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 .
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-15 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1, lines 13-16 recites “in which a mismatch between the coil sensitivity maps and the magnetic resonance image caused by a motion of the subject during the acquisition is reduced by operating the transformation operator on the coil sensitivity maps and/or on the magnetic resonance image.” However, “the magnetic resonance image” is not defined in the claimed process until the subsequent step recited in claim 1, line 17 of “reconstructing the motion-corrected magnetic resonance image.” Applicant’s originally filed specification filed 10/23/25 appears to disclose an iterative reconstruction, wherein the intent in the recited claim appears to refer to a current estimate of the image; however, this is not clear from the claim and is not recited therein.
Claim 1 recites the limitation “a phase factor corresponding to the motion state held by the subject at the time of acquiring the corresponding subset of k-space data” in lines 20-21. There is insufficient antecedent basis for this limitation in the claim. Applicant’s originally filed specification filed 10/23/25 discloses in equations (4), (5), (7), (9), and the corresponding parts of the description that it should be defined that each k-space point of such subset comprised in the respective group should be phase corrected with a corresponding phase factor, or in other words there should be a phase factor for each k-space point of each subset contained in a respective group.
Claim 9, lines 5-7 recites “wherein the motion states are optionally corrected by the transformation operator, if the transformation operator is operated onto the magnetic resonance image, whereby the image is pre-rotated and/or pre-shifted.” The phrase "optionally" renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
Claim 13, lines 3-5 recites “selecting an image reconstruction process according to the number of groups of motion states or to comprise an image reconstruction process using the SENSE + motion model wherein the groups of motion states are combined to reduce a reconstruction time. The first alternative in the limitations of “selecting an image reconstruction process according to the number of groups of motion states” appears to correspond to the steps recited in claim 1, lines 12-21. However, the second alternative in the limitations of “to comprise an image reconstruction process using the SENSE + motion model wherein the groups of motion states are combined to reduce a reconstruction time” are distinct from the steps recited in claim 1, lines 12-21 and instead apply the conventional SENSE+motion reconstruction which is distinct from the NuFT reconstruction as recited in claim 1, lines 12-21 (i.e., steps (e) and (f)). Applicant’s originally filed specification filed 10/23/25 paragraphs [0036]-[0041], paragraph [0050], paragraphs [0065]-[0071], and paragraphs [0080]-[0096] disclose this distinction. Therefore, as claim 1, lines 12-21 appears to be specific to the first alternative, the scope of claim 13 is unclear/indefinite when the second alternative is selected as claim 13 incorporates the limitations of claim 1 including those of claim 1, lines 12-21.
Claim 14, lines 15-18 recites “in which a mismatch between the coil sensitivity maps and the magnetic resonance image caused by a motion of the subject during the acquisition is reduced by operating the transformation operator on the coil sensitivity maps and/or on the magnetic resonance image.” However, “the magnetic resonance image” is not defined in the claimed process until the subsequent step recited in claim 14, line 19 of “reconstruct the motion-corrected magnetic resonance image.” Applicant’s originally filed specification filed 10/23/25 appears to disclose an iterative reconstruction, wherein the intent in the recited claim appears to refer to a current estimate of the image; however, this is not clear from the claim and is not recited therein.
Claim 14 recites the limitation “a phase factor corresponding to the motion state held by the subject at the time of acquiring the corresponding subset of k-space data” in lines 22-23. There is insufficient antecedent basis for this limitation in the claim. Applicant’s originally filed specification filed 10/23/25 discloses in equations (4), (5), (7), (9), and the corresponding parts of the description that it should be defined that each k-space point of such subset comprised in the respective group should be phase corrected with a corresponding phase factor, or in other words there should be a phase factor for each k-space point of each subset contained in a respective group.
