DETAILED ACTION
In view of the appeal brief filed on 05/21/2026, PROSECUTION IS HEREBY REOPENED. New grounds of rejection are set forth below.
To avoid abandonment of the application, appellant must exercise one of the following two options:
(1) file a reply under 37 CFR 1.111 (if this Office action is non-final) or a reply under 37 CFR 1.113 (if this Office action is final); or,
(2) initiate a new appeal by filing a notice of appeal under 37 CFR 41.31 followed by an appeal brief under 37 CFR 41.37. The previously paid notice of appeal fee and appeal brief fee can be applied to the new appeal. If, however, the appeal fees set forth in 37 CFR 41.20 have been increased since they were previously paid, then appellant must pay the difference between the increased fees and the amount previously paid.
A Supervisory Patent Examiner (SPE) has approved of reopening prosecution by signing below:
/ANDREW W BEE/ Supervisory Patent Examiner, Art Unit 2677
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 .
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-4, and 10-19 are rejected under 35 U.S.C. 102(a)(1) and (a)(2) as being anticipated by Brinks (US 20110081068 A1).
With respect to claim 1, Brinks teaches a computer-implemented method (see figure 1), comprising: obtaining positron emission tomography (PET) data (“The following relates to the imaging arts, medical arts, and related arts. It is described herein with illustrative reference to positron emission tomography (PET) imaging, but will find more general application in radiological imaging generally, for example PET…” paragraph 0001) that includes moving tissue of interest (see figure 1 element 26);
generating a set of short PET frames from the PET data, wherein each short PET frame of the set of short PET frames is based on a time duration (“A LOR grouping module 18 groups the acquired LOR's into time intervals such that each group of LOR's was acquired during a selected time interval. Each time interval is either: (i) a contiguous time interval of sufficiently short duration such that any motion occurring in the time interval should be small…” paragraph 0030);
identifying a first tissue of interest in the set of short PET frames (“A region-of-interest (ROI) identification module 22 determines a sub-set of the LORs of each time interval that intersect with or, more generally, contribute to image content within, a spatial (two- or three-dimensional) region-of-interest (ROI).” Paragraph 0031 and “Moreover, it is to be appreciated that one, two, or more ROI may be determined for each time interval. For example, in some embodiments disclosed herein multiple ROI are determined using an anatomical model, with the different ROI of a given time interval corresponding to different anatomical regions or features represented by the anatomical model.” Paragraph 0033);
identifying at least a second tissue of interest in the set of short PET frames (“A region-of-interest (ROI) identification module 22 determines a sub-set of the LORs of each time interval that intersect with or, more generally, contribute to image content within, a spatial (two- or three-dimensional) region-of-interest (ROI).” Paragraph 0031 and “Moreover, it is to be appreciated that one, two, or more ROI may be determined for each time interval. For example, in some embodiments disclosed herein multiple ROI are determined using an anatomical model, with the different ROI of a given time interval corresponding to different anatomical regions or features represented by the anatomical model.” Paragraph 0033);
estimating, separately and independently, a first motion of the first tissue of interest and a second motion of second tissue of interest based on the short PET frames (“The positional characteristic determined for the ROI of each time interval is a measure of local motion in the ROI. In some embodiments, the local motion is considered for computational simplicity to be a rigid translation within the ROI, although more complex non-rigid, or rotational, or other motions are also contemplated. If multiple ROI are determined for each time interval, then each ROI may in general have a different local motion.” Paragraph 0034 and “Moreover, it is to be appreciated that one, two, or more ROI may be determined for each time interval. For example, in some embodiments disclosed herein multiple ROI are determined using an anatomical model, with the different ROI of a given time interval corresponding to different anatomical regions or features represented by the anatomical model.” Paragraph 0033);
and motion correcting, separately and independently, the first tissue of interest for the first motion and the second tissue of interest for the second motion (“A local motion correction or compensation module 26 spatially adjusts the LOR's identified as contributing to image content within the ROI for each time interval so as to compensate for the local motion indicated by the determined positional characteristic.” Paragraph 0035 and “Moreover, it is to be appreciated that one, two, or more ROI may be determined for each time interval. For example, in some embodiments disclosed herein multiple ROI are determined using an anatomical model, with the different ROI of a given time interval corresponding to different anatomical regions or features represented by the anatomical model.” Paragraph 0033 and “In yet another approach, the LOR's contributing to image content in each ROI are treated independently, and the LOR's contributing to image content in each ROI are reconstructed after adjustment based on the positional characteristic of that ROI so as to produce one or more images corresponding to the one or more ROI for each time interval. In this approach, a LOR that contributes to image content in two or more ROI is duplicated and included in the set of LOR's for each ROI, and each instance of the LOR is adjusted in accordance with the positional characteristics of the ROI to which it is assigned.” Paragraph 0037).
With respect to claim 2, Brinks teaches the computer-implemented method of claim 1, further comprising: displaying the motion corrected first tissue of interest and the second motion corrected second tissue of interest (“At least the spatially adjusted LOR's are processed by a high resolution image reconstruction module 32 to generate a motion-compensated reconstructed image.” Paragraph 0039 and “A user interface, such as an illustrated computer 40, includes a display 42 for displaying the high resolution reconstructed image output by the high resolution reconstruction module 32” paragraph 0042).
