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
Applicant’s arguments with respect to claims 1, 14, and 20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Allowable Subject Matter
Claims 21 and 23 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.
Terminal Disclaimer
The terminal disclaimer filed on 04/09/2026 disclaiming the terminal portion of any patent granted on this application which would extend beyond the expiration date of U.S. Patent No. 11,596366 and U.S. Patent No. 12115009 has been reviewed and is accepted. The terminal disclaimer has been recorded.
Double Patenting
Pursuant of the terminal disclaimer filed 04/09/2026, the double patenting rejections have been withdrawn.
Claim Rejections - 35 USC § 112
Pursuant of Applicant’s amendments filed 04/09/2026, the rejections of claims 1-7, and 9-13 under 35 U.S.C. 112(b) has been withdrawn.
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.
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 1-5 and 9-18, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Schleyer, et al., US 20050123183 A1 in view of Thielemans, et al., US 20100220909 A1 and Wollenweber, S.D., US 20160163042 (disclosed in the IDS filed 01/06/2025).
Regarding claim 1, Schleyer teaches a method implemented on a machine having at least one processor and a storage device (the abstract discloses a system and method of correcting respiratory induced motion in nuclear medicine imaging. Images are acquired dynamically, and gated post-acquisition, generating a series of near motion-free bins. These bins are then aligned to produce a motion corrected image without extending the acquisition time), the method comprising:
for each of at least one scan region of a subject (spatial regions in [0010], [0023]), obtaining a motion curve of the scan region of the subject; ([0042] states that “the binning module 130 places each of the original, unfiltered frames in the appropriate bin by referencing the filtered counts-time series” and [0044] states that the binning module 130 divides the phase weighted counts into bins of equal count-range as opposed to equal time-ranges, as shown in FIG. 4. For example, a typical maximum amplitude of 2 cm for the phase weighted counts and R=16 (i.e., the number of near motion-free bins) translates to a maximum of 1.25 mm of respiratory induced motion in each near motion-free bin);
determining a spectrum corresponding to the motion curve (figs. 3A-3C depict frequency magnitude of pixels from liver spleen scans, showing background, edge of liver (respiratory frequency spike circled), and center of liver, respectively, due to motions of the liver spleen during the scans [0028] further discloses distinctions between the edge pixels and the central pixels. The frequency graphs in figs. 3A-3C correspond to the counts-time series graph of fig. 4);
PNG
media_image1.png
522
716
media_image1.png
Greyscale
determining a target frequency corresponding to a maximum signal intensity in the spectrum as a target frequency ([0028] states that “By specifying upper and lower frequencies, F.sub.up and F.sub.lo respectively, around the estimated respiration frequency F.sub.r, the pixel classification module 110 calculates the average amplitude of the frequencies in the search window”. The search window F.sub.win is the at least one spectrum segment containing the upper frequency F.sub.up);
determining at least one spectrum segment in the spectrum based on the determined target frequency; ([0028] states that “By specifying upper and lower frequencies, F.sub.up and F.sub.lo respectively, around the estimated respiration frequency F.sub.r, the pixel classification module 110 calculates the average amplitude of the frequencies in the search window”. The search window F.sub.win is the at least one spectrum segment containing the upper frequency F.sub.up);
determining whether there is a physiological motion in the scan region based on an intensity value of each of the at least one spectrum segment ([0025] discloses that “The pixel classification module or routine 110 of the processor 100 generates a filtered set of data by temporally and spatially Gaussian smoothing (one pixel full width half maximum) the frames to eliminate pixels not demonstrating respiratory motion characteristics in step 210. Since the respiration cycle is quasi-sinusoidal, the respiratory induced motion contains a dominant frequency component with approximately the same period as the respiration cycle itself”);
determining a scan mode for scanning the scan region based on whether there is the physiological motion in the scan region ([0010] states that “the respiratory motion correction technique and system utilize a temporal spectral analysis to determine the spatial regions in a dynamic scan which are subject to respiration motion…determines where, in the displacement phase of the respiration cycle, each frame lies from the change in counts within these spatial regions which are subject to respiration motion throughout the dynamic scan…places these frames into bins which contain other frames from equal displacement phases of the respiratory cycle, thereby effectively data gating the acquisition with a displacement based trigger, rather than temporally based…the inventive system and method processes list mode acquired data and images acquired as a dynamic scan, of short frame duration relative to respiratory period, so that minimal motion occurs during each frame”, meaning that a dynamic scanning mode using displacement triggering is used in the stead of a temporal parameters to perform the data acquisition).
Schleyer fails to teach wherein the motion curve indicates a change in a position of a point in the scan region over time; wherein the scan mode is a first mode when it is determined that there is no physiological motion in the scan region, the scan mode is a second mode when it is determined that there is the physiological motion in the scan region, the first mode is a static mode or a transmission mode, and the second mode is a gating mode.
