocity data set; ([0104] “Phase aliasing occurs when the VENC that was set for the 4D-Flow scan was too low causing the velocity values to “wrap”; ” phase aliasing is a synonym for phase wrapping or a wrapped phase https://onelook.com/thesaurus/?s=phase%20aliasing)
(ii) calculating a phase difference uncertainty data set ([0141] “Automatic Background Phase Error Correction” and [0142] “Determining eddy current correction (ECC) is done by examining the velocity signal in static (non-moving) tissue.” Error correction specifically eddy current correction is understood to be the same as the claimed calculate a phase difference uncertainty dataset in light of [0055] which details that the uncertainty is an error/noise calculation) from the magnitude data set; ([0142] “Determining eddy current correction (ECC) is done by examining the velocity signal in static (non-moving) tissue. This requires the masking of all moving tissue, blood and air.” And [0143] “Air is masked by masking out regions with anatomy image values below a set threshold.” The anatomy images are being used to calculate the error correction which is understood to be the same as the claimed calculate a phase difference uncertainty data set from the magnitude data set)
(ii) using the phase variation data set and the phase difference uncertainty data set, performing a computational reconstruction of the phase field data set to generate an unwrapped phase data set; ([0103] “Automatic Phase Aliasing Correction Using Time Domain” is previously stated to be the same as the claimed phase variation dataset. Aliasing correction is understood to be the same as the claimed generate unwrapped phase dataset. In regards to the claimed phase difference uncertainty dataset: [0141] “phase error correction” and [0142] “Accurate measurement of velocity in flow-4D MRI scans requires the application of corrections for the false signal introduced by eddy currents. Determining eddy current correction (ECC) is done by examining the velocity signal in static (non-moving) tissue.” Having an accurate velocity measurement after error correction is understood to be the same as the claimed use the phase difference uncertainty data to generate an unwrapped phase dataset. )
(ii) converting the unwrapped phase ([0072] “correct for phase aliasing.” Correcting for phase aliasing is understood to be the same as the claimed convert the unwrapped phase as stated above ) to a velocity field data set; ([0109] “iv) When aliasing is detected the wrap count for that point is either incremented if observed velocity reduced by more than VENC or decremented if the observed velocity increased by more than VENC. And [0110] “v) At each point in time the velocity is altered according to the current accumulated wrap count for that point” Altering the velocity according to the wrap count is understood by the examiner to be the same as the claimed converting the unwrapped phase to a velocity field dataset )
and
(e) outputting a resultant velocity field set based upon the velocity field data set. ([0237] “display 3 orthogonal views to the user …In addition to showing the anatomic images, the blood velocity images (with or without vectors)” Displaying is a type of output)
Beckers does not explicitly teach and (c) replacing the velocity data set with the velocity field data set;
(d) repeating steps (b) - (c) between five to 10 times;
Mistretta teaches and (c) replacing the velocity data set with the velocity field data set; (d) repeating steps (b) - (c) ; (replacing the velocity data set with the velocity field data set and repeating the same steps is taught by Mistretta et al [0061] “the pixel phase is corrected to have this consistent number of phase wraps. This process is performed on each pixel in the phase image and then the process is repeated two or three times.” )
It would have been obvious to persons of ordinary skill in the art before the effective filing date of the claimed invention to modify Beckers to have replacing and repeating the steps of claim 9 as taught by Mistretta to arrive at the claimed invention discussed above. The motivation for the proposed modification would have been so that (Mistretta et al [0014]“ The present invention enables a lower VENC (i.e., higher velocity sensitivity) to be used without artifacts due to phase aliasing.”)
Mistretta discloses the claimed invention except for (d) repeating steps (b) - (c) between five to 10 times;. It would have been obvious for one of ordinary skill in the art to repeat steps between five to ten times since it has been held that where the general conditions of a claim are disclosed in the prior art, discovering the optimum range involves only routine skill in the art. In re Aller, 105 USPQ 233 (MPEP 2144.05 (II-A)).
Claim 10. Beckers and Mistretta teach The method of claim 9,
Beckers teaches wherein outputting the resultant velocity field set includes transmitting the resultant velocity field set to a graphical display. ([0237] “The 3D surface can be shown in short axis to the user … In addition to showing the anatomic images, the blood velocity images (with or without vectors) can be overlaid onto the anatomic images to further clarify where the blood pool boundary is during the interactive 3D volume segmentation process.” And [0019] )
Claim 11. Beckers and Mistretta teach The method of claim 9,
Beckers teaches wherein performing the computational reconstruction of the phase field data set to generate the unwrapped phase data set includes performing a weighted least squares operation ([0099] “algorithm that will generate a least squares divergence free approximation of the flow field.”) to generate the unwrapped phase data set. ([0099]“The goal of this pre-processing algorithm is to correct the flow data (segmentation, flow quantification, and background phase error correction). There are 3 flow datasets that need to be corrected: i) x velocity, ii) y velocity, and iii) z velocity.”)
Claim 12. Beckers and Mistretta teach The method of claim 9,
Beckers teaches wherein the phase variation data set includes a spatial phase variation component and a temporal phase variation component, wherein the spatial phase variation component is representative of the difference between two or more neighboring voxels ([0097] “a filter or mask may be defined that shows only voxels having vectors in a same direction as the vectors of neighboring voxels, to for instance identify or view high velocity jets. Notably, velocity vectors of neighboring voxels are in different directions may be an indication of noise.” ) and the temporal phase variation component is representative of the difference between two or more consecutive cardiac frames. ([0042] “processing the captured movie to account for relative movement introduced by the pulmonary and cardiac cycles.” And [0189] “first identify the time points corresponding to the main temporal landmarks in the cardiac cycle ” is understood to be the same as the claimed temporal phase variation representative of the difference between cardiac frames)
Claim 13. Beckers and Mistretta teach The method of claim 9,
Beckers does not explicitly teach wherein converting the unwrapped phase to the velocity field data set includes multiplying the unwrapped phase by (venc/π).