With respect to claim 3, The computer-implemented method of claim 1, further comprising: inserting the motion corrected first tissue of interest at a corresponding first location in a rendering of the PET data (“If a given time interval includes two or more ROI,…Alternatively, as mentioned earlier the LOR adjustments can be feathered or otherwise smoothed for LOR's contributing to regions adjacent the ROI to provide smoothly adjusted LOR data that are suitably reconstructed as a single data set by the high resolution image reconstruction module 32 to generate a single motion-compensated reconstructed image.” Paragraph 0039);
inserting the motion corrected second tissue of interest at a corresponding second location in the rendering of the PET data (“If a given time interval includes two or more ROI,…Alternatively, as mentioned earlier the LOR adjustments can be feathered or otherwise smoothed for LOR's contributing to regions adjacent the ROI to provide smoothly adjusted LOR data that are suitably reconstructed as a single data set by the high resolution image reconstruction module 32 to generate a single motion-compensated reconstructed image.” Paragraph 0039); and
displaying the rendering of the PET data (“A user interface, such as an illustrated computer 40, includes a display 42 for displaying the high resolution reconstructed image output by the high resolution reconstruction module 32” paragraph 0042).
With respect to claim 4, Brinks teaches the computer-implemented method of claim 1, wherein at least one of the first motion and the second motion includes at least one of a translation in an x direction (“A local motion correction or compensation module 26 spatially adjusts the LOR's identified as contributing to image content within the ROI for each time interval so as to compensate for the local motion indicated by the determined positional characteristic. In an illustrative embodiment in which the local motion is considered as a rigid translation, the local motion correction module 26 adjusts the LOR's for the local motion by shifting each LOR by an amount corresponding to the positional characteristic determined for the ROI.” Paragraph 0035), a rotation about the x direction (“If the positional characteristic includes a rotation, then the correction can entail rotating each LOR by the rotation indicated by the positional characteristic.” Paragraph 0035), a translation in a y direction (“A local motion correction or compensation module 26 spatially adjusts the LOR's identified as contributing to image content within the ROI for each time interval so as to compensate for the local motion indicated by the determined positional characteristic. In an illustrative embodiment in which the local motion is considered as a rigid translation, the local motion correction module 26 adjusts the LOR's for the local motion by shifting each LOR by an amount corresponding to the positional characteristic determined for the ROI.” Paragraph 0035), a rotation about the y direction (“If the positional characteristic includes a rotation, then the correction can entail rotating each LOR by the rotation indicated by the positional characteristic.” Paragraph 0035), a translation in a z direction (“A local motion correction or compensation module 26 spatially adjusts the LOR's identified as contributing to image content within the ROI for each time interval so as to compensate for the local motion indicated by the determined positional characteristic. In an illustrative embodiment in which the local motion is considered as a rigid translation, the local motion correction module 26 adjusts the LOR's for the local motion by shifting each LOR by an amount corresponding to the positional characteristic determined for the ROI.” Paragraph 0035), and a rotation about the z direction (“If the positional characteristic includes a rotation, then the correction can entail rotating each LOR by the rotation indicated by the positional characteristic.” Paragraph 0035).
With respect to claim 10, Brinks teaches the computer-implemented method of claim 1, wherein at least one of the first motion and the second motion is rigid motion (“The positional characteristic determined for the ROI of each time interval is a measure of local motion in the ROI. In some embodiments, the local motion is considered for computational simplicity to be a rigid translation within the ROI, although more complex non-rigid, or rotational, or other motions are also contemplated. If multiple ROI are determined for each time interval, then each ROI may in general have a different local motion.” Paragraph 0034).
With respect to claim 11, Brinks teaches a computing system (see figure 1), comprising:
a computer readable storage medium memory that includes instructions for correcting motion in data (“For example, the microprocessor and associated software or firmware of the computer 40 can embody one, two, some, or all of the various computational components 12, 18, 22, 24, 26, 30, 32, 34, 36, and these computational components can also be thought of as being embodied by the storage medium that stores the instructions defining the software or firmware, such storage medium being suitably embodied, for example, as one or more of a magnetic disk, an optical disk, an electrostatic memory or storage such as a FLASH memory, a read-only-memory (ROM), random access memory (RAM), an off-site Internet storage unit, or so forth.” Paragraph 0042); and
a processor configured to execute the instructions (“For example, the microprocessor and associated software or firmware of the computer 40 can embody one, two, some, or all of the various computational components 12, 18, 22, 24, 26, 30, 32, 34, 36,…” paragraph 0042), wherein the instructions cause the processor to:
obtain PET data (“The following relates to the imaging arts, medical arts, and related arts. It is described herein with illustrative reference to positron emission tomography (PET) imaging, but will find more general application in radiological imaging generally, for example PET…” paragraph 0001) that includes moving tissue of interest (see figure 1 element 26);