However, within the same field of endeavor, Thielemans teaches a method and apparatus, for reducing motion related imaging artifacts, comprising determining an internal motion for of two regions of the object, each region having a different level of motion, scanning the first region using a first scan protocol based on the motion, scanning a second region using a second different scan protocol based on the motion, and generating an image of the object based on the first and second regions (see abstract), wherein the motion curve indicates a change in a position of a point in the scan region over time ([0046] discloses that To determine the motion within the object 16, the motion information is divided into regions, such as regions 160-163 based on the displacement of the motion signal using the motion characterization module 78, for example. More specifically, the motion information 182 is analyzed to determine if/when the motion information 182 exceeds or falls below a predetermined threshold, such as a threshold 202. Also see [0043]-[0044] and fig. 5A for the motion image); wherein the scan mode is a first mode when it is determined that there is no physiological motion in the scan region, the scan mode is a second mode when it is determined that there is the physiological motion in the scan region, the first mode is a static mode or a transmission mode, and the second mode is a gating mode ([0060] states that the method and apparatus described herein identify and characterize involuntary motion such as cardiac or respiratory motion. A first acquisition protocol for regions where there is large motion (e.g. around the diaphragm) is then utilized. A second acquisition protocol is utilized for regions having less motion. For example, regions having little motion utilize one protocol, e.g. ungated, whereas regions having more motion use a second protocol, e.g. longer acquisition time or more or shorter gates. Also see [0052]-[0053]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Schleyer, wherein the motion curve indicates a change in a position of a point in the scan region over time; wherein the scan mode is a first mode when it is determined that there is no physiological motion in the scan region, the scan mode is a second mode when it is determined that there is the physiological motion in the scan region, the first mode is a static mode or a transmission mode, and the second mode is a gating mode, as taught by Thielemans, to reduce motion artifacts (abstract), due to physiological motion ([0004]) and increase image quality ([0060]).
Schleyer in view of Thielemans does not teach generating a PET sub-image of the scan region based on PET data of the scan region acquired by scanning the scan region in the scan mode.
However, within the same field of endeavor, Wollenweber teaches a method (method 400 for imaging an object in [0037]) utilizing a sliding window to define segment sizes ([0037]) for PET listmode data acquisition ([0038]), the method comprising generating at least one PET sub-image of the at least one scan region based on PET data of the at least one scan region acquired in the scan mode ([0038] discloses defining a sliding window length, to correspond to a segment of PET data to be acquired, at step 404 and then based on the defined sliding window length, acquiring PET data for the defined data segment ([0039]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Schleyer as modified by Thielemans for generating at least one PET sub-image of the at least one scan region based on PET data of the at least one scan region acquired in the scan mode, as taught by Wollenweber, to reduce effects of motion artifacts in PET data while maintaining improved image quality ([0002]-[0003]), with a reasonable expectation of success, as Schleyer is also concerned with addressing limitations of motion correction protocols in PET image acquisitions ([0005]-[0004]).
Regarding claim 2, Schleyer in view of Thielemans and Wollenweber teaches all the limitations of claim 1 above.
Schleyer further teaches wherein the at least one spectrum segment includes a first spectrum segment, the first spectrum segment is a spectrum range where a target frequency is located or a union of the spectrum range where the target frequency is located and a spectrum range where 2 times the target frequency is located ([0028] states that “By specifying upper and lower frequencies, F.sub.up and F.sub.lo respectively, around the estimated respiration frequency F.sub.r, the pixel classification module 110 calculates the average amplitude of the frequencies in the search window”. The search window F.sub.win is the at least one spectrum segment containing the upper frequency F.sub.up).
Regarding claim 3, Schleyer in view of Thielemans and Wollenweber teaches all the limitations of claim 2 above.
Schleyer in view of the embodiment in fig. 4 of Wollenweber relied upon above does not teach wherein the determining whether there is a physiological motion in the at least one scan region based on an intensity value of each of the at least one spectrum segment ([0025] discloses that “The pixel classification module or routine 110 of the processor 100 generates a filtered set of data by temporally and spatially Gaussian smoothing (one pixel full width half maximum) the frames to eliminate pixels not demonstrating respiratory motion characteristics in step 210. Since the respiration cycle is quasi-sinusoidal, the respiratory induced motion contains a dominant frequency component with approximately the same period as the respiration cycle itself”) comprises: obtaining a ratio of a first intensity value of the first spectrum segment to a second intensity value of the spectrum; and determining whether there is a physiological motion in the at least one scan region based on the ratio.
However, in a separate embodiment, Wollenweber in fig. 1 discloses a method 100 of imaging an object ([0022]), the method comprising acquisition of PET data at step 102 ([0023]), determining a segment size at step 104 ([0026]). The method then analyzes an amount of motion for a current segment at step 106 ([0032]). Wollenweber teaches wherein the determining whether there is a physiological motion in the at least one scan region based on an intensity value of each of the at least one spectrum segment comprises: obtaining a ratio of a first intensity value of the first spectrum segment to a second intensity value of the spectrum (during the specifying of the amount of motion in a current segment at step 106, Wollenweber states in [0032] that “One or more metrics that may be determined using the PCA (or other computational technique) may be determined for each segment. The metric may describe or correspond to an amount of respiratory motion. For example, in some embodiments, R may be determined, where R is the ratio of a peak value in a respiratory frequency window to the mean value above the window for a Fourier transform of a waveform generated using the PCA”); and determining whether there is a physiological motion in the at least one scan region based on the ratio ([0032] discloses that an amount of motion for a current segment being analyzed is determined at step 106).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure modified Schleyer, wherein the determining whether there is a physiological motion in the at least one scan region based on an intensity value of each of the at least one spectrum segment comprises: obtaining a ratio of a first intensity value of the first spectrum segment to a second intensity value of the spectrum; and determining whether there is a physiological motion in the at least one scan region based on the ratio, as taught by Wollenweber, to reduce effects of motion artifacts in PET data while maintaining improved image quality ([0002]-[0003]), with a reasonable expectation of success, as Schleyer is also concerned with addressing limitations of motion correction protocols in PET image acquisitions ([0005]-[0004]).