Claim 15, lines 14-17 recites “in which a mismatch between the coil sensitivity maps and the magnetic resonance image caused by a motion of the subject during the acquisition is reduced by operating the transformation operator on the coil sensitivity maps and/or on the magnetic resonance image.” However, “the magnetic resonance image” is not defined in the claimed process until the subsequent step recited in claim 15, line 18 of to “reconstruct the motion-corrected magnetic resonance image.” Applicant’s originally filed specification filed 10/23/25 appears to disclose an iterative reconstruction, wherein the intent in the recited claim appears to refer to a current estimate of the image; however, this is not clear from the claim and is not recited therein.
Claim 15 recites the limitation “a phase factor corresponding to the motion state held by the subject at the time of acquiring the corresponding subset of k-space data” in lines 21-23. There is insufficient antecedent basis for this limitation in the claim. Applicant’s originally filed specification filed 10/23/25 discloses in equations (4), (5), (7), (9), and the corresponding parts of the description that it should be defined that each k-space point of such subset comprised in the respective group should be phase corrected with a corresponding phase factor, or in other words there should be a phase factor for each k-space point of each subset contained in a respective group.
Claims 2-8, and 10-13 are rejected as depending from and incorporating all the limitations of independent claim 1.
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim 13 is rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends.
Claim 13, lines 3-5 recites “selecting an image reconstruction process according to the number of groups of motion states or to comprise an image reconstruction process using the SENSE + motion model wherein the groups of motion states are combined to reduce a reconstruction time. The first alternative in the limitations of “selecting an image reconstruction process according to the number of groups of motion states” appears to correspond to the steps recited in claim 1, lines 12-21. However, the second alternative in the limitations of “to comprise an image reconstruction process using the SENSE + motion model wherein the groups of motion states are combined to reduce a reconstruction time” are distinct from the steps recited in claim 1, lines 12-21 and instead apply the conventional SENSE+motion reconstruction which is distinct from the NuFT reconstruction as recited in claim 1, lines 12-21 (i.e., steps (e) and (f)). Applicant’s originally filed specification filed 10/23/25 paragraphs [0036]-[0041], paragraph [0050], paragraphs [0065]-[0071], and paragraphs [0080]-[0096] disclose this distinction. Therefore, as claim 1, lines 12-21 appears to be specific to the first alternative, claim 13, lines 3-5 appear to broaden rather than limit independent claim 1 from which it depends by providing a second alternative whereby the limitations of claim 1, lines 12-21 are not encompassed by claim 13.
Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
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 1-5 and 9-13 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Yarach (“Correction of residual artifacts in prospectively motion-corrected MR-data” 2016), hereinafter “Yarach.”
Regarding claim 1, Yarach discloses a computer-implemented method for reconstructing a motion-corrected magnetic resonance image of a subject (reconstructing a motion-corrected magnetic resonance image of a subject using software running on a computer, P.53, ¶1; see also P.74, ¶2 and P.93, ¶3), the method comprising:
receiving k-space magnetic resonance image data acquired of the subject using a multi-channel coil array during a magnetic resonance imaging acquisition (receiving k-space magnetic resonance image data acquired of the subject using a multi-channel coil array during a magnetic resonance imaging acquisition, P.37, ¶3 – P.41, ¶2; P.45, ¶3 -P.48, ¶1, P.52, ¶1-3);
receiving coil sensitivity maps of the multi-channel coil array (receiving coil sensitivity maps of the multi-channel coil array, P.37, ¶3 – P.41, ¶2; P.45, ¶1 -P.48, ¶1, P.52, ¶1-3, P.53, ¶1, P.53, ¶3 – P.55, ¶1);