generate a set of short PET frames from the PET data, wherein each short PET frame of the set of short PET frames is based on a time duration (“A LOR grouping module 18 groups the acquired LOR's into time intervals such that each group of LOR's was acquired during a selected time interval. Each time interval is either: (i) a contiguous time interval of sufficiently short duration such that any motion occurring in the time interval should be small; or (ii) an aggregation of a plurality of non-contiguous time sub-intervals each of sufficiently short duration such that any motion occurring in the time sub-interval should be small and with the aggregated time sub-intervals having a common cardiac or respiratory phase as indicated by cardiac or respiratory monitoring. The output of the LOR grouping module 18 are LORs grouped into time intervals 20, with the LORs of each time interval suitably treated as having a substantially quiescent motion state. ” paragraph 0030);
identify a first tissue of interest in the set of short PET frames (“A region-of-interest (ROI) identification module 22 determines a sub-set of the LORs of each time interval that intersect with or, more generally, contribute to image content within, a spatial (two- or three-dimensional) region-of-interest (ROI).” Paragraph 0031 and “Moreover, it is to be appreciated that one, two, or more ROI may be determined for each time interval. For example, in some embodiments disclosed herein multiple ROI are determined using an anatomical model, with the different ROI of a given time interval corresponding to different anatomical regions or features represented by the anatomical model.” Paragraph 0033);
identify at least a second tissue of interest in set of short PET frames (“A region-of-interest (ROI) identification module 22 determines a sub-set of the LORs of each time interval that intersect with or, more generally, contribute to image content within, a spatial (two- or three-dimensional) region-of-interest (ROI).” Paragraph 0031 and “Moreover, it is to be appreciated that one, two, or more ROI may be determined for each time interval. For example, in some embodiments disclosed herein multiple ROI are determined using an anatomical model, with the different ROI of a given time interval corresponding to different anatomical regions or features represented by the anatomical model.” Paragraph 0033);
estimate, separately and independently, a first motion of the first tissue of interest and a second motion of second tissue of interest based on the short PET frames (“The positional characteristic determined for the ROI of each time interval is a measure of local motion in the ROI. In some embodiments, the local motion is considered for computational simplicity to be a rigid translation within the ROI, although more complex non-rigid, or rotational, or other motions are also contemplated. If multiple ROI are determined for each time interval, then each ROI may in general have a different local motion.” Paragraph 0034 and “Moreover, it is to be appreciated that one, two, or more ROI may be determined for each time interval. For example, in some embodiments disclosed herein multiple ROI are determined using an anatomical model, with the different ROI of a given time interval corresponding to different anatomical regions or features represented by the anatomical model.” Paragraph 0033); and
motion correct, separately and independently, the first tissue of interest for the first motion and the second tissue of interest for the second motion (“A local motion correction or compensation module 26 spatially adjusts the LOR's identified as contributing to image content within the ROI for each time interval so as to compensate for the local motion indicated by the determined positional characteristic.” Paragraph 0035 and “Moreover, it is to be appreciated that one, two, or more ROI may be determined for each time interval. For example, in some embodiments disclosed herein multiple ROI are determined using an anatomical model, with the different ROI of a given time interval corresponding to different anatomical regions or features represented by the anatomical model.” Paragraph 0033 and “In yet another approach, the LOR's contributing to image content in each ROI are treated independently, and the LOR's contributing to image content in each ROI are reconstructed after adjustment based on the positional characteristic of that ROI so as to produce one or more images corresponding to the one or more ROI for each time interval. In this approach, a LOR that contributes to image content in two or more ROI is duplicated and included in the set of LOR's for each ROI, and each instance of the LOR is adjusted in accordance with the positional characteristics of the ROI to which it is assigned.” Paragraph 0037).
With respect to claim 12, Brinks teaches the computing system of claim 11, wherein the instructions cause the processor to: display the motion corrected first tissue of interest and the second motion corrected second tissue of interest (“At least the spatially adjusted LOR's are processed by a high resolution image reconstruction module 32 to generate a motion-compensated reconstructed image.” Paragraph 0039 and “A user interface, such as an illustrated computer 40, includes a display 42 for displaying the high resolution reconstructed image output by the high resolution reconstruction module 32” paragraph 0042).
With respect to claim 13, Brinks teaches the computing system of claim 11, where the instructions further cause the processor to:
insert the motion corrected first tissue of interest at a corresponding first location in a rendering of the PET data (“If a given time interval includes two or more ROI,…Alternatively, as mentioned earlier the LOR adjustments can be feathered or otherwise smoothed for LOR's contributing to regions adjacent the ROI to provide smoothly adjusted LOR data that are suitably reconstructed as a single data set by the high resolution image reconstruction module 32 to generate a single motion-compensated reconstructed image.” Paragraph 0039);
insert the motion corrected second tissue of interest at a corresponding second location in the rendering of the PET data (“If a given time interval includes two or more ROI,…Alternatively, as mentioned earlier the LOR adjustments can be feathered or otherwise smoothed for LOR's contributing to regions adjacent the ROI to provide smoothly adjusted LOR data that are suitably reconstructed as a single data set by the high resolution image reconstruction module 32 to generate a single motion-compensated reconstructed image.” Paragraph 0039); and
display the rendering of the PET data (“A user interface, such as an illustrated computer 40, includes a display 42 for displaying the high resolution reconstructed image output by the high resolution reconstruction module 32” paragraph 0042).
