Prosecution Insights
Last updated: April 19, 2026
Application No. 18/259,488

METHOD FOR PROCESSING VOLUME IMAGES BY PRINCIPAL COMPONENT ANALYSIS

Final Rejection §103
Filed
Jun 27, 2023
Examiner
ZHAO, LEI
Art Unit
2668
Tech Center
2600 — Communications
Assignee
Centre National De La Recherche Scientifique
OA Round
2 (Final)
74%
Grant Probability
Favorable
3-4
OA Rounds
3y 1m
To Grant
99%
With Interview

Examiner Intelligence

Grants 74% — above average
74%
Career Allow Rate
41 granted / 55 resolved
+12.5% vs TC avg
Strong +31% interview lift
Without
With
+30.9%
Interview Lift
resolved cases with interview
Typical timeline
3y 1m
Avg Prosecution
29 currently pending
Career history
84
Total Applications
across all art units

Statute-Specific Performance

§101
4.8%
-35.2% vs TC avg
§103
64.4%
+24.4% vs TC avg
§102
26.2%
-13.8% vs TC avg
§112
4.6%
-35.4% vs TC avg
Black line = Tech Center average estimate • Based on career data from 55 resolved cases

Office Action

§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 Objections Claim 15 is objected to because of the following informalities: Claim 15 as recited is ambiguous. For the record, the examiner recommends claim 15 to be rewritten as follow, and interpretation will be as such until clarification is made of record or applicant accepts this proposal and makes changes accordingly. 15. A non-transitory computer-readable medium comprising instructions stored thereon that when executed by a processor cause the processor to execute a processing method according to claim 1 Response to Arguments Applicant's arguments filed December 22, 2025 have been fully considered but they are not persuasive. Regarding claim 1, applicant states that “There is no teaching, suggestion, or motivation in either Schneider or Tahmasebi, or in their combination, that would prompt a person of ordinary skill in the art to have applied Tahmasebi's PCA-based medical image deformation analysis to Schneider's industrial part characterization method, in order to achieve the specific goal of quantifying geometric dispersion between multiple distinct industrial parts.”. Examiner disagrees with this statement. In response to applicant's argument that Tahmasebi is nonanalogous art, it has been held that a prior art reference must either be in the field of the inventor’s endeavor or, if not, then be reasonably pertinent to the particular problem with which the inventor was concerned, in order to be relied upon as a basis for rejection of the claimed invention. See In re Oetiker, 977 F.2d 1443, 24 USPQ2d 1443 (Fed. Cir. 1992). In this case, Tahmasebi teaches a multi-modal deformable image registration method by quantifying geometric dispersion between multiple distinct images with different deformation states (for the landmark positions of one deformed state and performing registration between the landmark positions of other deformation state to generate deformation field (i.e., displacement fields) using, for example, principal component analysis (i.e., dimensionality reduction method), based on the deformation field to calculate an average deformation and the deformation mode eigenvectors. Page 7 13th paragraph), which is reasonably pertinent to the particular problem with which the inventor was concerned with analyzing the geometric dispersion of industrial components. applicant states that “A distinction lies in what constitutes the input to the PCA for eigenmode derivation. In Tahmasebi, PCA is used on the mean deformation to derive modes of object deformation. (Tahmasebi at [0046].)”. Examiner disagrees with this statement. Tahmasebi discloses a dimensionality-reduction method of a plurality of image displacement fields to express them according to eigenmodes. This means PCA is applied directly to the plurality of displacement fields ( PNG media_image1.png 554 1000 media_image1.png Greyscale ) and not the mean deformation, to derive modes of variability to capture inter-image variability patterns across a batch of distinct images. Tahmasebi’s application and purpose of PCA are to solve the same problem as the applicant's approach. Response to Amendment The Amendment of December 22, 2025 overcomes the following rejection/objection: Rejection of claim 15 based on 35 USC 101. Objections to drawings. 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. Claims 1, 3, 5-7 and 9-15 are rejected under 35 U.S.C. 103 as being unpatentable over Schneider (Chinese Patent Publication No.: CN 106233126 A), hereinafter Schneider, in view of Tahmasebi (PCT Patent Publication No.: WO 2013/136278 A1), hereinafter Tahmasebi. Regarding claim 1, Schneider teaches a method, implemented by a computer system, for processing a plurality of X-ray tomography volume images (The invention relates to a method for characterizing a component (10), comprising obtaining the parts of the X-ray tomography image. Abstract. information contained in X-ray tomography image is useful, because it relates to the entire volume parts, and only near its microstructure, and close the defect. Page 2 2nd paragraph), to quantify [[the]] a geometric dispersion between parts (said correlation step (200) is included in a predetermined set of X-ray tomography image of transformation (30) searching (40) minimizes the difference (50) between the image and the reference to characterizing (300, 350) of the part (10). Abstract), the plurality of volume images comprising a reference volume image (followed by the step of the image associated with the reference (20) to step(200), wherein: said correlation step (200) is included in a predetermined set of X-ray tomography image of transformation (30) searching (40) minimizes the difference (50) between the image and the reference to characterizing (300, 350) of the part (10). Abstract), including: - a step [[the]] a difference between the volume images (followed