receiving a motion trajectory comprising a series of motion states that were held by the subject during the acquisition (receiving a motion parameter comprising a series of motion poses that were held by the subject, P.53, ¶1-2);
determining similarities across the motion states (comparing similarities across the motion poses, P.53, ¶1-2);
forming groups of motion states such that each group contains motion states that are similar to each other (forming partitions of motion poses such that each partition contains motion poses that are similar to each other, P.53, ¶1-2); and
determining a single group motion state representing each group (determining a single partition motion pose representing each partition, P.53, ¶1-2);
computing, for each group of motion states, a single transformation operator and building a group-specific NuFT forward model, in which a mismatch between the coil sensitivity maps and the magnetic resonance image caused by a motion of the subject during the acquisition is reduced by operating the transformation operator on the coil sensitivity maps and/or on the magnetic resonance image (computing, for each partition of motion poses, a single forward operator and building a partition-specific non-uniform fast Fourier transform forward model, in which a mismatch between the coil sensitivity maps and the magnetic resonance image caused by a motion of the subject during the acquisition is reduced by operating the forward/encoding operator on the coil sensitivity maps, P.2, ¶2, P.29, ¶3 – P.30, ¶1, P.37, ¶3 – P.41, ¶2, P.43, ¶2 – P.44, ¶3, P.44, ¶4 – P.45, ¶ 2, P.51, ¶7, P.53, ¶3 – P.56, P.66, ¶2 – P.72, ¶2, P.73, ¶2); and
reconstructing the motion-corrected magnetic resonance image by minimizing a data consistency error between the received k-space data and the group-specific NuFT forward models, wherein each NuFT forward model comprises an image estimate, the coil sensitivity maps, a non-uniform Fourier Transformation, and a phase factor corresponding to the motion state held by the subject at a time of acquiring the corresponding subset of k-space data (reconstructing the motion-corrected magnetic resonance image by minimizing a data consistency error between the received k-space data and the partition-specific non-uniform fast Fourier transform forward models, wherein each non-uniform fast Fourier transform forward model comprises an image estimate, the coil sensitivity maps, a non-uniform fast Fourier transformation, and a phase factor corresponding to the motion pose held by the subject at a time of acquiring the corresponding subset of k-space data, P.37, ¶3 – P.41, ¶2, P.43, ¶2 – P.44, ¶3, P.44, ¶4 – P.45, ¶ 2, P.51, ¶7, P.53, ¶1 – P.56, P.66, ¶2 – P.72, ¶2).
Regarding claim 2, Yarach discloses the single transformation operator is computed based on the group motion state (the single forward operator is computed based on the partition motion pose, P.37, ¶3 – P.41, ¶2, P.43, ¶2 – P.44, ¶3, P.44, ¶4 – P.45, ¶ 2, P.51, ¶7, P.53, ¶3 – P.56, P.66, ¶2 – P.72, ¶2, P.73, ¶2).
Regarding claim 3, Yarach discloses the single transformation operator corresponds to the group motion state (the single forward operator corresponds to the partition motion pose, P.37, ¶3 – P.41, ¶2, P.43, ¶2 – P.44, ¶3, P.44, ¶4 – P.45, ¶ 2, P.51, ¶7, P.53, ¶3 – P.56, P.66, ¶2 – P.72, ¶2, P.73, ¶2).
Regarding claim 4, Yarach discloses for each group of motion states:
determining a part of the k-space data that was acquired while the subject was in one of the motion states belonging to that group (determining a part of the k-space data that was acquired while the subject was in one of the motion poses belonging to that partition, P.53, ¶1 – P.55, ¶1), and
dividing the k-space data into bins according to their group of motion states, wherein the k-space data from each bin is processed using a group-specific non-uniform Fourier Transformation operator during the reconstruction of the motion-corrected magnetic resonance image (dividing the k-space data into bins according to their partition of motion pose, wherein the k-space data from each bin is processed using a partition-specific non-uniform Fourier transformation operator during the reconstruction of the motion-corrected magnetic resonance image, P.37, ¶3 – P.41, ¶2, P.43, ¶2 – P.44, ¶3, P.44, ¶4 – P.45, ¶ 2, P.51, ¶7, P.53, ¶1 – P.56, P.66, ¶2 – P.72, ¶2, P.74, ¶2, P.89, ¶1, P.93, ¶3 – P.94, ¶1).