With respect to claim 14, Brinks teaches the computing system of claim 11, wherein at least one of the first motion and the second motion includes at least one of a translation in an x direction (“A local motion correction or compensation module 26 spatially adjusts the LOR's identified as contributing to image content within the ROI for each time interval so as to compensate for the local motion indicated by the determined positional characteristic. In an illustrative embodiment in which the local motion is considered as a rigid translation, the local motion correction module 26 adjusts the LOR's for the local motion by shifting each LOR by an amount corresponding to the positional characteristic determined for the ROI.” Paragraph 0035), a rotation about the x direction (“If the positional characteristic includes a rotation, then the correction can entail rotating each LOR by the rotation indicated by the positional characteristic.” Paragraph 0035), a translation in a y direction (“A local motion correction or compensation module 26 spatially adjusts the LOR's identified as contributing to image content within the ROI for each time interval so as to compensate for the local motion indicated by the determined positional characteristic. In an illustrative embodiment in which the local motion is considered as a rigid translation, the local motion correction module 26 adjusts the LOR's for the local motion by shifting each LOR by an amount corresponding to the positional characteristic determined for the ROI.” Paragraph 0035), a rotation about the y direction (“If the positional characteristic includes a rotation, then the correction can entail rotating each LOR by the rotation indicated by the positional characteristic.” Paragraph 0035), a translation in a z direction (“A local motion correction or compensation module 26 spatially adjusts the LOR's identified as contributing to image content within the ROI for each time interval so as to compensate for the local motion indicated by the determined positional characteristic. In an illustrative embodiment in which the local motion is considered as a rigid translation, the local motion correction module 26 adjusts the LOR's for the local motion by shifting each LOR by an amount corresponding to the positional characteristic determined for the ROI.” Paragraph 0035), and a rotation about the z direction (“If the positional characteristic includes a rotation, then the correction can entail rotating each LOR by the rotation indicated by the positional characteristic.” Paragraph 0035).
With respect to claim 15, Brinks teaches the computing system of claim 11, wherein at least one of the first motion and the second motion includes periodic motion (“For embodiments in which the local motion is expected to be principally due to cardiac or respiratory cycling or another periodic, quasi-periodic, or repetitive motion, it may be advantageous to define a time interval as an aggregation of two or more temporally non-contiguous time sub-intervals having a common phase of the cardiac, respiratory, or other repetitive cycling.” Paragraph 0054), non-periodic motion (“The positional characteristic determined for the ROI of each time interval is a measure of local motion in the ROI. In some embodiments, the local motion is considered for computational simplicity to be a rigid translation within the ROI, although more complex non-rigid, or rotational, or other motions are also contemplated. Paragraph 0034), or periodic (“For embodiments in which the local motion is expected to be principally due to cardiac or respiratory cycling or another periodic, quasi-periodic, or repetitive motion, it may be advantageous to define a time interval as an aggregation of two or more temporally non-contiguous time sub-intervals having a common phase of the cardiac, respiratory, or other repetitive cycling.” Paragraph 0054) and non-periodic motion (“The positional characteristic determined for the ROI of each time interval is a measure of local motion in the ROI. In some embodiments, the local motion is considered for computational simplicity to be a rigid translation within the ROI, although more complex non-rigid, or rotational, or other motions are also contemplated. Paragraph 0034).
With respect to claim 16, Brinks teaches a computer readable storage medium encoded with computer executable instructions (“For example, the microprocessor and associated software or firmware of the computer 40 can embody one, two, some, or all of the various computational components 12, 18, 22, 24, 26, 30, 32, 34, 36, and these computational components can also be thought of as being embodied by the storage medium that stores the instructions defining the software or firmware, such storage medium being suitably embodied, for example, as one or more of a magnetic disk, an optical disk, an electrostatic memory or storage such as a FLASH memory, a read-only-memory (ROM), random access memory (RAM), an off-site Internet storage unit, or so forth.” Paragraph 0042), which when executed by a processor (“For example, the microprocessor and associated software or firmware of the computer 40 can embody one, two, some, or all of the various computational components 12, 18, 22, 24, 26, 30, 32, 34, 36,…” paragraph 0042), causes the processor to:
obtain PET data (“The following relates to the imaging arts, medical arts, and related arts. It is described herein with illustrative reference to positron emission tomography (PET) imaging, but will find more general application in radiological imaging generally, for example PET…” paragraph 0001) that includes moving tissue of interest (see figure 1 element 26);
generate a set of short PET frames from the PET data, wherein each short PET frame of the set of short PET frames is based on a time duration (“A LOR grouping module 18 groups the acquired LOR's into time intervals such that each group of LOR's was acquired during a selected time interval. Each time interval is either: (i) a contiguous time interval of sufficiently short duration such that any motion occurring in the time interval should be small; or (ii) an aggregation of a plurality of non-contiguous time sub-intervals each of sufficiently short duration such that any motion occurring in the time sub-interval should be small and with the aggregated time sub-intervals having a common cardiac or respiratory phase as indicated by cardiac or respiratory monitoring. The output of the LOR grouping module 18 are LORs grouped into time intervals 20, with the LORs of each time interval suitably treated as having a substantially quiescent motion state. ” paragraph 0030);
