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.
Claims 1-4, 13, and 16-17 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Xie (“Robust EPI Nyquist Ghost Removal by Incorporating Phase Error Correction With Sensitivity Encoding (PEC-SENSE)”).
Regarding claim 1, Xie teaches a method for generating calibration data for completing undersampled measurement data of an object to be examined via a magnetic resonance system, comprising:
recording N measurement data sets using an acquisition scheme that subsamples k-space with an acceleration factor R, with N being is greater than or equal to R, and the N measurement data sets together sampling the k-space completely [See Page 943, “In these methods, single-shot EPI k space data are separated into positive and negative echo groups based on their readout polarity. Each group can be treated as a data set that is undersampled by twice the acceleration factor and thus can be reconstructed into a ghost-free image using parallel imaging reconstruction methods.” Fig. 1, wherein the acceleration factor is 1 because the combined k-space is completely sampled and there are two groups. See also rest of reference.];
generating phase images from the N recorded measurement data sets [See two images formed from the datasets in Fig. 1, where a phase different is determined from the two images. See also rest of reference.];
determining a homogeneity value of the phase images [See phase difference values. The phase difference will show how homogeneous the two images’ phases are. See also rest of reference.]; and
generating a complete calibration data set based upon the N recorded measurement data sets and the homogeneity value [The phase error map is incorporated it into the sensitivity encoding (SENSE) reconstruction for Nyquist ghost correction. See also rest of reference.].
Regarding claim 2, Xie further teaches wherein each phase image from among the phase images is generated from each respective one of the N recorded measurement data sets [See positive and negative image in Fig. 1. See also rest of reference.].
Regarding claim 3, Xie further teaches wherein a number M of recorded measurement data sets are combined to form a combined measurement data set [See Fig. 1, wherein the two phase difference images are combined to form the phase difference image. See also rest of reference.], and further comprising: determining a phase image of the combined measurement data set, wherein 2<M<R [See phase difference image. See also rest of reference.].
Regarding claim 4, Xie further teaches wherein the M recorded measurement data sets of the combined measurement data set completely scan k-space [Fig. 1, wherein the two datasets form a complete k-space. See also rest of reference.].
Regarding claim 13, Xie further teaches wherein the recorded measurement data sets comprise measurement data sets to be recorded repeatedly as part of a functional magnetic resonance measurement [See the inventive method can be used with fMRI. See also rest of reference.].
Regarding claim 16, the same reasons for rejection as claim 1 also apply to this claim. Claim 16 is merely the apparatus version of method claim 1.
Regarding claim 17, the same reasons for rejection as claim 1 also apply to this claim. Claim 16 is merely the non-transitory computer readable medium version of method claim 1.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over previously cited Xie, in view of Huang (US 2019/0041479).
Regarding claim 5, Xie teaches the limitations of claim 3, which this claim depends from.
However, Xie is silent in teaching further comprising: generating a combined measurement data set comprising two recorded measurement data sets that are averaged, the two recorded measurement data sets scanning the same k-space positions.
Huang, which is also in the field of MRI, teaches further comprising: generating a combined measurement data set comprising two recorded measurement data sets that are averaged, the two recorded measurement data sets scanning the same k-space positions [¶0011. See also rest of reference.].
It would have been obvious to a person having ordinary skill in the art before the filing date of the claimed invention to combine the teachings of Xie and Huang because both references are in the field of MRI and Huang teaches it is known to average k-space data when multiple k-space data sets are acquired [Huang - ¶0011. See also rest of reference.].
Claims 6-7, 9-10, and 15 are rejected under 35 U.S.C. 103 as being unpatentable over previously cited Xie, in view of Liang (“Prospective motion detection and re-acquisition in diffusion MRI using a phase image–based method—Application to brain and tongue imaging”).
Regarding claim 6, Xie teaches the limitations of claim 1, which this claim depends from.
Xie further teaches further comprising: comparing homogeneity values of respective phase images [See phase difference map. See also rest of reference.]; Xie further teaches a first combined measurement data set [See single shot EPI wherein the even echoes are combined vs the odd echoes are combined. See also rest of reference.] and measurement data sets combined from (i) other recorded measurement data sets [See single shot EPI wherein the even echoes are combined vs the odd echoes are combined. See also rest of reference.].
However, Xie is silent in teaching when a deviation of a homogeneity value of a phase image determined from a first recorded measurement data set and homogeneity values of other determined phase images of measurement data sets exceeds a first predetermined threshold value, the first recorded measurement data set is not used in the generation of the calibration data set; and when a deviation of a homogeneity value of a phase image determined from a first measurement data set and homogeneity values of other determined phase images of measurement data sets.