Regarding claim 5, Yarach discloses calculating a transformation operator that represents the motion of the group motion state, and computing inverse-rotated coil sensitivity maps by operating the inverse of the transformation operator on the coil sensitivity maps (calculating a Fourier transformation operator that represents the motion of the partition motion state, and computing inverse-rotated coil sensitivity maps by operating the inverse of the Fourier transformation operator on the coil sensitivity maps, P.19, ¶2, P.21, ¶2, P.33, ¶2 – P.34, ¶1, P.37, ¶3 – P.41, ¶2, P.44, ¶2 – P.48, ¶1, P.53, ¶1 – P.55, ¶1, P.66, ¶2 – P.72, ¶2, P.74, ¶2, P.89, ¶1, P.93, ¶3 – P.94, ¶1).
Regarding claim 9, Yarach discloses the non-uniform Fourier Transformation uses calculated k-space coordinates, wherein the calculated k-space coordinates are derived by transforming the original k-space coordinates of each subset of k-space data with a rotational operator corresponding to the motion state held by the subject at a time of acquiring the corresponding subset of k-space data, wherein the motion states are optionally corrected by the transformation operator, if the transformation operator is operated onto the magnetic resonance image, whereby the image is pre-rotated and/or pre-shifted (the non-uniform Fourier transformation uses calculated k-space coordinates, wherein the calculated k-space coordinates are derived by transforming the original k-space coordinates of each subset of k-space data with a rotational operator corresponding to the motion state held by the subject at a time of acquiring the corresponding subset of k-space data, P.19, ¶2, P.21, ¶2, P.33, ¶2 – P.34, ¶1, P.37, ¶3 – P.41, ¶2, P.44, ¶2 – P.48, ¶1, P.53, ¶1 – P.55, ¶1, P.66, ¶2 – P.72, ¶2, P.74, ¶2, P.89, ¶1, P.93, ¶3 – P.94, ¶1).
Regarding claim 10, Yarach discloses the motion trajectory is determined by using any one of: a retrospective motion correction method, a motion tracking device, a navigator method, an AI-based motion detection method, or a Pilot Tone method (the motion parameter is determined by using any one of a motion tracking device or a navigator method, P.25, ¶1 – P.28, ¶1, P.45, ¶2, P.50, ¶1, Fig. 3.5, P.53, ¶1 – P.55, ¶1).
Regarding claim 11, Yarach discloses each motion state comprises a plurality of motion parameters, for example translational and rotational motion parameters, and wherein a group of motion states are categorized to be similar to each other if all motion parameters of any one of the group of motion states differ by no more than by a predetermined threshold value from the corresponding motion parameter of any other one of the group of motion states (each motion pose comprises a plurality of motion parameters, for example translation and rotation parameters, and wherein a partition of motion poses are indexed to be similar to each other if all motion parameters of any one of the partition of motion poses differ by no more than by a predetermined threshold value from the corresponding motion parameter of any other one of the partition of motion poses, P.53, ¶1-2).
Regarding claim 12, Yarach discloses the motion trajectory comprises one motion state per subset of k-space data, wherein a subset corresponds to one shot of acquired k-space data (the motion parameter comprises one motion pose per subset k-space data, wherein a subset corresponds to one shot of acquired k-space data, P.53, ¶1-2).
Claim 14 is rejected under 35 U.S.C. 102(a)(1) as being anticipated by Yarach.