identify a first tissue of interest in the set of short PET frames (“A region-of-interest (ROI) identification module 22 determines a sub-set of the LORs of each time interval that intersect with or, more generally, contribute to image content within, a spatial (two- or three-dimensional) region-of-interest (ROI).” Paragraph 0031 and “Moreover, it is to be appreciated that one, two, or more ROI may be determined for each time interval. For example, in some embodiments disclosed herein multiple ROI are determined using an anatomical model, with the different ROI of a given time interval corresponding to different anatomical regions or features represented by the anatomical model.” Paragraph 0033);
identify at least a second tissue of interest in the set of short PET frames (“A region-of-interest (ROI) identification module 22 determines a sub-set of the LORs of each time interval that intersect with or, more generally, contribute to image content within, a spatial (two- or three-dimensional) region-of-interest (ROI).” Paragraph 0031 and “Moreover, it is to be appreciated that one, two, or more ROI may be determined for each time interval. For example, in some embodiments disclosed herein multiple ROI are determined using an anatomical model, with the different ROI of a given time interval corresponding to different anatomical regions or features represented by the anatomical model.” Paragraph 0033);
estimate, separately and independently, a first motion of the first tissue of interest and a second motion of second tissue of interest based on the short PET frames (“The positional characteristic determined for the ROI of each time interval is a measure of local motion in the ROI. In some embodiments, the local motion is considered for computational simplicity to be a rigid translation within the ROI, although more complex non-rigid, or rotational, or other motions are also contemplated. If multiple ROI are determined for each time interval, then each ROI may in general have a different local motion.” Paragraph 0034 and “Moreover, it is to be appreciated that one, two, or more ROI may be determined for each time interval. For example, in some embodiments disclosed herein multiple ROI are determined using an anatomical model, with the different ROI of a given time interval corresponding to different anatomical regions or features represented by the anatomical model.” Paragraph 0033); and
motion correct, separately and independently, the first tissue of interest for the first motion and the second tissue of interest for the second motion (“A local motion correction or compensation module 26 spatially adjusts the LOR's identified as contributing to image content within the ROI for each time interval so as to compensate for the local motion indicated by the determined positional characteristic.” Paragraph 0035 and “Moreover, it is to be appreciated that one, two, or more ROI may be determined for each time interval. For example, in some embodiments disclosed herein multiple ROI are determined using an anatomical model, with the different ROI of a given time interval corresponding to different anatomical regions or features represented by the anatomical model.” Paragraph 0033 and “In yet another approach, the LOR's contributing to image content in each ROI are treated independently, and the LOR's contributing to image content in each ROI are reconstructed after adjustment based on the positional characteristic of that ROI so as to produce one or more images corresponding to the one or more ROI for each time interval. In this approach, a LOR that contributes to image content in two or more ROI is duplicated and included in the set of LOR's for each ROI, and each instance of the LOR is adjusted in accordance with the positional characteristics of the ROI to which it is assigned.” Paragraph 0037).
With respect to claim 17, Brinks teaches the computer readable storage medium of claim 16, wherein the instructions further cause the processor to: display the motion corrected first tissue of interest and the second motion corrected second tissue of interest (“At least the spatially adjusted LOR's are processed by a high resolution image reconstruction module 32 to generate a motion-compensated reconstructed image.” Paragraph 0039 and “A user interface, such as an illustrated computer 40, includes a display 42 for displaying the high resolution reconstructed image output by the high resolution reconstruction module 32” paragraph 0042).
With respect to claim 18, Brinks teaches the computer readable storage medium of claim 16, where the instructions further cause the processor to:
insert the motion corrected first tissue of interest at a corresponding first location in a rendering of the PET data (“If a given time interval includes two or more ROI,…Alternatively, as mentioned earlier the LOR adjustments can be feathered or otherwise smoothed for LOR's contributing to regions adjacent the ROI to provide smoothly adjusted LOR data that are suitably reconstructed as a single data set by the high resolution image reconstruction module 32 to generate a single motion-compensated reconstructed image.” Paragraph 0039);
insert the motion corrected second tissue of interest at a corresponding second location in the rendering of the PET data (“If a given time interval includes two or more ROI,…Alternatively, as mentioned earlier the LOR adjustments can be feathered or otherwise smoothed for LOR's contributing to regions adjacent the ROI to provide smoothly adjusted LOR data that are suitably reconstructed as a single data set by the high resolution image reconstruction module 32 to generate a single motion-compensated reconstructed image.” Paragraph 0039); and
display the rendering of the PET data (“A user interface, such as an illustrated computer 40, includes a display 42 for displaying the high resolution reconstructed image output by the high resolution reconstruction module 32” paragraph 0042).