Regarding claim 4, Schleyer in view of Thielemans and Wollenweber teaches all the limitations of claim 2 above.
Schleyer further teaches wherein the at least one spectrum segment further includes a second spectrum segment, the second spectrum segment includes a spectrum range where a noise is located ([0033] states that “the pixel classification module 110 applied a 3.times.3 median filter to the binary mask as defined by Equation (6) to reduce "salt and pepper" noise, i.e., data drop-out noise. The pixel classification module 110 applies this mask, which represents pixels of significant power, to the original frames to eliminate pixels not demonstrating respiratory motion characteristics”. With reference to the frequency graphs in figs. 3A-3C, the noise is contained within a window outside the search window F.sub.win).
Regarding claim 5, Schleyer in view of Thielemans and Wollenweber teaches all the limitations of claim 2 above.
Schleyer further teaches wherein the determining whether there is a physiological motion in the at least one scan region based on an intensity value of each of the at least one spectrum segment ([0025] discloses that “The pixel classification module or routine 110 of the processor 100 generates a filtered set of data by temporally and spatially Gaussian smoothing (one pixel full width half maximum) the frames to eliminate pixels not demonstrating respiratory motion characteristics in step 210. Since the respiration cycle is quasi-sinusoidal, the respiratory induced motion contains a dominant frequency component with approximately the same period as the respiration cycle itself”) comprises:
obtaining a ratio of a first intensity value of the first spectrum segment to a third intensity value of the second spectrum segment ([0032] states that “The reference windows allow the pixel classification module 110 to determine a ratio of respiratory signal power to non-respiratory signal power in”, where the respiratory signal power is the first intensity value and the non-respiratory signal power is the second intensity value); and
determining whether there is a physiological motion in the at least one scan region based on the ratio ([0032] further discloses generating a mask as a selection criteria, and [0032] states that “The binary mask determines which regions in the X-Y plane contain the edge of a moving structure”).
Regarding claim 9, Schleyer in view of Thielemans and Wollenweber teaches all the limitations of claim 1 above.
Schleyer in view of the embodiment in fig. 4 of Wollenweber relied upon above does not teach wherein the method further comprises: determining a scan volume of the subject supported by a scan table; and dividing the scan volume into the at least one scan region, wherein each of the at least one scan region corresponds to a table position.
However, However, in a separate embodiment, Wollenweber in fig. 6 discloses a method for determining scanning and/or processing parameters and/or imaging [0045], with step 606 of the method in fig. 6 calling for a scan range normalization ([0048]), such scan range normalization depicted in reproduced figure 7 below, and [0049] stating that “In view 710, a series of overlapping FOVs or bed positions 711, 712, 713, 714, 715, 716, 717, 718, 719, and 720 are shown. The illustrated FOVs correspond to bed positions having a 20% overlap, and to a range extending from a portion of the skull to about the knee. The various locations along the length of the patient are normalized in view 710. For example, the dashed line 730 corresponds to a superior-most location of the lung, and the dashed line 740 corresponds to an inferior-most location of the lung. The superior location 730 is assigned a normalized value of 1.0, and the inferior location 740 is assigned a normalized value of 0.0.”, thereby determining a scan volume of the subject supported by a scan table; and dividing the scan volume into the at least one scan region, wherein each of the at least one scan region corresponds to a table position, as required by the limitation. [0050] further describes the normalization steps from the view 750.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure modified Schleyer wherein the method further comprises: determining a scan volume of the subject supported by a scan table; and dividing the scan volume into the at least one scan region, wherein each of the at least one scan region corresponds to a table position, as taught by Wollenweber, to reduce effects of motion artifacts in PET data while maintaining improved image quality ([0002]-[0003]), with a reasonable expectation of success, as Schleyer is also concerned with addressing limitations of motion correction protocols in PET image acquisitions ([0005]-[0004]).
Regarding claim 10, Schleyer in view of Thielemans, Wollenweber’s embodiment in fig. 4 and embodiment in fig. 6 teaches all the limitations of claim 9 above.
Schleyer in view of Thielemans and Wollenweber’s embodiment in fig. 4 does not teach adjusting a statistical characteristic of the at least one scan region according to at least one table position corresponding to the at least one scan region, wherein the statistical characteristic of one of the at least one scan region includes at least one of a scan time period of the scan region, a scan velocity of the scan region, or a number of data frames of the scan region.
However, Wollenweber’s embodiment in fig. 6 further teaches adjusting a statistical characteristic of the at least one scan region according to at least one table position corresponding to the at least one scan region, wherein the statistical characteristic of one of the at least one scan region includes at least one of a scan time period of the scan region, a scan velocity of the scan region, or a number of data frames of the scan region ([0050] states that “One or more scanning and/or acquisition settings for the positions identified as more likely affected to be affected by motion (e.g., positions 712, 713, 714 in the example discussed above) may be adjusted relative to the other portions to account for the anticipated motion”, and [0052] states that “the method proceeds to 612, and motion mitigation scanning and/or analysis parameters are applied. For example, a scan time or duration for the position being analyzed may be increased at 612 based on the value of R, with higher values of R resulting in longer scan times or durations”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure modified Schleyer for adjusting a statistical characteristic of the at least one scan region according to at least one table position corresponding to the at least one scan region, wherein the statistical characteristic of one of the at least one scan region includes at least one of a scan time period of the scan region, a scan velocity of the scan region, or a number of data frames of the scan region, as taught by Wollenweber, to reduce effects of motion artifacts in PET data while maintaining improved image quality ([0002]-[0003]), with a reasonable expectation of success, as Schleyer is also concerned with addressing limitations of motion correction protocols in PET image acquisitions ([0005]-[0004]).