Regarding claim 14, Yarach discloses a non-transitory computer readable storage medium comprising a set of computer-readable instructions stored thereon for reconstructing a motion-corrected magnetic resonance image of a subject, the computer-readable instructions that, when executed by at least one processor cause the at least one processor (reconstructing a motion-corrected magnetic resonance image of a subject using software stored and executed on a computer comprising a processor, P.53, ¶1; see also P.74, ¶2 and P.93, ¶3) to:
receive k-space magnetic resonance image data acquired of the subject using a multi-channel coil array during a magnetic resonance imaging acquisition (receive k-space magnetic resonance image data acquired of the subject using a multi-channel coil array during a magnetic resonance imaging acquisition, P.37, ¶3 – P.41, ¶2; P.45, ¶3 -P.48, ¶1, P.52, ¶1-3);
receive coil sensitivity maps of the multi-channel coil array (receive coil sensitivity maps of the multi-channel coil array, P.37, ¶3 – P.41, ¶2; P.45, ¶1 -P.48, ¶1, P.52, ¶1-3, P.53, ¶1, P.53, ¶3 – P.55, ¶1);
receive a motion trajectory comprising a series of motion states that were held by the subject during the acquisition (receive a motion parameter comprising a series of motion poses that were held by the subject, P.53, ¶1-2);
determine similarities across the motion states (compare similarities across the motion poses, P.53, ¶1-2);
form groups of motion states such that each group contains motion states that are similar to each other (form partitions of motion poses such that each partition contains motion poses that are similar to each other, P.53, ¶1-2); and
determine a single group motion state representing each group (determine a single partition motion pose representing each partition, P.53, ¶1-2);
compute, for each group of motion states, a single transformation operator and building a group-specific NuFT forward model, in which a mismatch between the coil sensitivity maps and the magnetic resonance image caused by a motion of the subject during the acquisition is reduced by operating the transformation operator on the coil sensitivity maps and/or on the magnetic resonance image (compute, for each partition of motion poses, a single forward operator and building a partition-specific non-uniform fast Fourier transform forward model, in which a mismatch between the coil sensitivity maps and the magnetic resonance image caused by a motion of the subject during the acquisition is reduced by operating the forward/encoding operator on the coil sensitivity maps, P.2, ¶2, P.29, ¶3 – P.30, ¶1, P.37, ¶3 – P.41, ¶2, P.43, ¶2 – P.44, ¶3, P.44, ¶4 – P.45, ¶ 2, P.51, ¶7, P.53, ¶3 – P.56, P.66, ¶2 – P.72, ¶2, P.73, ¶2); and
reconstruct the motion-corrected magnetic resonance image by minimizing a data consistency error between the received k-space data and the group-specific NuFT forward models, wherein each NuFT forward model comprises an image estimate, the coil sensitivity maps, a non-uniform Fourier Transformation, and a phase factor corresponding to the motion state held by the subject at a time of acquiring the corresponding subset of k-space data (reconstruct the motion-corrected magnetic resonance image by minimizing a data consistency error between the received k-space data and the partition-specific non-uniform fast Fourier transform forward models, wherein each non-uniform fast Fourier transform forward model comprises an image estimate, the coil sensitivity maps, a non-uniform fast Fourier transformation, and a phase factor corresponding to the motion pose held by the subject at a time of acquiring the corresponding subset of k-space data, P.37, ¶3 – P.41, ¶2, P.43, ¶2 – P.44, ¶3, P.44, ¶4 – P.45, ¶ 2, P.51, ¶7, P.53, ¶1 – P.56, P.66, ¶2 – P.72, ¶2).
Claim 15 is rejected under 35 U.S.C. 102(a)(1) as being anticipated by Yarach.