With respect to claim 19, Brinks teaches the computer readable storage medium of claim 16, wherein at least one of the first motion and the second motion includes at least one of a translation in an x direction (“A local motion correction or compensation module 26 spatially adjusts the LOR's identified as contributing to image content within the ROI for each time interval so as to compensate for the local motion indicated by the determined positional characteristic. In an illustrative embodiment in which the local motion is considered as a rigid translation, the local motion correction module 26 adjusts the LOR's for the local motion by shifting each LOR by an amount corresponding to the positional characteristic determined for the ROI.” Paragraph 0035), a rotation about the x direction (“If the positional characteristic includes a rotation, then the correction can entail rotating each LOR by the rotation indicated by the positional characteristic.” Paragraph 0035), a translation in a y direction (“A local motion correction or compensation module 26 spatially adjusts the LOR's identified as contributing to image content within the ROI for each time interval so as to compensate for the local motion indicated by the determined positional characteristic. In an illustrative embodiment in which the local motion is considered as a rigid translation, the local motion correction module 26 adjusts the LOR's for the local motion by shifting each LOR by an amount corresponding to the positional characteristic determined for the ROI.” Paragraph 0035), a rotation about the y direction (“If the positional characteristic includes a rotation, then the correction can entail rotating each LOR by the rotation indicated by the positional characteristic.” Paragraph 0035), a translation in a z direction (“A local motion correction or compensation module 26 spatially adjusts the LOR's identified as contributing to image content within the ROI for each time interval so as to compensate for the local motion indicated by the determined positional characteristic. In an illustrative embodiment in which the local motion is considered as a rigid translation, the local motion correction module 26 adjusts the LOR's for the local motion by shifting each LOR by an amount corresponding to the positional characteristic determined for the ROI.” Paragraph 0035), and a rotation about the z direction (“If the positional characteristic includes a rotation, then the correction can entail rotating each LOR by the rotation indicated by the positional characteristic.” Paragraph 0035).
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.
Claims 5 is rejected under 35 U.S.C. 103 as being unpatentable over Brinks (US 20110081068 A1), as applied to claim 1 above, and further in view of Narayanan (US 8787643 B2).
With respect to claim 5, Brinks teaches the computer-implemented method of claim 1, and first tissue of interest (“A region-of-interest (ROI) identification module 22 determines a sub-set of the LORs of each time interval that intersect with or, more generally, contribute to image content within, a spatial (two- or three-dimensional) region-of-interest (ROI).” Paragraph 0031 and “Moreover, it is to be appreciated that one, two, or more ROI may be determined for each time interval. For example, in some embodiments disclosed herein multiple ROI are determined using an anatomical model, with the different ROI of a given time interval corresponding to different anatomical regions or features represented by the anatomical model.” Paragraph 0033), and a second tissue of interest (“A region-of-interest (ROI) identification module 22 determines a sub-set of the LORs of each time interval that intersect with or, more generally, contribute to image content within, a spatial (two- or three-dimensional) region-of-interest (ROI).” Paragraph 0031 and “Moreover, it is to be appreciated that one, two, or more ROI may be determined for each time interval. For example, in some embodiments disclosed herein multiple ROI are determined using an anatomical model, with the different ROI of a given time interval corresponding to different anatomical regions or features represented by the anatomical model.” Paragraph 0033). Brinks does not teach generating a first volume of interest for the first tissue of interest, wherein the first volume of interest is less than an entire field of view of the PET data and only PET data within the first volume of interest is utilized to estimate the first motion; and generating a second volume of interest for the second tissue of interest, wherein the second volume of interest is less than the entire field of view of the PET data and only PET data within the second volume of interest is utilized to estimate the second motion, wherein the first volume of interest and the second volume of interest are different volumes of interest.
Narayanan further teaches generating a first volume of interest for the first tissue of interest (“A region of interest (ROI) identifier 202 identifies a volume of interest (VOI) in the PET image data for kinetic analysis. The VOI may include an organ, a lesion, or other feature of interest of the object or subject.” Col 4 lines 15-18), wherein the first volume of interest is less than an entire field of view of the PET data (“A region of interest (ROI) identifier 202 identifies a volume of interest (VOI) in the PET image data for kinetic analysis. The VOI may include an organ, a lesion, or other feature of interest of the object or subject.” Col 4 lines 15-18, the VOI is within the PET data) and only PET data within the first volume of interest is utilized to estimate the first motion (“A motion corrector 206 corrects the PET data for motion artifact based on the VOI. The corrected PET data can be reconstructed to generate motion corrected images.” Col 4 lines 39-41); and
generating a second volume of interest for the second tissue of interest (“A region of interest (ROI) identifier 202 identifies a volume of interest (VOI) in the PET image data for kinetic analysis. The VOI may include an organ, a lesion, or other feature of interest of the object or subject.” Col 4 lines 15-18), wherein the second volume of interest is less than the entire field of view of the PET data (“A region of interest (ROI) identifier 202 identifies a volume of interest (VOI) in the PET image data for kinetic analysis. The VOI may include an organ, a lesion, or other feature of interest of the object or subject.” Col 4 lines 15-18, the VOI is within the PET data) and only PET data within the second volume of interest is utilized to estimate the second motion (“A motion corrector 206 corrects the PET data for motion artifact based on the VOI. The corrected PET data can be reconstructed to generate motion corrected images.” Col 4 lines 39-41),
wherein the first volume of interest and the second volume of interest are different volumes of interest (“At 706, one or more VOIs are identified and/or segmented using the registered images.” Col 7 lines 60-61).
