Prosecution Insights
Last updated: April 19, 2026
Application No. 18/329,434

Systems and Methods for Using Multi-Dimensional X-Ray Imaging in Meat Production and Processing Applications

Non-Final OA §102§103
Filed
Jun 05, 2023
Examiner
FOX, DANIELLE A
Art Unit
2884
Tech Center
2800 — Semiconductors & Electrical Systems
Assignee
Rapiscan Holdings Inc.
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

§102 §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 § 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) 1-6, 8, 9, 11, 15-18, 20, and 24 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US 2021/0041378 (Morton). Regarding claim 1, Morton disclose an imaging system configured to evaluate meat, comprising: an X-ray scanning system configured to generate X-ray scan data of meat (Fig. 1A and 1B); a hyperspectral imaging system configured to generate hyperspectral imaging data (Fig. 16A, [0218], 1606); a computing device in data communication with the X-ray scanning system and the hyperspectral imaging system [0112], wherein the computing device includes a processor and memory storing a plurality of programmatic instructions which when executed by the processor, configures the processor to: acquire the X-ray scan data and hyperspectral imaging data [0171]; automatically determine a quality of the meat by analyzing the acquired X-ray scan data in combination with the hyperspectral imaging data [0227]; categorize the meat, based on the determined quality, into one of acceptable quality and unacceptable quality categories ([0227], via product quality check; [0228], carcass valuation algorithms 1620 identify meet as contaminated and mark such projects for de-contamination or further analysis); and generate data indicative of the quality of the meat ([0227]-[0228]). Regarding claim 2, Morton disclose the system of claim 1, wherein the X-ray scanning system comprises a two-dimensional projection X-ray imaging system having at least one of a single-view or a dual-view configuration, in combination with multi-energy X-ray (MEXA) sensors ([0178]-[0179], [0236]). Regarding claim 3, Morton disclose the system of claim 2, wherein the X-ray scanning system comprises an inclined conveyor such that an entrance end of the conveyor is at a lower height position than an exit end of the conveyor (Fig. 1A, 9A-9B). Regarding claim 4, Morton disclose the system of claim 2, wherein the X-ray scanning system uses a declining conveyor such that an entrance end of the conveyor is at a higher height position than an exit end of the conveyor (Fig. 1A, 9A-9B, [0028], [0180], system 900 deployed in 901 to scan meat hanging from hooks of conveyor 910). Regarding claim 5, Morton disclose the system of claim 1, wherein the hyperspectral scan data comprises data in a visible light wavelength range and a shortwave infrared wavelength range [0071]. Regarding claim 6, Morton disclose the system of claim 1, wherein the meat comprises offal and organs [0114]. Regarding claim 8, Morton disclose the system of claim 1, wherein the processor is further configured to: generate at least one graphical user interface to display at least one image corresponding to the X-ray scan data, and determine the quality based on data indicative of a thickness and/or a density of the meat (Fig. 16A, [0221], [0233], [0236]). Regarding claim 9, Morton disclose the system of claim 1, further comprising a conveyor that translates the meat through the system at a speed ranging from 0.1 m/s to 1.0 m/s ([0046], Fig. 9A-9B, [0180]). Regarding claim 11, Morton disclose the system of claim 1, wherein the X-ray scanning system comprises a first X-ray source of 120 to 160 keV with 0.2 to 1.25mA beam current and a second X-ray source of 120 to 160 keV with 0.2 to 1.25mA beam current, wherein the first X-ray source is configured in up-shooter configuration and the second X-ray source is configured in a side-shooter configuration ([0022], [0121]). Regarding claim 15, Morton disclose the system of claim 1, wherein the hyperspectral imaging system comprises a first camera sensor configured for visible imaging in 200 to 1200 wavelength bands and a second camera sensor configured for shortwave infrared imaging in 400 to 700 wavelength bands [0071]. Regarding claim 16, Morton disclose the system of claim 15, wherein the first camera sensor is configured to operate in a range of 400nm to 900nm and have a spectral resolution of at least 20nm with a pixel size not exceeding 2.0mm across a width of a conveyor [0145]. Regarding claim 17, Morton disclose the system of claim 16, wherein the second camera sensor operates is configured to operate in a range of 900nm to 1800nm and have a spectral resolution of at least 20nm with a pixel size not exceeding 2.0mm across the width of the conveyor [0145]. Regarding claim 18, Morton disclose the system of claim 1, wherein the hyperspectral imaging system is configured to have an acquisition rate of 30 to 150 Hz [0145]. Regarding claim 20, Morton disclose the system of claim 1, wherein the processor is further configured to determine a type of meat based on the acquired X-ray scan data and hyperspectral imaging data ([0227]-[0228]). Regarding claim 24, Morton disclose the system of claim 1, wherein the data indicative of a quality of the meat includes at least one of a lean meat yield, a ratio of intra-muscular fat to tissue, an amount of inter-muscular fat, an absolute size of individual organs, a relative size of individual organs, a muscle volume, a number of ribs, a presence or an absence of diseases, a presence or an absence of cysts, a presence or an absence of tumors, a presence or an absence of pleurisy, or a presence or an absence of foreign objects [0032]. 