Regarding claim 15, Yarach discloses a magnetic resonance apparatus (MRI scanner and software running on a computer, P.50, ¶2, P.53, ¶1; see also P.73, 2 – P.74, ¶2, P.91, ¶1, P.93, ¶3) comprising:
a MR data acquisition scanner configured to acquire k-space magnetic resonance image data of a subject using a multi-channel coil array during a magnetic resonance imaging acquisition (MRI scanner configured to acquire k-space magnetic resonance image data of a subject using a multi-channel coil array during a magnetic resonance imaging acquisition, P.37, ¶3 – P.41, ¶2; P.45, ¶3 -P.48, ¶1, P.50, ¶2, P.52, ¶1-3); and
a data processing device (software running on a computer, P.53, ¶1; see also P.74, ¶2 and P.93, ¶3) configured to:
receive coil sensitivity maps of the multi-channel coil array (receive coil sensitivity maps of the multi-channel coil array, P.37, ¶3 – P.41, ¶2; P.45, ¶1 -P.48, ¶1, P.52, ¶1-3, P.53, ¶1, P.53, ¶3 – P.55, ¶1);
receive a motion trajectory comprising a series of motion states that were held by the subject during the acquisition (receive a motion parameter comprising a series of motion poses that were held by the subject, P.53, ¶1-2);
determine similarities across the motion states (compare similarities across the motion poses, P.53, ¶1-2);
form groups of motion states such that each group contains motion states that are similar to each other (form partitions of motion poses such that each partition contains motion poses that are similar to each other, P.53, ¶1-2); and
determine a single group motion state representing each group (determine a single partition motion pose representing each partition, P.53, ¶1-2);
compute, for each group of motion states, a single transformation operator and building a group-specific NuFT forward model, in which a mismatch between the coil sensitivity maps and the magnetic resonance image caused by a motion of the subject during the acquisition is reduced by operating the transformation operator on the coil sensitivity maps and/or on the magnetic resonance image (compute, for each partition of motion poses, a single forward operator and building a partition-specific non-uniform fast Fourier transform forward model, in which a mismatch between the coil sensitivity maps and the magnetic resonance image caused by a motion of the subject during the acquisition is reduced by operating the forward/encoding operator on the coil sensitivity maps, P.2, ¶2, P.29, ¶3 – P.30, ¶1, P.37, ¶3 – P.41, ¶2, P.43, ¶2 – P.44, ¶3, P.44, ¶4 – P.45, ¶ 2, P.51, ¶7, P.53, ¶3 – P.56, P.66, ¶2 – P.72, ¶2, P.73, ¶2); and
reconstruct the motion-corrected magnetic resonance image by minimizing a data consistency error between the received k-space data and the group-specific NuFT forward models, wherein each NuFT forward model comprises an image estimate, the coil sensitivity maps, a non-uniform Fourier Transformation, and a phase factor corresponding to the motion state held by the subject at a time of acquiring the corresponding subset of k-space data (reconstruct the motion-corrected magnetic resonance image by minimizing a data consistency error between the received k-space data and the partition-specific non-uniform fast Fourier transform forward models, wherein each non-uniform fast Fourier transform forward model comprises an image estimate, the coil sensitivity maps, a non-uniform fast Fourier transformation, and a phase factor corresponding to the motion pose held by the subject at a time of acquiring the corresponding subset of k-space data, P.37, ¶3 – P.41, ¶2, P.43, ¶2 – P.44, ¶3, P.44, ¶4 – P.45, ¶ 2, P.51, ¶7, P.53, ¶1 – P.56, P.66, ¶2 – P.72, ¶2).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 7-8 are rejected under 35 U.S.C. 103 as being unpatentable over Yarach in further view of Polak et al. (U.S. Pub. No. 2023/0160989), hereinafter “Polak.”
Regarding claim 7, Yarach discloses computing comprises operating the transformation operator onto the magnetic resonance image, whereby the image is pre-rotated and/or pre-shifted (computing comprises operating the affine transform operator onto the magnetic resonance image, whereby the image is pre-rotated and/or pre-shifted, P.19, ¶2, P.21, ¶2, P.24, ¶1, Fig. 2.6, P.33, ¶2 – P.34, ¶1, P.37, ¶3 – P.41, ¶2, P.44, ¶2 – P.48, ¶1, P.53, ¶1 – P.55, ¶1, P.66, ¶2 – P.72, ¶2, P.74, ¶2, P.89, ¶1, P.93, ¶3 – P.94, ¶1).