Mistretta teaches wherein converting the unwrapped phase to the velocity field data set includes multiplying the unwrapped phase by (venc/π). ([0033] “Using this information and the LOW VENC phase information, the spin velocity may then be calculated as follows:
PNG
media_image1.png
77
267
media_image1.png
Greyscale
PNG
media_image2.png
96
538
media_image2.png
Greyscale
”)
It would have been obvious to persons of ordinary skill in the art before the effective filing date of the claimed invention to modify Beckers to have converting the unwrapped phase to the velocity field data set includes multiplying the unwrapped phase by venc/π as taught by Mistretta to arrive at the claimed invention discussed above. The motivation for the proposed modification would have been so that (Mistretta et al [0014]“ The present invention enables a lower VENC (i.e., higher velocity sensitivity) to be used without artifacts due to phase aliasing.”)
Claim 15. Beckers and Mistretta teach The method of claim 9,
Beckers teaches wherein calculating the phase difference uncertainty data set from the magnitude data set ([0099] “goal of this pre-processing algorithm is to correct the flow data (segmentation, flow quantification, and background phase error correction). There are 3 flow datasets that need to be corrected: i) x velocity, ii) y velocity, and iii) z velocity.”) includes incorporating with the magnitude data set a divergence- free constraint ([0099] “algorithm that will generate a least squares divergence free approximation of the flow field.”) of incompressible flow. ([0099] “the flow entering a stationary volume must match the flow exiting the volume if the fluid is incompressible.”)
Claim 2. The method herein has been executed and performed by the method of claim 10 and is likewise rejected
Claim 5. The method herein has been executed and performed by the method of claim 13 and is likewise rejected
Claim 8. Beckers teaches The method of claim 1, wherein outputting the resultant velocity field set based upon the first velocity field data set includes:
Beckers does not explicitly teach (a) calculating a second phase variation data set from a second wrapped phase field data set associated with the first velocity field data set;
(b) calculating a second phase difference uncertainty data set from a second magnitude data set associated with the first velocity field data set;
(c) using the second phase variation data set and the second phase difference uncertainty data set, performing a second computational reconstruction of the second phase field data set to generate a second unwrapped phase data set;
(d) converting the second unwrapped phase to a second velocity field data set;
and (e) outputting the resultant velocity field set based upon the second velocity field data set.
Mistretta teaches (a) calculating a second phase variation data set from a second wrapped phase field data set associated with the first velocity field data set;
(b) calculating a second phase difference uncertainty data set from a second magnitude data set associated with the first velocity field data set;
(c) using the second phase variation data set and the second phase difference uncertainty data set, performing a second computational reconstruction of the second phase field data set to generate a second unwrapped phase data set;
(d) converting the second unwrapped phase to a second velocity field data set; (The second phase variation, second wrapped phase field data, second phase difference uncertainty, second magnitude data, second computational reconstruction, second phase field data, second unwrapped phase data and second velocity field data is understood by the examiner to be the same as the “replacing the velocity data set with the velocity field data set; (d) repeating steps b-c” in claim 9 because repeating the same steps will include a second of each of the steps which was done in claims 1 and 16. This is taught by Mistretta et al [0061] “the pixel phase is corrected to have this consistent number of phase wraps. This process is performed on each pixel in the phase image and then the process is repeated two or three times.”)
and (e) outputting the resultant velocity field set ([0040] “operates to reconstruct one or more images as will be described below… conveyed to the operator console 100 and presented on the display 104.”) based upon the second velocity field data set. ([0060] “unwrapped velocity images” The unwrapped velocity is based upon repeated steps which include a second velocity field data set as stated above Mistretta [0061])
It would have been obvious to persons of ordinary skill in the art before the effective filing date of the claimed invention to modify Beckers to have a second phase variation, second wrapped phase field data, second phase difference uncertainty, second magnitude data, second computational reconstruction, second phase field data, second unwrapped phase data and second velocity field data and repeating the steps of claim 1 as taught by Mistretta to arrive at the claimed invention discussed above. The motivation for the proposed modification would have been so that (Mistretta et al [0014]“ The present invention enables a lower VENC (i.e., higher velocity sensitivity) to be used without artifacts due to phase aliasing.”)
Allowable Subject Matter
Claims 6, 14 and 19 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.
Wang US20110044524 teaches utilizing weighted least squares after the phase data is unwrapped but does not render obvious the claimed combination as a whole
Zhang et al NPL “4D Flow MRI Pressure Estimation Using Velocity Measurement-Error-Based Weighted Least-Squares” teaches using weighted least squares for calculating pressure gradients from velocity fields but does not render obvious the claimed combination as a whole
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure:
Wang US20110044524 teaches utilizing weighted least squares after the phase data is unwrapped.
Zhang et al NPL “4D Flow MRI Pressure Estimation Using Velocity Measurement-Error-Based Weighted Least-Squares” teaches using weighted least squares for calculating pressure gradients from velocity fields.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to OWAIS MEMON whose telephone number is (571)272-2168. The examiner can normally be reached M-F (7:00am - 4:00pm) CST.
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, Gregory Morse can be reached at (571) 272-3838. 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.
/OWAIS I MEMON/Examiner, Art Unit 2663
Prosecution Insights