Regarding claim 11, Schleyer in view of Thielemans, Wollenweber’s embodiment in fig. 4 and embodiment in fig. 6 teaches all the limitations of claim 9 above.
Schleyer does not teach generating a PET image of the scan volume by stitching the at least one PET sub-image of the at least one scan region.
However, Wollenweber’s embodiment in fig. 4 further teaches generating a PET image of the scan volume by stitching the at least one PET sub-image of the at least one scan region, stating in [0040] that “If it is determined that all data segments have been analyzed, the method proceeds to 420. At 420, PET image data (e.g., slices of data and/or images from the various bed or detector positions) is stitched together, for example using conventional techniques”.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure modified Schleyer for generating a PET image of the scan volume by stitching the at least one PET sub-image of the at least one scan region, as taught by Wollenweber, to reduce effects of motion artifacts in PET data while maintaining improved image quality ([0002]-[0003]), with a reasonable expectation of success, as Schleyer is also concerned with addressing limitations of motion correction protocols in PET image acquisitions ([0005]-[0004]).
Regarding claim 12, Schleyer in view of Thielemans and Wollenweber teaches all the limitations of claim 1 above.
Schleyer further teaches wherein the scan mode is a gating mode in response to determining that there is a physiological motion in the at least one scan region ([0023] states “The processor 100 receives a dynamic image of the target organ having a plurality of frames, preferably a moving organ or an organ subject to respiratory motion, from any known nuclear medicine image system…The binning module 130 bins or places frames into bins containing other frames from equal displacement phases of the respiratory cycle, effectively data gating the acquisition with a displacement based trigger”), the PET data is divided into multiple data frames and the count of the multiple data frames is determined based on an amplitude of the physiological motion of the at least one scan region ([0041] states that “The binning module 130 convolves frames with the phase weighted mask defined by phase weighting module 120, and obtains total counts per frame, i.e., counts-time series or phase weighted counts in step 230” and [0042] states that “the binning module 130 places each of the original, unfiltered frames in the appropriate bin by referencing the filtered counts-time series”).
Schleyer in view of Thielemans and the embodiment in fig. 4 of Wollenweber relied upon above does not teach that the at least one PET sub-image is generated by performing gating reconstruction on the PET data of the at least one scan region acquired in the gating mode, during the gating reconstruction.
However, the embodiment in fig. 1 of Wollenweber further discloses that the at least one PET sub-image is generated by performing gating reconstruction on the PET data of the at least one scan region acquired in the gating mode, during the gating reconstruction ([0034] states that “At 110, if the amount of motion for a given segment satisfied the threshold, motion mitigation is performed on the data for the particular segment. Various motion mitigation techniques may be employed in various embodiments. For example, in some embodiments, PET coincident data for a segment having motion above the threshold may be gated to produce 4D PET image volumes used to generate a motion mitigated image volume”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure modified Schleyer such that the at least one PET sub-image is generated by performing gating reconstruction on the PET data of the at least one scan region acquired in the gating mode, during the gating reconstruction, as taught by Wollenweber, to reduce effects of motion artifacts in PET data while maintaining improved image quality ([0002]-[0003]), with a reasonable expectation of success, as Schleyer is also concerned with addressing limitations of motion correction protocols in PET image acquisitions ([0005]-[0004]).
Regarding claim 13, Schleyer in view of Thielemans and Wollenweber teaches all the limitations of claim 1 above.
Schleyer further teaches wherein the scan mode is a gating mode in response to determining that there is a physiological motion in the at least one scan region ([0023] states “The processor 100 receives a dynamic image of the target organ having a plurality of frames, preferably a moving organ or an organ subject to respiratory motion, from any known nuclear medicine image system…The binning module 130 bins or places frames into bins containing other frames from equal displacement phases of the respiratory cycle, effectively data gating the acquisition with a displacement based trigger”), and the method further comprises:
determining a scan duration based on an amplitude of the physiological motion of the at least one scan region; and collecting the PET data by performing a gating scan on the at least one scan region based on the scan duration ([0010] states that “the respiratory motion correction technique and system utilize a temporal spectral analysis to determine the spatial regions in a dynamic scan which are subject to respiration motion” and then further state that “the inventive system and method processes list mode acquired data and images acquired as a dynamic scan, of short frame duration relative to respiratory period, so that minimal motion occurs during each frame”. As [0028] discloses, the method specifies “upper and lower frequencies, F.sub.up and F.sub.lo respectively, around the estimated respiration frequency F.sub.r, the pixel classification module 110 calculates the average amplitude of the frequencies in the search window F.sub.win”).