by the step of the image associated with the reference (20) to step(200), wherein: said correlation step (200) is included in a predetermined set of X-ray tomography image of transformation (30) searching (40) minimizes the difference (50) between the image and the reference to characterizing (300, 350) of the part (10). Abstract). Schneider does not teach the following limitations as further recited, but Tahmasebi further teaches - a processing by dimensionality reduction method (for the landmark positions of one deformed state and performing registration between the landmark positions of other deformation state to generate deformation field (i.e., displacement fields). using, for example, principal component analysis (i.e., dimensionality reduction method), based on the deformation field to calculate an average deformation and the deformation mode eigenvectors. Page 7 13th paragraph), and - a statistical analysis (This invention relates to the field of medical imaging, and more particularly, to a distortion modelling for using statistical and sparse deformation data automatic multimode deformable registration method, system and computer program product. [0001]) of the fields expressed according to the eigenmodes (Then, according to the deformation field computing for a plurality of target average deformation and the deformation mode eigenvectors. [0010]). It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Schneider to incorporate the teachings of Tahmasebi to utilize dimensionality reduction method of the plurality of the image displacement fields to express them according to eigenmodes and a statistical analysis of the fields expressed according to the eigenmodes in order to implement a distortion modelling for using statistical and sparse deformation data automatic multimode deformable registration method. Claim 3, unamended and is rejected based on the combination of Schneider, in view of Tahmasebi. The grounds of rejection established in the last Office Action is fully incorporated herein. Regarding claim 5, Tahmasebi in the combination teaches the method according to claim 1, wherein the dimensionality reduction method on a plurality of transformed displacement fields PNG media_image2.png 26 22 media_image2.png Greyscale is implemented by [[the]] a formula: PNG media_image3.png 36 130 media_image3.png Greyscale with PNG media_image4.png 30 50 media_image4.png Greyscale [[the]] a covariance matrix of the plurality of displacement fields PNG media_image5.png 28 30 media_image5.png Greyscale ( PNG media_image6.png 674 1006 media_image6.png Greyscale PNG media_image7.png 340 1002 media_image7.png Greyscale . A person having ordinary skill in the art would recognize the transformed displacement fields can be expressed in terms of the covariance matrix.). Regarding claim 6, Tahmasebi in the combination teaches the method according to claim 3, wherein the processing by principal component analysis makes it possible to express a displacement field PNG media_image8.png 22 58 media_image8.png Greyscale with PNG media_image9.png 24 82 media_image9.png Greyscale ( PNG media_image1.png 554 1000 media_image1.png Greyscale ) according to [[the]] a formula: PNG media_image10.png 54 284 media_image10.png Greyscale with PNG media_image11.png 32 38 media_image11.png Greyscale [[the]] a covariance matrix of the plurality of displacement fields, PNG media_image12.png 30 50 media_image12.png Greyscale a basis of shape functions from the method of [[the]] finite elements, PNG media_image13.png 22 20 media_image13.png Greyscale [[the]] eigenvalues, PNG media_image14.png 22 26 media_image14.png Greyscale an eigenmode, and PNG media_image15.png 26 24 media_image15.png Greyscale [[the]] an associated right eigenmode ( PNG media_image6.png 674 1006 media_image6.png Greyscale PNG media_image7.png 340 1002 media_image7.png Greyscale . A person having ordinary skill in the art would recognize the displacement fields can be expressed in terms of the covariance matrix, the shape function, eigen values and eigen mode.). Regarding claim 7, Tahmasebi in the combination teaches the method according to claim 1, further comprising a determination of an average image PNG media_image16.png 24 38 media_image16.png Greyscale : PNG media_image17.png 66 180 media_image17.png Greyscale with N [[the]] a number of images ( PNG media_image18.png 468 1012 media_image18.png Greyscale ). Schneider in the combination further teaches PNG media_image19.png 24 52 media_image19.png Greyscale the images obtained after application of the displacement field PNG media_image20.png 22 34 media_image20.png Greyscale : PNG media_image21.png 28 178 media_image21.png Greyscale (In addition, a general transformation type is caused by a group of continuous displacement field u (x), is as follows: Tu [f (x)] = f (x + u (x)). Page 2 8th paragraph). Claim 9, unamended and is rejected based on the combination of Schneider, in view of Tahmasebi. The grounds of rejection established in the last Office Action is fully incorporated herein. Regarding claim 10, Schneider in the combination teaches a method for monitoring a line of manufacture of parts (in the usual manner, which is possible on the composite material parts such as turbojet blade for non-destructive testing (NDT). described technology saves examination and obtaining and storing the time data. Accordingly, for example, during step 350, it is possible only to determine whether the part should be retained or rejected based on transformation T*. Page 5 4th paragraph) comprising an acquisition of X-ray tomography volume images of the parts (reconstruction part 10 in a part 10 of the original X-ray tomography image, such as composite material parts, the image can be small by some X-ray chromatography photography data 100 (i.e., the number of projection). Page 4 last paragraph), - an