Prosecution Insights
Last updated: September 17, 2026
Application No. 18/883,709

METHOD FOR GENERATING A SERIES OF MAGNETIC RESONANCE IMAGES WITH CROSS-FRAME ITERATIVE RECONSTRUCTION

Non-Final OA §102§103
Filed
Sep 12, 2024
Priority
Sep 14, 2023 — DE 10 2023 208 954.8
Examiner
CURRAN, GREGORY H
Art Unit
2852
Tech Center
2800 — Semiconductors & Electrical Systems
Assignee
Bruker Biospin GmbH & Co. Kg
OA Round
1 (Non-Final)
90%
Grant Probability
Favorable
1-2
OA Rounds
1m
Est. Remaining
95%
With Interview

Examiner Intelligence

Grants 90% — above average
90%
Career Allowance Rate
769 granted / 853 resolved
+22.2% vs TC avg
Moderate +5% lift
Without
With
+5.2%
Interview Lift
resolved cases with interview
Fast prosecutor
2y 1m
Avg Prosecution
18 currently pending
Career history
865
Total Applications
across all art units

Statute-Specific Performance

§101
4.1%
-35.9% vs TC avg
§103
41.4%
+1.4% vs TC avg
§102
37.3%
-2.7% vs TC avg
§112
11.8%
-28.2% vs TC avg
Black line = Tech Center average estimate • Based on career data from 853 resolved cases

Office Action

§102 §103
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 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. Claim(s) 1, 3-5, 7, 8, 11 and 12 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Lai et al (US 2012/0262167 A1), hereinafter referred to as Lai. With reference to claim 1, Lai teaches A method for generating a series of n-dimensional magnetic resonance images from an MR bin series obtained by means of an MRI measurement, wherein the MR bin series comprises a plurality of bin frames (f1, f2, f3) with determined MR data, wherein at least one bin frame is undersampled, i.e., has missing MR data in addition to the determined MR data, wherein the bin frames differ by the value of x prespecified parameters (x = 1 or greater) under which the MR data were determined (Fig. 6, ¶0044-¶0046) , comprising: a) calculating an n-dimensional preliminary reconstruction kernel from preliminary reference data of a reference frame (¶0040); b) determining preliminary reconstruction frames by reconstruction of the MR data missing in the MR bin series by means of the preliminary reconstruction kernel (¶0040); c) calculating an n+x-dimensional reconstruction kernel from the MR data of the preliminary reconstruction frames, wherein MR data of different preliminary reconstruction frames are used for the calculation of the n+x-dimensional reconstruction kernels (Fig. 5, ¶0040); d) determining further reconstruction frames by reconstructing the data missing in the bin frames by means of the n+x-dimensional reconstruction kernels (¶0040, ¶0043); e) generating n-dimensional magnetic resonance images from the reconstruction frames determined in step (d) (¶0046). With reference to claim 3, Lai further teaches that the at least one prespecified parameter is the direction and/or the amplitude of the diffusion gradients used in the MRI measurement (¶0043). With reference to claim 4, Lai further teaches the at least one prespecified parameter comprises the time coordinate within a cycle (Fig. 4) With reference to claim 5, Lai further teaches the at least one prespecified parameter is the echo time used in the MRI measurement (¶0030) With reference to claim 7, Lai further teaches characterized in that only bin frames, the values of which for the prespecified parameter lie within a prespecified interval, are used for the reconstruction of the missing MR data (¶0022). With reference to claim 8, Lai further teaches that the MR bin series has bin frames with different encoding (¶0043). With reference to claim 11, Lai further teaches steps c) and d) are repeated, wherein the calculation of the n+x-dimensional reconstruction kernel in step c) is carried out from the MR data of the previously determined further reconstruction frames (¶0040). With reference to claim 12, Lai further teaches that the reconstruction in step (d) takes place in the k-space (¶0047) 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. Claim(s) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lai as applied to claim 1 above, and further in view of Grodzki et al. (US 2015/0253408 A1), hereinafter referred to as Grodzki. With reference to claim 2, Lai teaches all that is required as explained above, however is silent with using EPI. Grodzki teaches an echo-planar imaging measurement sequence is used in the MRI measurement (¶0013). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use the teaching of Grodzki with the method of Lai so as to improve image quality (Grodzki ¶0013). Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lai as applied to claim 8 above, and further in view of Ding et al. (US 2013/0279781 A1), hereinafter referred to as Ding. With reference to claim 9, Lai teaches all that is required as explained above, however is silent with regards to the n-dimensional preliminary reconstruction kernel is a t-GRAPPA kernel. Ding teaches the n-dimensional preliminary reconstruction kernel is a t-GRAPPA kernel (¶0006). It would have been obvious to use the teaching of Ding with the method of Lai so as to improve SNR (Ding, ¶0006). Claim(s) 6 and 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lai as applied to claims 1 and 8 above, and further in view of Zhang et al. (US 2024/0036141 A1), hereinafter referred to as Zhang. With reference to claim 6, Lai teaches all that is required as explained above and further teaches the encoding of the MR data in the MR bin frames is periodic or in that the encoding of the MR data in the MR bin frames is irregular in at least one dimension (Fig. 5, ¶0043) However, Lai is silent with regards to using GRAPPA, SPIRiT or CAIPIRINHA. Zhang teaches wherein preferably a GRAPPA or CAIPIRINHA reconstruction method is applied or a SPIRiT reconstruction method is preferably applied (¶0053). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use the teaching of Zhang with the method of Lai so as to effectively realize the reconstruction of an undersampled image frame (Zhang ¶0053). With reference to claim 10, Lai teaches all that is required as explained above and further teaches the encoding of the MR data in the MR bin frames is periodic or in that the encoding of the MR data in the MR bin frames is irregular in at least one dimension (Fig. 5, ¶0043) However, Lai is silent with regards to using GRAPPA, SPIRiT or CAIPIRINHA. Zhang teaches wherein preferably a GRAPPA or CAIPIRINHA reconstruction method is applied or a SPIRiT reconstruction method is preferably applied (¶0053). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use the teaching of Zhang with the method of Lai so as to effectively realize the reconstruction of an undersampled image frame (Zhang ¶0053). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to GREGORY H CURRAN whose telephone number is (571)270-7505. The examiner can normally be reached Monday-Friday, 8am-5pm, EST. 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, Walter Lindsay can be reached at (571) 272-1674. 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. /GREGORY H CURRAN/Primary Examiner, Art Unit 2852
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Prosecution Timeline

Sep 12, 2024
Application Filed
Aug 21, 2026
Non-Final Rejection mailed — §102, §103 (current)

Precedent Cases

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MAGNETIC RESONANCE IMAGING APPARATUS AND METHOD OF CONTROLLING SUPERCONDUCTING MAGNET
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EPI Data Correction Method and Device and MRI System
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SYSTEMS AND METHODS FOR REMOVING ELECTROMAGNETIC INTERFERENCE FROM MAGNETIC RESONANCE IMAGES
2y 9m to grant Granted Jul 28, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
90%
Grant Probability
95%
With Interview (+5.2%)
2y 1m (~1m remaining)
Median Time to Grant
Low
PTA Risk
Based on 853 resolved cases by this examiner. Grant probability derived from career allowance rate.

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