Liang, which is also in the field of MRI, teaches when a deviation of a homogeneity value of a phase image determined from a first recorded measurement data set and homogeneity values of other determined phase images of measurement data sets exceeds a first predetermined threshold value, the first recorded measurement data set is not used in the generation of the calibration data set [Section 2.1.1-2.1.2, wherein the dataset is reacquired if the HHI is below a threshold. See also rest of reference.]; and when a deviation of a homogeneity value of a phase image determined from a first measurement data set and homogeneity values of other determined phase images of measurement data sets [Section 2.1.1-2.1.2, wherein the dataset is reacquired if the HHI is below a threshold. See also rest of reference.].
It would have been obvious to a person having ordinary skill in the art before the filing date of the claimed invention to combine the teachings of Xie and Liang because both references teach acquiring phase images in MRI and because Liang it is known in the art to use Haralick’s homogeneity index (HHI) as a quantitative metric of phase image homogeneity [Liang - See Haralick’s homogeneity index (HHI). See also rest of reference.].
Regarding claim 7, Xie teaches the limitations of claim 1, which this claim depends from.
Xie is silent in teaching further comprising: comparing homogeneity values of respective phase images with a predetermined minimum homogeneity value; when the homogeneity value of a respective phase image determined from (i) a second recorded measurement data set, or (ii) from a second combined measurement data set, does not meet the minimum homogeneity value, the second recorded measurement data set or the second combined measurement data set identified that does not meet the minimum homogeneity value is not used in the generation of the calibration data set.
Liang further teaches further comprising: comparing homogeneity values of respective phase images with a predetermined minimum homogeneity value [Section 2.1.1-2.1.2, wherein the dataset is reacquired if the HHI is below a threshold. See also rest of reference.]; when the homogeneity value of a respective phase image determined from (i) a second recorded measurement data set, or (ii) from a second combined measurement data set, does not meet the minimum homogeneity value, the second recorded measurement data set or the second combined measurement data set identified that does not meet the minimum homogeneity value is not used in the generation of the calibration data set [Section 2.1.1-2.1.2, wherein the dataset is reacquired if the HHI is below a threshold. See also rest of reference.].
It would have been obvious to a person having ordinary skill in the art before the filing date of the claimed invention to combine the teachings of Xie and Liang because both references teach acquiring phase images in MRI and because Liang it is known in the art to use Haralick’s homogeneity index (HHI) as a quantitative metric of phase image homogeneity [Liang - See Haralick’s homogeneity index (HHI). See also rest of reference.].
Regarding claim 9, Xie and Liang teach the limitations of claim 9, which this claim depends from.
Xie is silent in teaching wherein a new recording of measurement data sets identified as having respective homogeneity values deviating from the first predetermined threshold value or the second predetermined threshold value is carried out when a complete calibration data set cannot be created.
Liang further teaches wherein a new recording of measurement data sets identified as having respective homogeneity values deviating from the first predetermined threshold value or the second predetermined threshold value is carried out when a complete calibration data set cannot be created[Section 2.1.1-2.1.2, wherein the dataset is reacquired if the HHI is below a threshold. See also rest of reference.].
It would have been obvious to a person having ordinary skill in the art before the filing date of the claimed invention to combine the teachings of Xie and Liang because both references teach acquiring phase images in MRI and because Liang it is known in the art to use Haralick’s homogeneity index (HHI) as a quantitative metric of phase image homogeneity [Liang - See Haralick’s homogeneity index (HHI). See also rest of reference.].
Regarding claim 10, Xie teaches the limitations of claim 1, which this claim depends from.
Xie is silent in teaching wherein the determination of a homogeneity value comprises: calculating absolute values of phase gradients, a determination of auto-correlation values of the phase images in one dimension, and/or a determination of Haralick's homogeneity index.
Liang, which is also in the field of MRI, teaches wherein the determination of a homogeneity value comprises: calculating absolute values of phase gradients, a determination of auto-correlation values of the phase images in one dimension, and/or a determination of Haralick's homogeneity index [See Haralick’s homogeneity index (HHI). See also rest of reference.].
It would have been obvious to a person having ordinary skill in the art before the filing date of the claimed invention to combine the teachings of Xie and Liang because both references teach acquiring phase images in MRI and because Liang teaches it is known in the art to use Haralick’s homogeneity index (HHI) as a quantitative metric of phase image homogeneity [Liang - See Haralick’s homogeneity index (HHI). See also rest of reference.].
Regarding claim 15, Xie teaches the limitations of claim 1, which this claim depends from.
Xie is silent in teaching wherein the recorded measurement data sets comprise reference data measurements to be performed repeatedly as part of dynamic field corrections or as dynamic reference measurements.