implementation of the processing method according to claim 1 on [[the]] an acquired X-ray tomography volume images (in the embodiment shown in FIG. 1 uses a real reference image 20, image parts such as standard or template. reconstruction part 10 in a part 10 of the original X-ray tomography image, such as composite material parts, the image can be small by some X-ray chromatography photography data 100 (i.e., the number of projection). using a group is considered to be a transformation of the real 30 performs reconstruction. calculation is based on finding and identifying the group 30 in the transformed T* (refer to 40). by searching the minimum value (optimal 200) described in the preface to perform the identification. at the same time, determining the topological difference Delta (reference 50) is associated. Page 4 last paragraph). Claims 11-13, unamended and are rejected based on the combination of Schneider, in view of Tahmasebi. The grounds of rejection established in the last Office Action is fully incorporated herein. Apparatus claim 14 is drawn to the apparatus corresponding to the method of using same as claimed in claim 1. Therefore apparatus claim 14 corresponds to method claim 1, and is rejected for the same reasons of obviousness as used above. Claim 15 is drawn to a non-transitory computer-readable medium including instructions for the execution of the steps of a processing method according to claim 1, when said program is executed by a computer. Therefore, claim 15 corresponds to method claim 1, and is rejected for the same reasons of obviousness as used above. Claims 2 and 4 are rejected under 35 U.S.C. 103 as being unpatentable over Schneider (Chinese Patent Publication No.: CN 106233126 A), hereinafter Schneider, in view of Tahmasebi (PCT Patent Publication No.: WO 2013/136278 A1), hereinafter Tahmasebi, further in view of Jolliffe (Principal component analysis: a review and recent developments, Phil. Trans. R. Soc. A 374: 20150202. http://dx.doi.org/10.1098/rsta.2015.0202), hereinafter Jolliffe. Claim 2, unamended and is rejected based on the combination of Schneider, in view of Tahmasebi, and further in view of Jolliffe. The ground of rejection established in the last Office Action is fully incorporated herein. Regarding claim 4, Tahmasebi in the combination teaches the method according to claim 3, wherein the plurality of images contains N images each associated with a displacement field PNG media_image22.png 26 186 media_image22.png Greyscale ( PNG media_image1.png 554 1000 media_image1.png Greyscale ). Jolliffe in the combination further teaches wherein the processing by principal component analysis makes it possible to express a displacement field according to [[the]] a formula: PNG media_image23.png 250 722 media_image23.png Greyscale ( PNG media_image24.png 398 984 media_image24.png Greyscale Page 3 5th paragraph). Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Schneider (Chinese Patent Publication No.: CN 106233126 A), hereinafter Schneider, in view of Tahmasebi (PCT Patent Publication No.: WO 2013/136278 A1), hereinafter Tahmasebi, further in view of Zhao (Multimode analysis and online monitoring for injection molding processes, 2017 29th Chinese Control And Decision Conference (CCDC) (2017, Page(s): 3451-3456), hereinafter Zhao. Regarding claim 8, Schneider and Tahmasebi teach all of the elements of the claimed invention as stated in claim 1 except for the following limitations as further recited. However, Zhao teaches wherein one of the characteristics of production of the parts may vary, the method further comprising a determination of one or more modes affected by that characteristic, and a determination of [[the]] an influence of the characteristic on [[the]] a geometry of the parts (In this work, the process modeling and online monitoring for an injection molding process is conducted by utilizing PCA and ICA to trace the multimode characteristic along the batch direction. First, after phase division, Jarque-Bera test is utilized as the normality test to analyze the normality of process data. Then, different models are established for different inter-batch modes according to their different characteristic, so the online monitoring model is properly chosen by identifying which mode the new data belongs to. ICA-PCA method I applied, and the analysis of the multimode characteristic of the injection molding process will be given. So the online monitoring of the multi-mode injection molding process can be conducted. Page 3452 left column 3rd paragraph). It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Schneider and Tahmasebi to incorporate the teachings of Zhao to determine one or more modes affected by the characteristics of production of the parts which may vary in production and determine the influence of the characteristic on the geometry of the parts so that online monitoring model can be properly chosen by identifying which mode to apply to the production of the part. Conclusion THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to LEI ZHAO whose telephone number is (703)756-1922. The examiner can normally be reached Monday - Friday 8:00 am - 5:00 pm. 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, VU LE can be reached at (571)272-7332. 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. /LEI ZHAO/Examiner, Art Unit 2668 /VU LE/Supervisory Patent Examiner, Art Unit 2668
Read full office action

Prosecution Timeline

Jun 27, 2023
Application Filed
Sep 25, 2025
Non-Final Rejection — §103
Dec 22, 2025
Response Filed
Feb 12, 2026
Final Rejection — §103 (current)

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Prosecution Projections

3-4
Expected OA Rounds
74%
Grant Probability
99%
With Interview (+30.9%)
3y 1m
Median Time to Grant
Moderate
PTA Risk
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