Regarding claim 14, Schleyer teaches a system (the abstract discloses a system and method of correcting respiratory induced motion in nuclear medicine imaging. Images are acquired dynamically, and gated post-acquisition, generating a series of near motion-free bins. These bins are then aligned to produce a motion corrected image without extending the acquisition time), comprising:
at least one storage device storing a set of instructions; and at least one processor configured to communicate with the at least one storage device, wherein when executing the set of instructions, the at least one processor is configured to direct the system to perform operations ([0021] states “the data driven respiratory motion correction method for nuclear medicine imaging is a software program running on a processor or computer 100 of FIG. 1”, the processor 100 comprising one or more modules or routines performing various steps according to [0022] and configured for receiving dynamic image for processing [0023]. The computer inherently includes a computer readable medium for storing the software as evidenced by recitation in claims 24-27) including:
for each of at least one scan region of a subject (spatial regions in [0010], [0023]), obtaining a motion curve of the scan region of the subject; ([0042] states that “the binning module 130 places each of the original, unfiltered frames in the appropriate bin by referencing the filtered counts-time series” and [0044] states that the binning module 130 divides the phase weighted counts into bins of equal count-range as opposed to equal time-ranges, as shown in FIG. 4. For example, a typical maximum amplitude of 2 cm for the phase weighted counts and R=16 (i.e., the number of near motion-free bins) translates to a maximum of 1.25 mm of respiratory induced motion in each near motion-free bin);
determining a spectrum corresponding to the motion curve (figs. 3A-3C depict frequency magnitude of pixels from liver spleen scans, showing background, edge of liver (respiratory frequency spike circled), and center of liver, respectively, due to motions of the liver spleen during the scans [0028] further discloses distinctions between the edge pixels and the central pixels. The frequency graphs in figs. 3A-3C correspond to the counts-time series graph of fig. 4);
PNG
media_image1.png
522
716
media_image1.png
Greyscale
determining a target frequency corresponding to a maximum signal intensity in the spectrum as a target frequency ([0028] states that “By specifying upper and lower frequencies, F.sub.up and F.sub.lo respectively, around the estimated respiration frequency F.sub.r, the pixel classification module 110 calculates the average amplitude of the frequencies in the search window”. The search window F.sub.win is the at least one spectrum segment containing the upper frequency F.sub.up);
determining at least one spectrum segment in the spectrum based on the determined target frequency; ([0028] states that “By specifying upper and lower frequencies, F.sub.up and F.sub.lo respectively, around the estimated respiration frequency F.sub.r, the pixel classification module 110 calculates the average amplitude of the frequencies in the search window”. The search window F.sub.win is the at least one spectrum segment containing the upper frequency F.sub.up);
determining whether there is a physiological motion in the scan region based on an intensity value of each of the at least one spectrum segment ([0025] discloses that “The pixel classification module or routine 110 of the processor 100 generates a filtered set of data by temporally and spatially Gaussian smoothing (one pixel full width half maximum) the frames to eliminate pixels not demonstrating respiratory motion characteristics in step 210. Since the respiration cycle is quasi-sinusoidal, the respiratory induced motion contains a dominant frequency component with approximately the same period as the respiration cycle itself”);
determining a scan mode for scanning the scan region based on whether there is the physiological motion in the scan region ([0010] states that “the respiratory motion correction technique and system utilize a temporal spectral analysis to determine the spatial regions in a dynamic scan which are subject to respiration motion…determines where, in the displacement phase of the respiration cycle, each frame lies from the change in counts within these spatial regions which are subject to respiration motion throughout the dynamic scan…places these frames into bins which contain other frames from equal displacement phases of the respiratory cycle, thereby effectively data gating the acquisition with a displacement based trigger, rather than temporally based…the inventive system and method processes list mode acquired data and images acquired as a dynamic scan, of short frame duration relative to respiratory period, so that minimal motion occurs during each frame”, meaning that a dynamic scanning mode using displacement triggering is used in the stead of a temporal parameters to perform the data acquisition).
Schleyer fails to teach wherein the motion curve indicates a change in a position of a point in the scan region over time; wherein the scan mode is a first mode when it is determined that there is no physiological motion in the scan region, the scan mode is a second mode when it is determined that there is the physiological motion in the scan region, the first mode is a static mode or a transmission mode, and the second mode is a gating mode.
However, within the same field of endeavor, Thielemans teaches a method and apparatus, for reducing motion related imaging artifacts, comprising determining an internal motion for of two regions of the object, each region having a different level of motion, scanning the first region using a first scan protocol based on the motion, scanning a second region using a second different scan protocol based on the motion, and generating an image of the object based on the first and second regions (see abstract), wherein the motion curve indicates a change in a position of a point in the scan region over time ([0046] discloses that To determine the motion within the object 16, the motion information is divided into regions, such as regions 160-163 based on the displacement of the motion signal using the motion characterization module 78, for example. More specifically, the motion information 182 is analyzed to determine if/when the motion information 182 exceeds or falls below a predetermined threshold, such as a threshold 202. Also see [0043]-[0044] and fig. 5A for the motion image); wherein the scan mode is a first mode when it is determined that there is no physiological motion in the scan region, the scan mode is a second mode when it is determined that there is the physiological motion in the scan region, the first mode is a static mode or a transmission mode, and the second mode is a gating mode ([0060] states that the method and apparatus described herein identify and characterize involuntary motion such as cardiac or respiratory motion. A first acquisition protocol for regions where there is large motion (e.g. around the diaphragm) is then utilized. A second acquisition protocol is utilized for regions having less motion. For example, regions having little motion utilize one protocol, e.g. ungated, whereas regions having more motion use a second protocol, e.g. longer acquisition time or more or shorter gates. Also see [0052]-[0053]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Schleyer, wherein the motion curve indicates a change in a position of a point in the scan region over time; wherein the scan mode is a first mode when it is determined that there is no physiological motion in the scan region, the scan mode is a second mode when it is determined that there is the physiological motion in the scan region, the first mode is a static mode or a transmission mode, and the second mode is a gating mode, as taught by Thielemans, to reduce motion artifacts (abstract), due to physiological motion ([0004]) and increase image quality ([0060]).
Schleyer in view of Thielemans does not teach generating a PET sub-image of the scan region based on PET data of the scan region acquired by scanning the scan region in the scan mode.