Liang, which is also in the field of MRI, teaches wherein the recorded measurement data sets comprise reference data measurements to be performed repeatedly as part of dynamic field corrections or as dynamic reference measurements [See no-motion image. See also rest of reference.].
It would have been obvious to a person having ordinary skill in the art before the filing date of the claimed invention to combine the teachings of Xie and Liang because both references teach acquiring phase images in MRI and because Liang teaches acquiring no-motion images for motion correction [Liang – Page 725. See no-motion image. See also rest of reference.].
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over previously cited Xie, in view of Weingartner (US 2018/0067176).
Regarding claim 8, Xie teaches the limitations of claim 4, which this claim depends from.
Xie further teaches wherein different combined measurement data sets are composed of at least partially different recorded measurement data sets [See Fig. 1, wherein the even and odd echo data sets are combined. See also rest of reference.], and using, as a calibration data set, one of the different combined measurement data sets having a phase image corresponding to a predetermined homogeneity value [The phase error map is incorporated it into the sensitivity encoding (SENSE) reconstruction for Nyquist ghost correction. See also rest of reference.].
However, Xie is silent in teaching comparing the determined homogeneity values of the respective phase images generated from the different combined measurement data sets.
Weingartner, which is also in the field of MRI, teaches wherein different combined measurement data sets are composed of at least partially different recorded measurement data sets [¶0022, wherein the pulse sequence (Fig. 2) is repeated multiple times and the data is combined to form first and second images. See also rest of reference.], and further comprising: comparing the determined homogeneity values of the respective phase images generated from the different combined measurement data sets [See phase difference data. See also rest of reference.]; and using, as a calibration data set, one of the different combined measurement data sets having a phase image corresponding to a predetermined homogeneity value [Fig. 1 and ¶0029, see B1+ maps are used for calibration. See also rest of reference.].
It would have been obvious to a person having ordinary skill in the art before the filing date of the claimed invention to combine the teachings of Xie and Weingartner because both methods include using MRI to acquire phase difference data and because Weingartner teaches it is known in the art to use phase difference data to calibrate the B1 field [Weingartner – see B1 shimming].
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over previously cited Xie, in view of Herbst (US 2021/0270918).
Regarding claim 11, Xie teaches the limitations of claim 1, which this claim depends from.
Xie further teaches performing a phase correction of the recorded measurement data sets to generate phase- corrected measurement data sets [See final image is corrected by the phase difference data. See also rest of reference.].
However, Xie is silent in teaching generating the phase images from the phase-corrected measurement data sets.
Herbst, which is also in the field of MRI, teaches further comprising: performing a phase correction of the recorded measurement data sets to generate phase- corrected measurement data sets [Fig. 8 and ¶0068, wherein the datasets which include phase data are smoothed. See also rest of reference.]; and generating the phase images from the phase-corrected measurement data sets [Fig. 8 and ¶0068, wherein the datasets which include phase data are smoothed. See also rest of reference.].
It would have been obvious to a person having ordinary skill in the art before the filing date of the claimed invention to combine the teachings of Xie and Herbst because both references are in the field of phase images in MRI and because Herbst teaches it is known in the art to smooth data to remove noise [Herbst – see smoothing. See also rest of reference.].
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over previously cited Xie, in view of Blashe (US 2017/0261582).
Regarding claim 12, Xie teaches the limitations of claim 1, which this claim depends from.
Xie is silent in teaching wherein the recorded measurement data sets comprise measurement data sets to be recorded repeatedly as part of a diffusion measurement with a diffusion value b=0.
Blashe, which is also in the field of MRI, teaches wherein the recorded measurement data sets comprise measurement data sets to be recorded repeatedly as part of a diffusion measurement with a diffusion value b=0 [¶0020. See also rest of reference.].
It would have been obvious to a person having ordinary skill in the art before the filing date of the claimed invention to combine the teachings of Xie and Blashe are both in the field of MRI and because Xie teaches their method can be used with diffusion tensor imaging [Xie – Page 949. See also rest of reference.].
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over previously cited Xie, in view of Zeller (US 2020/0088826).
Regarding claim 14, Xie teaches the limitations of claim 1, which this claim depends from.
Xie is silent in teaching wherein the recorded measurement data sets are acquired as part of dummy recordings.
Zeller, which is also in the field of MRI, teaches wherein the recorded measurement data sets are acquired as part of dummy recordings [See dummy scans. See also rest of reference.].
It would have been obvious to a person having ordinary skill in the art before the filing date of the claimed invention to combine the teachings of Xie and Zeller are both in the field of MRI and because Zeller teaches it is known to use dummy scans to establish steady-state of acquired MRI signals [Zeller - See dummy scans. See also rest of reference.].
Conclusion
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/RISHI R PATEL/ Primary Examiner, Art Unit 2896