Prosecution Insights
Last updated: April 19, 2026
Application No. 18/730,080

REAL-TIME MONITORED COMPUTED TOMOGRAPHY (CT) RECONSTRUCTION FOR REDUCING RADIATION DOSE

Non-Final OA §103
Filed
Jul 18, 2024
Examiner
FOX, DANIELLE A
Art Unit
2884
Tech Center
2800 — Semiconductors & Electrical Systems
Assignee
Smart Engines Service LLC
OA Round
1 (Non-Final)
83%
Grant Probability
Favorable
1-2
OA Rounds
2y 8m
To Grant
96%
With Interview

Examiner Intelligence

Grants 83% — above average
83%
Career Allow Rate
590 granted / 711 resolved
+15.0% vs TC avg
Moderate +13% lift
Without
With
+13.3%
Interview Lift
resolved cases with interview
Typical timeline
2y 8m
Avg Prosecution
29 currently pending
Career history
740
Total Applications
across all art units

Statute-Specific Performance

§101
2.9%
-37.1% vs TC avg
§103
39.6%
-0.4% vs TC avg
§102
41.4%
+1.4% vs TC avg
§112
10.4%
-29.6% vs TC avg
Black line = Tech Center average estimate • Based on career data from 711 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 . 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. Claim(s) 1, 4-12, and 16-17 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 9466133 (Sowards-Emmerd) and US 7751607 (Reeves). Regarding claim 1, Sowards-Emmerd disclose a method comprising using at least one hardware processor (column 8, lines 20-21) to, during helical computed tomography (CT) scanning (column 8, lines 37-40) of a target object, after acquiring a set of projections from a sector in a full mode which subjects the target object to a first radiation dose (column 8, lines 3-6): identify a slice of the target object that is influenced by the sector (column 8, lines 10-14); reconstruct a CT image of the identified slice using projections that have been previously acquired for the slice (column 8, lines 10-14); determine whether or not a stopping rule is satisfied based on the reconstructed CT image (column 8, lines 15-19); and, when determining that the stopping rule is satisfied, switch from the full mode to a reduced mode which subjects the target object to a second radiation dose (column 8, lines 7-10), wherein the second radiation dose is less than the first radiation dose (column 8, lines 37-41), and acquire a set of projections from at least one subsequent sector in the reduced mode (column 8, lines 20-23). Sowards-Emmerd fails to teach acquisition during helical CT. Reeves teaches acquisition during helical CT (column 11, lines 63-66). It would have been obvious to one of ordinary skill in the art at the time the invention was filed to apply the known method of Sowards-Emmerd to a known method such as helical CT to yield predictable results. See MPEP 2143. Regarding claim 4, Sowards-Emmerd in view of Reeves disclose the method of Claim 1, wherein identifying a slice of the target object that is influenced by the sector comprises identifying a first slice, along a trajectory of the helical CT scanning, in a range of slices that are influenced by the sector based on a geometry of the helical CT scanning (column 15, lines 4-18). Regarding claim 5, Sowards-Emmerd in view of Reeves disclose the method of Claim 1, wherein determining whether or not a stopping rule is satisfied based on the reconstructed CT image comprises: applying a classification model to the reconstructed CT image to produce a membership estimation representing a probability that the reconstructed CT image is a member of one of a plurality of classes; and determining whether or not the stopping rule is satisfied based on the membership estimation (column 22, lines 21-26). Regarding claim 6, Sowards-Emmerd in view of Reeves disclose the method of Claim 5, wherein determining whether or not the stopping rule is satisfied based on the membership estimation comprises: when the membership estimation exceeds a prediction threshold at least once within an initial subset of sectors consisting of a first threshold number of sectors, determining that the stopping rule is satisfied when the first threshold number of sectors have been acquired; and, when the membership estimation never exceeds the prediction threshold within the initial subset of sectors, determining that the stopping rule is satisfied when a second threshold number of sectors have been acquired following an initial sector for which the membership estimation of the reconstructed CT image exceeds the prediction threshold (column 19, lines 11-25). Regarding claim 7, Sowards-Emmerd in view of Reeves disclose the method of Claim 5, wherein the plurality of classes comprises a first class representing an absence of an anomaly, and a second class representing a presence of an anomaly (column 6, lines 1-5). Regarding claim 8, Sowards-Emmerd in view of Reeves disclose the method of Claim 7, wherein the anomaly is COVID-19 (column 6, lines 1-5). Regarding claim 9, Sowards-Emmerd in view of Reeves disclose the method of Claim 8, wherein the target object comprises at least one lung of a subject (abstract). Regarding claim 10, Sowards-Emmerd in view of Reeves disclose the method of Claim 5, wherein the