However, within the same field of endeavor, Wollenweber teaches a method (method 400 for imaging an object in [0037]) utilizing a sliding window to define segment sizes ([0037]) for PET listmode data acquisition ([0038]), the method comprising generating at least one PET sub-image of the at least one scan region based on PET data of the at least one scan region acquired in the scan mode ([0038] discloses defining a sliding window length, to correspond to a segment of PET data to be acquired, at step 404 and then based on the defined sliding window length, acquiring PET data for the defined data segment ([0039]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Schleyer as modified by Thielemans for generating at least one PET sub-image of the at least one scan region based on PET data of the at least one scan region acquired in the scan mode, as taught by Wollenweber, to reduce effects of motion artifacts in PET data while maintaining improved image quality ([0002]-[0003]), with a reasonable expectation of success, as Schleyer is also concerned with addressing limitations of motion correction protocols in PET image acquisitions ([0005]-[0004]).
Regarding claim 15, Schleyer in view of Thielemans and Wollenweber teaches all the limitations of claim 14 above.
Schleyer further teaches wherein the at least one spectrum segment includes a first spectrum segment, the first spectrum segment is a spectrum range where a target frequency is located, or the first spectrum segment is a union of the spectrum range where the target frequency is located and a spectrum range where 2 times the target frequency is located ([0028] states that “By specifying upper and lower frequencies, F.sub.up and F.sub.lo respectively, around the estimated respiration frequency F.sub.r, the pixel classification module 110 calculates the average amplitude of the frequencies in the search window”. The search window F.sub.win is the at least one spectrum segment containing the upper frequency F.sub.up).
Regarding claim 16, Schleyer in view of Wollenweber teaches all the limitations of claim 15 above.
Schleyer in view of the embodiment in fig. 4 relied upon above does not teach wherein the determining whether there is a physiological motion in the scan region based on an intensity value of each of the at least one spectrum segment ([0025] discloses that “The pixel classification module or routine 110 of the processor 100 generates a filtered set of data by temporally and spatially Gaussian smoothing (one pixel full width half maximum) the frames to eliminate pixels not demonstrating respiratory motion characteristics in step 210. Since the respiration cycle is quasi-sinusoidal, the respiratory induced motion contains a dominant frequency component with approximately the same period as the respiration cycle itself”) comprises: obtaining a ratio of a first intensity value of the first spectrum segment to a second intensity value of the spectrum; and determining whether there is a physiological motion in the at least one scan region based on the ratio.
However, in a separate embodiment, Wollenweber in fig. 1 discloses a method 100 of imaging an object ([0022]), the method comprising acquisition of PET data at step 102 ([0023]), determining a segment size at step 104 ([0026]). The method then analyzes an amount of motion for a current segment at step 106 ([0032]). Wollenweber teaches wherein the determining whether there is a physiological motion in the scan region based on an intensity value of each of the at least one spectrum segment comprises: obtaining a ratio of a first intensity value of the first spectrum segment to a second intensity value of the spectrum (during the specifying of the amount of motion in a current segment at step 106, Wollenweber states in [0032] that “One or more metrics that may be determined using the PCA (or other computational technique) may be determined for each segment. The metric may describe or correspond to an amount of respiratory motion. For example, in some embodiments, R may be determined, where R is the ratio of a peak value in a respiratory frequency window to the mean value above the window for a Fourier transform of a waveform generated using the PCA”); and determining whether there is a physiological motion in the at least one scan region based on the ratio ([0032] discloses that an amount of motion for a current segment being analyzed is determined at step 106).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure modified Schleyer wherein the determining whether there is a physiological motion in the scan region based on an intensity value of each of the at least one spectrum segment comprises: obtaining a ratio of a first intensity value of the first spectrum segment to a second intensity value of the spectrum; and determining whether there is a physiological motion in the at least one scan region based on the ratio, as taught by Wollenweber, to reduce effects of motion artifacts in PET data while maintaining improved image quality ([0002]-[0003]), with a reasonable expectation of success, as Schleyer is also concerned with addressing limitations of motion correction protocols in PET image acquisitions ([0005]-[0004]).
Regarding claim 17, Schleyer in view of Wollenweber teaches all the limitations of claim 15 above.
Schleyer further teaches wherein the at least one spectrum segment further includes a second spectrum segment, the second spectrum segment includes a spectrum range where a noise is located ([0033] states that “the pixel classification module 110 applied a 3.times.3 median filter to the binary mask as defined by Equation (6) to reduce "salt and pepper" noise, i.e., data drop-out noise. The pixel classification module 110 applies this mask, which represents pixels of significant power, to the original frames to eliminate pixels not demonstrating respiratory motion characteristics”. With reference to the frequency graphs in figs. 3A-3C, the noise is contained within a window outside the search window F.sub.win), and the determining whether there is a physiological motion in the at least one scan region based on an intensity value of each of the at least one spectrum segment ([0025] discloses that “The pixel classification module or routine 110 of the processor 100 generates a filtered set of data by temporally and spatially Gaussian smoothing (one pixel full width half maximum) the frames to eliminate pixels not demonstrating respiratory motion characteristics in step 210. Since the respiration cycle is quasi-sinusoidal, the respiratory induced motion contains a dominant frequency component with approximately the same period as the respiration cycle itself”) comprises:
obtaining a ratio of a first intensity value of the first spectrum segment to a third intensity value of the second spectrum segment ([0032] states that “The reference windows allow the pixel classification module 110 to determine a ratio of respiratory signal power to non-respiratory signal power in”, where the respiratory signal power is the first intensity value and the non-respiratory signal power is the second intensity value); and
determining whether there is a physiological motion in the at least one scan region based on the ratio ([0032] further discloses generating a mask as a selection criteria, and [0032] states that “The binary mask determines which regions in the X-Y plane contain the edge of a moving structure”).
