Prosecution Insights
Last updated: April 19, 2026
Application No. 17/759,401

METHODS AND APPARATUS FOR DEEP LEARNING BASED IMAGE ATTENUATION CORRECTION

Non-Final OA §103
Filed
Jul 25, 2022
Examiner
ISLAM, MEHRAZUL NMN
Art Unit
2662
Tech Center
2600 — Communications
Assignee
Siemens Healthcare
OA Round
5 (Non-Final)
58%
Grant Probability
Moderate
5-6
OA Rounds
3y 4m
To Grant
86%
With Interview

Examiner Intelligence

Grants 58% of resolved cases
58%
Career Allow Rate
29 granted / 50 resolved
-4.0% vs TC avg
Strong +28% interview lift
Without
With
+28.3%
Interview Lift
resolved cases with interview
Typical timeline
3y 4m
Avg Prosecution
46 currently pending
Career history
96
Total Applications
across all art units

Statute-Specific Performance

§101
9.2%
-30.8% vs TC avg
§103
68.6%
+28.6% vs TC avg
§102
4.1%
-35.9% vs TC avg
§112
15.2%
-24.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 50 resolved cases

Office Action

§103
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 . The Final Office Action presented on 10/24/2025 is withdrawn and this Non-Final Office Action is current. Status of Claims Claims 1-20 are pending. 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, 4-9, 12-15, and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Hu et al. (US 2020/0126231 A1), in view of Watson (US 2014/0228673 A1), and in further view of Bachschmidt et al. (US 2016/0259024 A1). Regarding claim 1, Hu teaches, A computer-implemented method comprising: (Hu, ¶0051: “To implement various modules, units, and their functionalities described in the present disclosure, computer hardware platforms may be used”) receiving first positron emission tomography (PET) measurement data (Hu, ¶0004: “obtain at least one first PET image”) representing radiation emitted from crystals of an image scanning system (Hu, ¶0035: “The detector may detect radiation photons (e.g., γ photons) emitted from a subject being examined. The electronics module may collect and/or process electrical signals (e.g., scintillation pulses) generated by the detector”) (Hu, ¶0004: “at least one first MR image of the subject acquired by an MR scanner”) and second PET measurement data (Hu, ¶0075: “a second PET image… may be acquired) of a subject from the image scanning system; (Hu, ¶0035: “The PET scanner may scan a subject or a portion thereof that is located within its detection region and generate projection data”) the second PET measurement data representing gamma rays emitted from the subject while the subject is located in the image scanning system; (Hu, ¶0035: “The detector may detect radiation photons (e.g., γ photons) emitted from a subject being examined”) (Hu, ¶0080: “the neural network model may be trained using the plurality of groups of PET images and MR images, and the multiple attenuation correction data”) and storing the trained neural network in a memory device. (Hu, ¶0082: “target neural network model may be transmitted to the storage device 130”). However, Hu does not explicitly teach, (a first scan) while no subject is located in the image scanning system, generating a first attenuation map based on a difference between the first PET measurement data and the second PET measurement data, and output an attenuation map based on input MR measurement data; and not on input PET measurement data. In an analogous field of endeavor, Watson teaches, (a first scan) while no subject is located in the image scanning system (Watson, ¶0077: “the target is moved to avoid intersection with the positron beam”) and generating a first attenuation map based on a difference (Watson, ¶0081: “the attenuation correction factors are determined from the differences in gamma radiation detected in acts 64 and 68”; also see Fig. 4) between the first PET measurement data (blank scan) (Watson, ¶0078: “In act 68, radiation is detected while… the target moved to avoid intersection”) and the second PET measurement data (target scan). (Watson, ¶0075: “In act 64, the rays are detected… from the interaction of positron beams with targets”). Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Hu using the teachings of Watson to introduce computing differences in radiation between a subject scan and a blank scan. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of compensating for the attenuation of the radiation. Therefore, it would have been obvious to combine the analogous arts Hu and Watson to obtain the above-described limitations of claim 1. However, the combination of Hu and Watson does not explicitly teach, output an attenuation map based on input MR measurement data; and not on input PET measurement data. In an analogous field of endeavor, Bachschmidt teaches, output an attenuation map based on input MR measurement data; and not on input PET measurement data. (Bachschmidt, ¶0010: “The attenuation map for the attenuation correction of the emission tomography scan data is typically generated on the basis of magnetic resonance scan data.”) Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Hu in view of Watson using the teachings of Bachschmidt to introduce an output attenuation map from input MR data. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of improving the quality of a medical scan image by reducing artifacts. Therefore, it would have been obvious to combine the analogous arts Hu, Watson and Bachschmidt to obtain the invention in claim 1. Regarding claim 4, Hu in view of Watson, and in further view of Bachschmidt teaches, The computer-implemented method of claim 2, wherein the second attenuation map is generated based on prior images computed using MR measurement data. (Hu, ¶0008: “determine the second attenuation correction data corresponding to the sample based on the at least one of the second MR image or the second PET image for each training data of a sample of the multiple groups of training data”). Regarding claim 5, Hu in view of Watson, and in further view of Bachschmidt teaches, The computer-implemented method of claim 1, wherein the first attenuation map is generated based on synthetic transmission images. (Watson, ¶0017: “supplemental transmission information is used to improve attenuation correction for PET”). Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Hu in view of Watson, in further view of Bachschmidt using the additional teachings of Watson to introduce transmission images. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of reducing medical scan image artifacts using attenuation correction. Therefore, it would have been obvious to combine the analogous arts Hu, Watson and Bachschmidt to obtain the invention in claim 5. Regarding claim 6, Hu in view of Watson, and in further view of Bachschmidt teaches, The computer-implemented method of claim 5, further comprising generating the synthetic transmission images based on the PET measurement data. (Hu, ¶0035: “PET scanner may scan a subject or a portion thereof that is located within its detection region and generate projection data relating to the subject or the portion thereof”). Regarding claim 7, Hu in view of Watson, and in further view of Bachschmidt teaches, The computer-implemented method of claim 1, comprising scaling the first attenuation map (Hu, ¶0076: “using the scaling technique, the reference attenuation correction image associated with the PET image of the sample may be determined by multiplying a ratio and pixel values of the CT image”) based on a corresponding energy window. (Watson, ¶0031: “The Hounsfield units of the CT image are then appropriately scaled to linear attenuation coefficients at 511 keV”). Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Hu in view of Watson, in further view of Bachschmidt using the additional teachings of Watson to introduce energy-based scaling. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of scaling the attenuation map to match the radiation energy window. Therefore, it would have been obvious to combine the analogous arts Hu, Watson and Bachschmidt to obtain the invention in claim 7. Regarding claim 8, Hu in view of Watson, and in further view of Bachschmidt teaches, The computer-implemented method of claim 1, wherein the neural network is a deep learning neural network. (Hu, ¶0065: “neural network models may include… a deep belief nets (DBN) neural network model”). Regarding claim 9, it recites a non-transitory computer readable medium including instructions corresponding to the steps of the computer-implemented method recited in claim 1. Therefore, the recited instructions of the non-transitory computer readable medium of claim 9 are mapped to the proposed combination in the same manner as the corresponding steps of the computer-implemented method claim 1. Additionally, the rationale and motivation to combine Hu, Watson and Bachschmidt presented in rejection of claim 1, apply to this claim. Additionally, Hu teaches, A non-transitory computer readable medium storing instructions that, (Hu, ¶0014: “a non-transitory computer-readable medium storing at least one set of instructions”) when executed by at least one processor, cause the at least one processor to perform operations comprising: (Hu, ¶0014: “When executed by at least one processor, the at least one set of instructions may direct the at least one processor to perform a method”). Regarding claim 12, Hu in view of Watson, and in further view of Bachschmidt teaches, The non-transitory computer readable medium of claim 9 storing instructions that, when executed by at least one processor, further cause the at least one processor to perform operations comprising generating synthetic transmission images based on the first PET measurement data, (Hu, ¶0035: “PET scanner may scan a subject or a portion thereof that is located within its detection region and generate projection data relating to the subject or the portion thereof”) wherein the first attenuation map is generated based on the synthetic transmission images. (Watson, ¶0017: “supplemental transmission information is used to improve attenuation correction for PET”). Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Hu in view of Watson, in further view of Bachschmidt using the additional teachings of Watson to introduce transmission images. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of reducing medical scan image artifacts using attenuation correction. Therefore, it would have been obvious to combine the analogous arts Hu, Watson and Bachschmidt to obtain the invention in claim 12. Regarding claim 13, it recites a non-transitory computer readable medium including instructions corresponding to the steps of the computer-implemented method recited in claim 4. Therefore, the recited instructions of the non-transitory computer readable medium of claim 13 are mapped to the proposed combination in the same manner as the corresponding steps of the computer-implemented method claim 4. Additionally, the rationale and motivation to combine Hu, Watson and Bachschmidt presented in rejection of claim 1, apply to this claim. Regarding claim 14, it recites a non-transitory computer readable medium including instructions corresponding to the steps of the computer-implemented method recited in claim 7. Therefore, the recited instructions of the non-transitory computer readable medium of claim 14 are mapped to the proposed combination in the same manner as the corresponding steps of the computer-implemented method claim 7. Additionally, the rationale and motivation to combine Hu, Watson and Bachschmidt presented in rejection of claim 7, apply to this claim. Regarding claim 15, it recites a system with elements corresponding to the steps of the computer-implemented method recited in claim 1. Therefore, the recited elements of system claim 15 are mapped to the proposed combination in the same manner as the corresponding steps in method claim 1. Additionally, the rationale and motivation to combine Hu, Watson and Bachschmidt presented in rejection of claim 1, apply to this claim. Hu additionally teaches, A system comprising: a database; and at least one processor communicatively coupled to the database (Hu, ¶0031: “The system may include at least one storage device storing executable instructions, and at least one processor in communication with the at least one storage device.”) Regarding claim 18, it recites a system with elements corresponding to the instructions of the computer readable medium recited in claim 12. Therefore, the recited elements of system claim 18 are mapped to the proposed combination in the same manner as the corresponding instructions in computer readable medium claim 12. Additionally, the rationale and motivation to combine Hu, Watson, and Bachschmidt presented in rejection of claim 12, apply to this claim. Regarding claim 19, it recites a system with elements corresponding to the steps of the computer-implemented method recited in claim 4. Therefore, the recited elements of system claim 19 are mapped to the proposed combination in the same manner as the corresponding steps in method claim 4. Additionally, the rationale and motivation to combine Hu, Watson, and Bachschmidt presented in rejection of claim 1, apply to this claim. Regarding claim 20, it recites a system with elements corresponding to the steps of the computer-implemented method recited in claim 7. Therefore, the recited elements of system claim 20 are mapped to the proposed combination in the same manner as the corresponding steps in method claim 7. Additionally, the rationale and motivation to combine Hu, Watson, and Bachschmidt presented in rejection of claim 7, apply to this claim. Claims 2, 3, 10, 11, 16, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Hu et al. (US 2020/0126231 A1), in view of Watson (US 2014/0228673 A1), in further view of Bachschmidt et al. (US 2016/0259024 A1) and still in further view of Zhu et al. (US 2018/0025512 A1) Regarding claim 2, Hu in view of Watson, and in further view of Bachschmidt teaches, The computer-implemented method of claim 1 further comprising: receiving second MR measurement data (Hu, ¶0075: “a second MR image) may be acquired by… an MR scanner”) from the image scanning system; (Hu, ¶0036: “MR scanner may scan a subject or a portion thereof that is located within its detection region”) and applying the trained neural network to the second MR measurement data to (Hu, ¶0015: “The target neural network model may provide a mapping relationship between PET images, MR images, and corresponding attenuation correction data”). However, the combination of Hu, Watson and Bachschmidt does not explicitly teach, determine a second attenuation map. In an analogous field of endeavor, Zhu teaches, determine a second attenuation map. (Zhu, ¶0075: “generating a second attenuation map”). Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Hu in view of Watson, in further view of Bachschmidt using the teachings of Zhu to introduce a second attenuation map. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of updating the attenuation map to further improve medical image quality. Therefore, it would have been obvious to combine the analogous arts Hu, Watson, Bachschmidt and Zhu to obtain the invention in claim 2. Regarding claim 3, Hu in view of Watson, in further view of Bachschmidt, and still in further view of Zhu teaches, The computer-implemented method of claim 2 further comprising receiving third PET measurement data from the image scanning system; (Hu, ¶0062: “The acquisition module 402 may obtain the at least one PET image of the subject from the PET scanner”) and generating an image based on the third PET measurement data and the second attenuation map. (Zhu, ¶0075: “updating the first PET image based on the second attenuation map and generating a second PET image”). The proposed combination as well as the motivation for combining Hu, Watson, Bachschmidt and Zhu references presented in the rejection of claim 2, apply to claim 3 and are incorporated herein by reference. Thus, the method recited in claim 3 is met by Hu, Watson, Bachschmidt and Zhu. Regarding claim 10, it recites a non-transitory computer readable medium including instructions corresponding to the steps of the computer-implemented method recited in claim 2. Therefore, the recited instructions of the non-transitory computer readable medium of claim 10 are mapped to the proposed combination in the same manner as the corresponding steps of the computer-implemented method claim 2. Additionally, the rationale and motivation to combine Hu, Watson, Bachschmidt and Zhu presented in rejection of claim 2, apply to this claim. Regarding claim 11, Hu in view of Watson, in further view of Bachschmidt, and still in further view of Zhu teaches, The non-transitory computer readable medium of claim 10, storing instructions that, when executed by at least one processor, further cause the at least one processor to perform operations comprising: receiving third PET measurement data from the image scanning system; (Hu, ¶0062: “The acquisition module 402 may obtain the at least one PET image of the subject from the PET scanner”) and generating an image based on the second attenuation map. (Zhu, ¶0075: “updating the first PET image based on the second attenuation map and generating a second PET image”). The proposed combination as well as the motivation for combining Hu, Watson, Bachschmidt and Zhu references presented in the rejection of claim 2, apply to claim 11 and are incorporated herein by reference. Thus, the method recited in claim 11 is met by Hu, Watson, Bachschmidt and Zhu. Regarding claim 16, it recites a system with elements corresponding to the steps of the computer-implemented method recited in claim 2. Therefore, the recited elements of system claim 16 are mapped to the proposed combination in the same manner as the corresponding steps in method claim 2. Additionally, the rationale and motivation to combine Hu, Watson, Bachschmidt and Zhu presented in rejection of claim 2, apply to this claim. Regarding claim 17, Hu in view of Watson, in further view of Bachschmidt, and still in further view of Zhu teaches, The system of claim 16, wherein the at least one processor is configured to; receive third PET measurement data from the image scanning system; (Hu, ¶0062: “The acquisition module 402 may obtain the at least one PET image of the subject from the PET scanner”) and generate an image based on the second attenuation map. (Zhu, ¶0075: “updating the first PET image based on the second attenuation map and generating a second PET image”). The proposed combination as well as the motivation for combining Hu, Watson, Bachschmidt and Zhu references presented in the rejection of claim 2, apply to claim 17 and are incorporated herein by reference. Thus, the method recited in claim 17 is met by Hu, Watson, Bachschmidt and Zhu. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to MEHRAZUL ISLAM whose telephone number is (571)270-0489. The examiner can normally be reached Monday-Friday: 8am-5pm. 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, Saini Amandeep can be reached on (571) 272-3382. 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. /MEHRAZUL ISLAM/Examiner, Art Unit 2662 /AMANDEEP SAINI/Supervisory Patent Examiner, Art Unit 2662
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Prosecution Timeline

Jul 25, 2022
Application Filed
Nov 04, 2024
Non-Final Rejection — §103
Feb 03, 2025
Response Filed
Mar 06, 2025
Final Rejection — §103
May 01, 2025
Request for Continued Examination
May 08, 2025
Response after Non-Final Action
May 15, 2025
Non-Final Rejection — §103
Aug 12, 2025
Response Filed
Oct 20, 2025
Final Rejection — §103
Dec 15, 2025
Response after Non-Final Action
Dec 15, 2025
Notice of Allowance
Jan 06, 2026
Response after Non-Final Action
Feb 19, 2026
Non-Final Rejection — §103 (current)

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Prosecution Projections

5-6
Expected OA Rounds
58%
Grant Probability
86%
With Interview (+28.3%)
3y 4m
Median Time to Grant
High
PTA Risk
Based on 50 resolved cases by this examiner. Grant probability derived from career allow rate.

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