classification model comprises a neural network (column 4, lines 20-21). Regarding claim 11, Sowards-Emmerd in view of Reeves disclose the method of Claim 10, wherein the neural network is a deep-learning neural network (column 4, lines 20-21). Regarding claim 12, Sowards-Emmerd in view of Reeves disclose the method of Claim 10, wherein the neural network is a Feature Pyramid Network (FPN) (column 4, lines 20-21). Regarding claim 16, Sowards-Emmerd disclose a system comprising: at least one hardware processor configured to control a scanning mode of a computed tomography (CT) scanner (column 8, lines 20-21, 37-40); and software (column 9, lines 26-28) that is configured to, when executed by the at least one hardware processor, during helical CT scanning of a target object (column 8, lines 20-21, lines 37-40), after acquiring a set of projections from a sector in a full mode which subjects the target object to a first radiation dose identify a slice of the target object that is influenced by the sector, reconstruct a CT image of the identified slice using projections that have been previously acquired for the slice (column 8, lines 10-14), determine whether or not a stopping rule is satisfied based on the reconstructed CT image (column 10, lines 15-19), and, when determining that the stopping rule is satisfied, switch from the full mode to a reduced mode which subjects the target object to a second radiation dose (column 8, lines 7-10), wherein the second radiation dose is less than the first radiation dose, and acquire a set of projections from at least one subsequent sector in the reduced mode (column 8, lines 20-23). Regarding claim 17, Sowards-Emmerd disclose a non-transitory computer-readable medium having instructions stored therein, wherein the instructions, when executed by a processor, cause the processor to, during helical computed tomography (CT) scanning of a target object, after acquiring a set of projections from a sector in a full mode which subjects the target object to a first radiation dose: identify a slice of the target object that is influenced by the sector (column 10, lines 6-8); reconstruct a CT image of the identified slice using projections that have been previously acquired for the slice (column 8, lines 10-14); determine whether or not a stopping rule is satisfied based on the reconstructed CT image (column 10, lines 15-19); and, when determining that the stopping rule is satisfied, switch from the full mode to a reduced mode which subjects the target object to a second radiation dose (column 8, lines 7-10), wherein the second radiation dose is less than the first radiation dose (column 8, lines 37-41), and acquire a set of projections from at least one subsequent sector in the reduced mode (column 8, lines 20-23). Allowable Subject Matter Claims 2, 3, and 13-15 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. The following is a statement of reasons for the indication of allowable subject matter: Regarding claim 2, Sowards-Emmerd disclose the method of Claim 1, but fails to teach the details of further comprising using the at least one hardware processor to, when determining that the stopping rule is satisfied, determine a next sector that corresponds to a next slice of the target object, wherein acquiring a set of projections from at least one subsequent sector in the reduced mode comprises acquiring a set of projections from each subsequent sector in the reduced mode until the determined next sector, and switching from the reduced mode to the full mode prior to acquiring a set of projections from the determined next sector. Claim 3 depends on claim 2. Regarding claim 13, Sowards-Emmerd disclose the method of Claim 1, but fails to teach the details of wherein the full mode acquires a first number of projections, and the reduced mode acquires a second number of projections that is less than the first number. Claim 14 depends on claim 13. Regarding claim 15, Sowards-Emmerd disclose the method of Claim 1, but fails to teach the details of wherein the full mode acquires each projection using a first exposure time, and the reduced mode acquires each projection using a second exposure time that is shorter than the first exposure time. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to DANI FOX whose telephone number is (571)272-3513. The examiner can normally be reached M-F: 9-5. 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, David Makiya can be reached at 571-272-2273. 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. /DANI FOX/Primary Examiner, Art Unit 2884
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Prosecution Timeline

Jul 18, 2024
Application Filed
Feb 06, 2026
Non-Final Rejection — §103 (current)

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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
83%
Grant Probability
96%
With Interview (+13.3%)
2y 8m
Median Time to Grant
Low
PTA Risk
Based on 711 resolved cases by this examiner. Grant probability derived from career allow rate.

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