Narayanan is analogous art in the same field of endeavor as the claimed invention. Narayanan is directed towards PET image data motion correction (“A motion corrector 206 corrects the PET data for motion artifact based on the VOI. The corrected PET data can be reconstructed to generate motion corrected images.” Col 4 lines 39-41). A person of ordinary skill in the art before the effective filing date of the claimed invention, would have found it obvious to combine the similar teachings of Brinks and Narayana by using Narayanan to generate volume of its (Brinks’) tissue ROIs, with the expectation that doing so would lead to decreased blur due to motion (“In addition, accurate estimation of kinetic parameters, which is used in characterizing the underlying tracer distribution, is confounded by a number of factors including that of physiologic motion such as cardiac and respiratory motion. Methods to minimize blur due to motion include gating (cardiac, respiratory or both). However, the loss of counts with gating add to the challenge of fitting noisy time-activity curves in conventional PET or SPECT dynamic images.” Col 1 lines 36-43)
Claims 6-8 are rejected under 35 U.S.C. 103 as being unpatentable over Brinks and Narayanan as applied to claim 5 above, and further in view of Tang (US 20220323035 A1).
With respect to claim 6, Brinks and Narayanan teach the computer-implemented method of claim 5. Narayanan teaches the first and second volumes of interest to motion correct (“A region of interest (ROI) identifier 202 identifies a volume of interest (VOI) in the PET image data for kinetic analysis. The VOI may include an organ, a lesion, or other feature of interest of the object or subject.” Col 4 lines 15-18 and “At 706, one or more VOIs are identified and/or segmented using the registered images.” Col 7 lines 60-61), but does not teach the further limitations.
Tang teaches determining a patch within a volume of interest to correct (“Next, in block B820, the image-generation device generates PARs of a patch that includes the contour. For example, FIG. 9A illustrates a patch 1027 that includes the contour 1026” paragraph 0074, see also figure 8 B835).
Tang is analogous art in the same field of endeavor as the claimed invention. Tang is directed towards motion correction of images taken by various forms of anatomical scanners including PET (“The one or more image-generation devices 110 are configured to perform motion-correction operations while generating reconstructed images.” Page 26 paragraph 0043 lines 17-19). A person of ordinary skill in the art before the effective filing date of the claimed invention would have found it obvious to combine Brinks, Narayanan and Tang by utilizing the teachings of tang to incorporate the partitioning by patching method within the combined system’s multi-volume motion correction process, with the expectation that doing so would lead to the combined system being able to isolate specific areas moving during image capturing further allowing it to motion correct and reconstruct these areas (“For example, FIG. 9A illustrates an example embodiment of a contour 1026 of a track caused by a moving object. In this example, the object is a vessel, and the contour 1026 delineates the area in the half reconstruction 1025 in which the vessel moved during the capture of the scan data.” Page 29 paragraph 0073 lines 6-16 And “Next, in block B820, the image-generation device generates PARs of a patch that includes the contour. For example, FIG. 9A illustrates a patch 1027 that includes the contour 1026.” Paragraph 0074 And “The one or more image-generation devices 110 are configured to perform motion-correction operations” page 26 paragraph 0043 lines 17-19).
With respect to claim 7, Brinks, Narayanan and Tang teach the computer-implemented method of claim 6. Narayanan teaches the first and second volumes of interest (“A region of interest (ROI) identifier 202 identifies a volume of interest (VOI) in the PET image data for kinetic analysis. The VOI may include an organ, a lesion, or other feature of interest of the object or subject.” Col 4 lines 15-18 and “At 706, one or more VOIs are identified and/or segmented using the registered images.” Col 7 lines 60-61), but does not teach the further limitations.
Tang further teaches where a volume of interest has a first size a patch has a second size, and the second size is equal to the first size (“Also, FIG. 7A illustrates a patch 1027 that includes an object or a part of an object.” Volume as object page 28 paragraph 0064 lines 5-6).
With respect to claim 8, Brinks, Narayanan, and Tang teach the computer-implemented method of claim 6. Narayanan teaches the first and second volumes of interest (“A region of interest (ROI) identifier 202 identifies a volume of interest (VOI) in the PET image data for kinetic analysis. The VOI may include an organ, a lesion, or other feature of interest of the object or subject.” Col 4 lines 15-18 and “At 706, one or more VOIs are identified and/or segmented using the registered images.” Col 7 lines 60-61), but does not teach the further limitations.
Tang further teaches where a volume has a first size, a patch has a second size and the second size is smaller than the first size (“The flow then moves to block B615, where the image-generation device identifies one or more patches, in the half reconstruction” paragraph 0064 lines 1-3).
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Brinks and Narayanan as applied to claim 5 above, and further in view of Kabus (WO 2012004742 A1).