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) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Morton as applied to claim 1 above. Regarding claim 10, Morton disclose the system of claim 1, wherein the multi-sensor imaging system has an inspection tunnel having a length ranging from 1100mm to 5000mm, a width ranging from 500mm to 1000mm, and a height ranging from 300mm to 1000mm (Fig. 3, [0137]), but fails to explicitly. Morton fails to explicitly teach an inspection tunnel having a length ranging from 1100mm to 5000mm. Morton teaches a length having a range from 600mm to 1100mm. It would have been obvious to one of ordinary skill in the art at the time the invention was filed to modify the inspection tunnel of Morton to have a length ranging from 1100mm to 5000mm, for when the general conditions of a claim are disclosed by the prior art it is not inventive to discover an optimum or workable range by routine experimentation. See MPEP 2144.05. Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Morton as applied to claim 1 above, and further in view of WO2021/112784 (SAHIN). Regarding claim 7, Morton disclose the system of claim 1, but fails to teach further comprising at least one of an ink-jet, a laser beam, a LED strip or an augmented reality headset adapted to generate a visual indication of quality in relation to the meat. SAHIN teach an ink-jet, a laser beam, a LED strip or an augmented reality headset adapted to generate a visual indication of quality in relation to meat page 4, lines 10-11). It would have been obvious to one of ordinary skill in the art at the time the invention was filed to modify the system of Morton with the teachings of SAHIN to generate a visual indication to improve performance and accuracy of the system (page 3, lines 18-22). Allowable Subject Matter Claims 12-14, 19, 21-23 and 29-32 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 12, Morton disclose the system of claim 11, but fails to teach the details of wherein the X-ray scanning system comprises multi- energy photon counting X-ray sensor arrays. Regarding claim 13, Morton disclose the system of claim 11, but fails to teach the details of wherein the X-ray scanning system comprises 6 to 22 data acquisition boards corresponding to the first X-ray source and 4 to 20 data acquisition boards corresponding to the second X-ray source. Regarding claim 14, Morton disclose the system of claim 1, but fails to teach the details of wherein the X-ray scanning system is configured to acquire data in a plurality of energy bands, wherein the plurality of energy bands ranges from 3 to 20 and wherein each of the energy bands are in the range of 20-160 keV. Regarding claim 19, Morton disclose the system of claim 1, but fails to teach the details of wherein the X-ray scanning system and the hyperspectral imaging system are synchronized to an X-ray base frequency ranging from 150 to 500Hz. Regarding claim 21, Morton disclose the system of claim 1, but fails to teach the details of wherein the processor is further configured to: generate at least one graphical user interface to display at least one image corresponding to the hyperspectral imaging data; identify regions indicative of anomalies in the at least one image; and apply an annotation to the identified regions, wherein the annotation is at least one of a shape or a color. Regarding claim 22, Morton disclose the system of claim 21, but fails to teach the details of wherein the processor is configured to implement at least one machine learning model, and wherein the machine learning model is configured to analyze the hyperspectral imaging data in order to determine the quality of the meat and the regions indicative of anomalies. Regarding claim 23, Morton disclose the system of claim 22, but fails to teach the details of wherein the machine learning model is adapted to be trained using K-means clustering in order to identify the regions indicative of anomalies. Regarding claim 29, Morton disclose the system of claim 1, but fails to teach the details of wherein the computing device is further configured to segment at least one region of interest of the meat by applying a hyperspectral band-specific filtering operation, wherein the hyperspectral band-specific filtering operation is configured to isolate tissue signatures associated with one or more organs. Regarding claim 30, Morton disclose the system of claim 1, but fails to teach the details of wherein the computing device is further configured to normalize the hyperspectral imaging data using a reflectance-normalization process prior to determining the quality of the meat. Regarding claim 31, Morton disclose the system of claim 1, but fails to teach the details of wherein the quality determination comprises extracting, from the X-ray scan data, one or more volumetric density features derived from a plurality of imaging planes within the X-ray scanning tunnel. Regarding claim 32, Morton disclose the system of claim 1, but fails to teach the details of further comprising at least one radar or millimeter-wave transceiver positioned proximate the imaging tunnel, wherein the computing device is configured to combine radar-derived surface-contour data with the hyperspectral imaging data to aid in identifying anatomical boundaries of the meat. 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

Jun 05, 2023
Application Filed
Dec 27, 2025
Non-Final Rejection — §102, §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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