Additionally, or in the alternative, in the same field of endeavor of motion-corrected MRI, Polak teaches computing comprises operating the transformation operator onto the magnetic resonance image, whereby the image is pre-rotated and/or pre-shifted (an operator comprising image rotations and image translations is operated onto the magnetic resonance image, whereby the image is pre-rotated and/or pre-shifted, [0023], [0026]-[0028]).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have applied Polak’s known technique of applying an operator for image rotation and image translation to the magnetic resonance image to Yarach’s known process of computing a group of motion states and reconstructing a motion-corrected magnetic resonance image to achieve the predictable result that this reduces the computing time. See, e.g., Polak, [0023] and [0028].
Regarding claim 8, Yarach discloses computing comprises operating the transformation operator onto the magnetic resonance image, wherein
x
is the magnetic resonance image, j is a number of the partition of motion states, j(x,y,z) is the transformation operator belong to that partition, R(x,y,z) or
R
→
j is a rotation matrix belonging to the transformation operator j(x,y,z), and T(x,y,z) or
T
→
j is a rotation matrix belonging to the transformation operator j(x,y,z), and
x
→
’ is the is the pre-rotated and/or pre-shifted image for partition j (P.24, ¶1, Fig. 2.6, P.32, ¶2 – P.34, ¶1, P.37, ¶3 – P.41, ¶2, P.44, ¶2 – P.48, ¶1, P.53, ¶1 – P.55, ¶1, P.66, ¶2 – P.72, ¶2, P.74, ¶2, P.89, ¶1, P.93, ¶3 – P.94, ¶1).
However, Yarach does not appear to disclose computing comprises operating the transformation operator onto the magnetic resonance image according to
x
j
=
R
θ
j
T
θ
j
x
wherein
x
is the magnetic resonance image, j is an index of the group of motion states,
θ
j
is the transformation operator belonging to that group,
R
θ
j
is the rotation matrix belonging to the transformation operator
θ
j
,
T
θ
j
is a translation vector belonging to the transformation operator
θ
j
, and
x
j
is the pre-rotated and/or pre-shifted image for group j.
However, in the same field of endeavor of motion-corrected MRI, Polak teaches computing comprises operating the transformation operator onto the magnetic resonance image according to
x
j
=
R
θ
j
T
θ
j
x
wherein
x
is the magnetic resonance image, j is an index of the group of motion states,
θ
j
is the transformation operator belonging to that group,
R
θ
j
is the rotation matrix belonging to the transformation operator
θ
j
,
T
θ
j
is a translation vector belonging to the transformation operator
θ
j
, and
x
j
is the pre-rotated and/or pre-shifted image for group j (an operator comprising image rotations and image translations is operated onto the magnetic resonance image according to the (rotated/shifted image) = VijTiRix, wherein x is the magnetic resonance image, j is an index of the group of motion states, Vij is the transformation operator belonging to that group, Ri is the rotation matrix belonging to the transformation operator Vij, Ti is the translation vector belonging to the transformation operator Vij, and (rotated/shifted image) is the pre-rotated and/or pre-shifted image for group j, [0023], [0026]-[0028]).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have applied Polak’s known technique of applying an operator for image rotation and image translation to the magnetic resonance image to Yarach’s known process of computing a group of motion states and reconstructing a motion-corrected magnetic resonance image to achieve the predictable result that this reduces the computing time. See, e.g., Polak, [0023] and [0028].