With respect to claim 9, Brinks and Narayanan teach the computer-implemented method of claim 5. Brinks teaches identifying ROIs in short PET frames (“A region-of-interest (ROI) identification module 22 determines a sub-set of the LORs of each time interval that intersect with or, more generally, contribute to image content within, a spatial (two- or three-dimensional) region-of-interest (ROI).” Paragraph 0031 and “Moreover, it is to be appreciated that one, two, or more ROI may be determined for each time interval. For example, in some embodiments disclosed herein multiple ROI are determined using an anatomical model, with the different ROI of a given time interval corresponding to different anatomical regions or features represented by the anatomical model.” Paragraph 0033). Narayanan teaches the first and second volumes of interest (“A region of interest (ROI) identifier 202 identifies a volume of interest (VOI) in the PET image data for kinetic analysis. The VOI may include an organ, a lesion, or other feature of interest of the object or subject.” Col 4 lines 15-18 and “At 706, one or more VOIs are identified and/or segmented using the registered images.” Col 7 lines 60-61), but does not teach the further limitations. Kabus further teaches modifying the size of a volume of interest (“One reason for this observation may be that large deformations providing more accurate alignment often lead to deformations resulting in unreasonably large volume changes. “ page 4 lines 19-21 and “In an embodiment of the system, the metric of the local volume change is based on the Jacobian metric. In an embodiment of the system, the metric unit is further arranged for computing an image-intensity-based metric of the local volume change at the plurality of locations, based on the first and second image, and the local property of the first or second image defined at the plurality of locations is the computed image-intensity-based metric.” Page 4 lines 23-28 , deformation as volume change )
Kabus is analogous art in the same field of endeavor as the claimed invention. Kabus is directed towards medical imaging motion correction and estimation (“In general, this invention relates to automatic point-wise validation of motion estimation, wherein the motion is estimated by a deformation vector field for transforming a first image at a first phase of the motion into a second image at a second phase of the motion. In particular, this invention relates to automatic point-wise validation of respiratory motion estimation on the basis of CT images.” Field of invention). A person of ordinary skill in the art before the effective filing date of the claimed invention would have found it obvious to combine Brinks, Narayanan and Kabus by utilizing Kabus’ teachings of the impact of volumetric changes on motion estimation processes would lead to improvements in motion compensation and image registration by eliminating erroneous measurements caused by volumetric changes (“Typically, an image registration scheme aims at balancing two types of forces: an outer force driven by the difference of the two images and an inner force driven by a physical model. Consequently, a weighting factor is introduced to balance these two forces. Generally, the application of a large weight on the outer force is likely to yield a small residuum image. Unfortunately, it often introduces incorrect deformations, even folding, into the DVF. Therefore, using a residuum image for validating a DVF may often lead to an erroneous determination of the DVF. It would be useful to provide a validation scheme for reducing the likelihood of positive validation of an erroneously estimated DVF.” Page 3 lines 27-33 and page 4 lines 1-2).
Claim 20 is rejected under 35 U.S.C. 103 as being unpatentable over Brinks as applied to claim 16 above, and further in view of Thielemans (US 20090154641 A1).
With respect to claim 20, Brinks teaches the computer readable storage medium of claim 16. Brinks teaches the first and second motion (“The positional characteristic determined for the ROI of each time interval is a measure of local motion in the ROI. In some embodiments, the local motion is considered for computational simplicity to be a rigid translation within the ROI, although more complex non-rigid, or rotational, or other motions are also contemplated. If multiple ROI are determined for each time interval, then each ROI may in general have a different local motion.” Paragraph 0034 and “Moreover, it is to be appreciated that one, two, or more ROI may be determined for each time interval. For example, in some embodiments disclosed herein multiple ROI are determined using an anatomical model, with the different ROI of a given time interval corresponding to different anatomical regions or features represented by the anatomical model.” Paragraph 0033), but does not explicitly teach affine motion. Thielemans teaches where observed motion in pet images includes affine motion (“The above methods for motion correction are applicable to arbitrary motions, including non-rigid motion. The third embodiment is preferably applied to motions where the positions of the body at different instants of time are connected by an affine transformation, including rigid motion of the body.” Paragraph 0023)
Thielemans is analogous art in the same field of endeavor as the claimed invention. Thielemans is directed towards motion correction in medical imaging (“The invention relates to a method of and software for conducting motion correction in tomographic scanning and a system for tomographic scanning using this method, in particular but not exclusively a positron emission tomography (PET) scanning system.” Field of invention). A person of ordinary skill in the art before the effective filing date of the claimed invention would have found it obvious to combine Brinks and Thielemans by incorporating its teachings of affine motion in PET images, with the expectation that doing so would lead to an improved motion correction strategy that takes into account affine motion which can lead to blur and/or poor registration or diagnosis capabilities (“The above methods for motion correction are applicable to arbitrary motions, including non-rigid motion. The third embodiment is preferably applied to motions where the positions of the body at different instants of time are connected by an affine transformation, including rigid motion of the body.” Paragraph 0023).
Response to Arguments
Applicant's appeal brief filed 05/21/2026 has been fully considered. With respect to applicant’s arguments concerning the previously made 103 rejections, the examiner agrees with the applicant that the previously cited source Bharat, when properly interpretated, does not teach all assigned limitations within claim 1. Particularly, the examiner agrees with the applicant that Bharat does not teach separate and independent motion correction and that the combination of Bharat and Hayden fails to teach that limitation, ultimately agreeing with applicant’s argument found in the third and fourth paragraphs (staring at line 15 ending 4 lines above the bottom) on page 7. Accordingly, it was decided to reopen prosecution and upon further search and consideration new rejections have been provided.
Because the combination of Hayden and Bharat is no longer being used to reject independent
claim 1, nor the substantially similar independent claims 11 and 16, applicant’s arguments regarding the patentably of the dependent claims due to the poor applicability of Hayden and Bharat are considered moot, and new rejections have been made.
Conclusion
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/REBECCA COLETTE WILLIAMS/Examiner, Art Unit 2677
/ANDREW W BEE/Supervisory Patent Examiner, Art Unit 2677
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