Regarding claim 18, Schleyer in view of Thielemans and Wollenweber teaches all the limitations of claim 14 above.
Schleyer does not teach wherein the first mode is a static mode or a transmission mode, and the second mode is a gating mode.
However, Thielemans further teaches wherein the first mode is a static mode ([0052] discloses that a single bin may be used and the fraction of time over the whole cycle that corresponds to this bin may be reduced to "freeze" the motion in a single image, effectively producing static images, and [0060] disclose ungated acquisition) or a transmission mode, and the second mode is a gating mode ([0050], [0052]-[0054]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure modified Schleyer, wherein the first mode is a static mode or a transmission mode, and the second mode is a gating mode, as taught by Thielemans, to reduce motion artifacts (abstract), due to physiological motion ([0004]) and increase image quality ([0060]).
Regarding claim 20, Schleyer teaches a non-transitory computer readable medium, comprising a set of instructions, wherein when executed by at least one processor, the set of instructions direct the at least one processor to effectuate a method ([0021] discloses a software program running on a processor or computer 100 of FIG. 1 for a data driven respiratory motion correction method), the method comprising:
for each of at least one scan region of a subject (spatial regions in [0010], [0023]), obtaining a motion curve of the scan region of the subject; ([0042] states that “the binning module 130 places each of the original, unfiltered frames in the appropriate bin by referencing the filtered counts-time series” and [0044] states that the binning module 130 divides the phase weighted counts into bins of equal count-range as opposed to equal time-ranges, as shown in FIG. 4. For example, a typical maximum amplitude of 2 cm for the phase weighted counts and R=16 (i.e., the number of near motion-free bins) translates to a maximum of 1.25 mm of respiratory induced motion in each near motion-free bin);
determining a spectrum corresponding to the motion curve (figs. 3A-3C depict frequency magnitude of pixels from liver spleen scans, showing background, edge of liver (respiratory frequency spike circled), and center of liver, respectively, due to motions of the liver spleen during the scans [0028] further discloses distinctions between the edge pixels and the central pixels. The frequency graphs in figs. 3A-3C correspond to the counts-time series graph of fig. 4);
PNG
media_image1.png
522
716
media_image1.png
Greyscale
determining a target frequency corresponding to a maximum signal intensity in the spectrum as a target frequency ([0028] states that “By specifying upper and lower frequencies, F.sub.up and F.sub.lo respectively, around the estimated respiration frequency F.sub.r, the pixel classification module 110 calculates the average amplitude of the frequencies in the search window”. The search window F.sub.win is the at least one spectrum segment containing the upper frequency F.sub.up);
determining at least one spectrum segment in the spectrum based on the determined target frequency; ([0028] states that “By specifying upper and lower frequencies, F.sub.up and F.sub.lo respectively, around the estimated respiration frequency F.sub.r, the pixel classification module 110 calculates the average amplitude of the frequencies in the search window”. The search window F.sub.win is the at least one spectrum segment containing the upper frequency F.sub.up);
determining whether there is a physiological motion in the scan region based on an intensity value of each of the at least one spectrum segment ([0025] discloses that “The pixel classification module or routine 110 of the processor 100 generates a filtered set of data by temporally and spatially Gaussian smoothing (one pixel full width half maximum) the frames to eliminate pixels not demonstrating respiratory motion characteristics in step 210. Since the respiration cycle is quasi-sinusoidal, the respiratory induced motion contains a dominant frequency component with approximately the same period as the respiration cycle itself”);
determining a scan mode for scanning the scan region based on whether there is the physiological motion in the scan region ([0010] states that “the respiratory motion correction technique and system utilize a temporal spectral analysis to determine the spatial regions in a dynamic scan which are subject to respiration motion…determines where, in the displacement phase of the respiration cycle, each frame lies from the change in counts within these spatial regions which are subject to respiration motion throughout the dynamic scan…places these frames into bins which contain other frames from equal displacement phases of the respiratory cycle, thereby effectively data gating the acquisition with a displacement based trigger, rather than temporally based…the inventive system and method processes list mode acquired data and images acquired as a dynamic scan, of short frame duration relative to respiratory period, so that minimal motion occurs during each frame”, meaning that a dynamic scanning mode using displacement triggering is used in the stead of a temporal parameters to perform the data acquisition).
Schleyer fails to teach wherein the motion curve indicates a change in a position of a point in the scan region over time; wherein the scan mode is a first mode when it is determined that there is no physiological motion in the scan region, the scan mode is a second mode when it is determined that there is the physiological motion in the scan region, the first mode is a static mode or a transmission mode, and the second mode is a gating mode.