Allowable Subject Matter
Claims 6 and 13 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, or 35 U.S.C. 112(d) or 35 U.S.C. 112 (pre-AIA ), 4th paragraph, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding claim 6, Yarach discloses the inverse-rotated coil sensitivity maps are calculated wherein
C
represents the coil sensitivity maps (24), j is a number of the group of motion states,
θ
j
is the transformation operator belonging to that group,
R
θ
j
is a rotation matrix belonging to the transformation operator
θ
j
, and
T
θ
j
is a translation vector belonging to the transformation operator
θ
j
(calculating a Fourier transformation operator that represents the motion of the partition motion state, and computing inverse-rotated coil sensitivity maps by operating the inverse of the Fourier transformation operator on the coil sensitivity maps, wherein C represents the coil sensitivity maps, j is a number of the partition of motion states, j(x,y,z) is the transformation operator belong to that partition, R(x,y,z) or
R
→
j is a rotation matrix belonging to the transformation operator j(x,y,z), and T(x,y,z) or
T
→
j is a rotation matrix belonging to the transformation operator j(x,y,z), P.19, ¶2, P.21, ¶2, P.24, ¶1, Fig. 2.6, P.33, ¶2 – P.34, ¶1, P.37, ¶3 – P.41, ¶2, P.44, ¶2 – P.48, ¶1, P.53, ¶1 – P.55, ¶1, P.66, ¶2 – P.72, ¶2, P.74, ¶2, P.89, ¶1, P.93, ¶3 – P.94, ¶1).
However, Yarach does not appear to disclose the inverse-rotated coil sensitivity maps are calculated according to
C
j
=
R
θ
j
T
θ
j
-
1
C
wherein
C
represents the coil sensitivity maps (24), j is a number of the group of motion states,
θ
j
is the transformation operator belonging to that group,
R
θ
j
is a rotation matrix belonging to the transformation operator
θ
j
,
T
θ
j
is a translation vector belonging to the transformation operator
θ
j
, and
C
j
represents an inverse-rotated coil sensitivity maps for group j.
Regarding claim 13, Yarach does not appear to disclose assessing a number of groups of motion states; and
selecting an image reconstruction process according to the number of groups of motion states or to comprise an image reconstruction process using the SENSE + motion model wherein the groups of motion states are combined to reduce a reconstruction time.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Bammer et al. (“Augmented generalized SENSE reconstruction to correct for rigid body motion” 2007) discloses using counter/inversely rotated and translated images and coil sensitivity maps to correct for rotation and translation in reconstructing a motion-corrected MRI image.
Polak et al. (“Scout accelerated motion estimation and reduction (SAMER)” 2022) discloses reconstructing a motion-corrected MRI image using the motion states to correct images and coil sensitivity maps for rotation and translation.
Polak et al. (“Scout acquisition enables rapid motion estimation (SAME) for retrospective motion mitigation” 2020) discloses reconstructing a motion-corrected MRI image using the motion states to correct images and coil sensitivity maps for rotation and translation.
Polak et al. (“Motion guidance lines for robust data consistency-based retrospective motion correction in 2D and 3D MRI” 2022) discloses reconstructing a motion-corrected MRI image using the motion states to correct images and coil sensitivity maps for rotation and translation.
Haskell et al. (“Targeted motion estimation and reduction (TAMER): Data consistency based motion mitigation for MRI using a reduced model joint optimization” 2018) discloses reconstructing a motion-corrected MRI image using the motion states to correct images and coil sensitivity maps for rotation and translation.
Vaillant et al. (“Retrospective rigid motion correction in k-space for segmented radial MRI” 2014) discloses reconstructing a motion-corrected MRI image using the motion states to correct images and coil sensitivity maps for rotation and translation.
Polak et al. (U.S. Pub. No. 2023/0293039) discloses reconstructing a motion-corrected MRI image using the motion states to correct images and coil sensitivity maps for rotation and translation.
Polak et al. (U.S. Pub. No. 2022/0342016) discloses reconstructing a motion-corrected MRI image using the motion states to correct images and coil sensitivity maps for rotation and translation.
Polak et al. (U.S. Pub. No. 2021/0373105) discloses reconstructing a motion-corrected MRI image using the motion states to correct images and coil sensitivity maps for rotation and translation.
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/Johnathan Maynard/Examiner, Art Unit 3798
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