However, within the same field of endeavor, Thielemans teaches a method and apparatus, for reducing motion related imaging artifacts, comprising determining an internal motion for of two regions of the object, each region having a different level of motion, scanning the first region using a first scan protocol based on the motion, scanning a second region using a second different scan protocol based on the motion, and generating an image of the object based on the first and second regions (see abstract), wherein the motion curve indicates a change in a position of a point in the scan region over time ([0046] discloses that To determine the motion within the object 16, the motion information is divided into regions, such as regions 160-163 based on the displacement of the motion signal using the motion characterization module 78, for example. More specifically, the motion information 182 is analyzed to determine if/when the motion information 182 exceeds or falls below a predetermined threshold, such as a threshold 202. Also see [0043]-[0044] and fig. 5A for the motion image); wherein the scan mode is a first mode when it is determined that there is no physiological motion in the scan region, the scan mode is a second mode when it is determined that there is the physiological motion in the scan region, the first mode is a static mode or a transmission mode, and the second mode is a gating mode ([0060] states that the method and apparatus described herein identify and characterize involuntary motion such as cardiac or respiratory motion. A first acquisition protocol for regions where there is large motion (e.g. around the diaphragm) is then utilized. A second acquisition protocol is utilized for regions having less motion. For example, regions having little motion utilize one protocol, e.g. ungated, whereas regions having more motion use a second protocol, e.g. longer acquisition time or more or shorter gates. Also see [0052]-[0053]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Schleyer, wherein the motion curve indicates a change in a position of a point in the scan region over time; wherein the scan mode is a first mode when it is determined that there is no physiological motion in the scan region, the scan mode is a second mode when it is determined that there is the physiological motion in the scan region, the first mode is a static mode or a transmission mode, and the second mode is a gating mode, as taught by Thielemans, to reduce motion artifacts (abstract), due to physiological motion ([0004]) and increase image quality ([0060]).
Schleyer in view of Thielemans does not teach generating a PET sub-image of the scan region based on PET data of the scan region acquired by scanning the scan region in the scan mode.
However, within the same field of endeavor, Wollenweber teaches a method (method 400 for imaging an object in [0037]) utilizing a sliding window to define segment sizes ([0037]) for PET listmode data acquisition ([0038]), the method comprising generating at least one PET sub-image of the at least one scan region based on PET data of the at least one scan region acquired in the scan mode ([0038] discloses defining a sliding window length, to correspond to a segment of PET data to be acquired, at step 404 and then based on the defined sliding window length, acquiring PET data for the defined data segment ([0039]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Schleyer as modified by Thielemans for generating at least one PET sub-image of the at least one scan region based on PET data of the at least one scan region acquired in the scan mode, as taught by Wollenweber, to reduce effects of motion artifacts in PET data while maintaining improved image quality ([0002]-[0003]), with a reasonable expectation of success, as Schleyer is also concerned with addressing limitations of motion correction protocols in PET image acquisitions ([0005]-[0004]).
Regarding claim 22, , Schleyer in view of Thielemans and Wollenweber teaches all the limitations of claim 1 above.
Schleyer fails to teach wherein the motion curve of the scan region of the subject is determined based on first PET data of the scan region collected in the first mode, and the generating a PET sub-image of the scan region based on PET data of the scan region acquired by scanning the scan region in the scan mode comprises: in response to that the scan mode is the first mode, generating the PET sub-image of the scan region based on the first PET data of the scan region; or in response to that the scan mode is the second mode, obtaining second PET data of the scanning region by scanning the scan region in the second mode, and generating the PET sub-image of the scan region based on the second PET data of the scan region.
However, Thielemans further teaches Schleyer fails to teach wherein the motion curve of the scan region of the subject is determined based on first PET data of the scan region collected in the first mode (see figs. 5A-5C), and the generating a PET sub-image of the scan region based on PET data of the scan region acquired by scanning the scan region in the scan mode comprises: in response to that the scan mode is the first mode, generating the PET sub-image of the scan region based on the first PET data of the scan region; or in response to that the scan mode is the second mode, obtaining second PET data of the scanning region by scanning the scan region in the second mode, and generating the PET sub-image of the scan region based on the second PET data of the scan region ([0049] states that at 208 a scan protocol is selected for each anatomical region, e.g. anatomical regions 164-167 based on the determined motion as describe above. As discussed above, each anatomical region 164-167 is defined based on the quantity of real-time motion within the respective anatomical region. Accordingly, a scan protocol is selected for each anatomical region based on the real-time motion within each respective motion region; and [0053] states that More specifically, referring again to FIG. 5C, the first anatomical region 164 has relatively little motion. Accordingly, the information obtained during the scanning operation may be gated to a single bin 240. Moreover, the second anatomical region 165 has an increased quantity of motion. As discussed above, the second anatomical region 165 may be scanned at a slower scanning speed to generate an increased quantity of information. In the exemplary embodiment, the scan protocol controlling bin quantity for the second anatomical region 165 is modified to provide an increased quantity of bins 242 that are potentially configured to receive the increased quantity of motion information obtained during the slower scanning procedure).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Schleyer as modified by Thielemans for generating at least one PET sub-image of the at least one scan region based on PET data of the at least one scan region acquired in the scan mode, as taught by Wollenweber, to reduce effects of motion artifacts in PET data while maintaining improved image quality ([0002]-[0003]), with a reasonable expectation of success, as Schleyer is also concerned with addressing limitations of motion correction protocols in PET image acquisitions ([0005]-[0004]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US 20150021488 A1 discloses PET/CT scanner that performs continuous table motion scanning and also switches between static and gated image acquisition modes.
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 Farouk A Bruce whose telephone number is (408)918-7603. The examiner can normally be reached Mon-Fri 8-5pm PST.
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, Christopher Koharski can be reached at (571) 272-7230. 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.
/FAROUK A BRUCE/ Examiner, Art Unit 3797
/CHRISTOPHER KOHARSKI/ Supervisory Patent Examiner, Art Unit 3797
Prosecution Insights