Prosecution Insights
Last updated: April 19, 2026
Application No. 18/296,859

ADAPTIVE SUBTRACTION FOR C-SIM MICROSCOPY

Non-Final OA §103
Filed
Apr 06, 2023
Examiner
YANG, JIANXUN
Art Unit
2662
Tech Center
2600 — Communications
Assignee
Thermo Electron Scientific Instruments LLC
OA Round
3 (Non-Final)
74%
Grant Probability
Favorable
3-4
OA Rounds
2y 9m
To Grant
93%
With Interview

Examiner Intelligence

Grants 74% — above average
74%
Career Allow Rate
472 granted / 635 resolved
+12.3% vs TC avg
Strong +19% interview lift
Without
With
+18.6%
Interview Lift
resolved cases with interview
Typical timeline
2y 9m
Avg Prosecution
45 currently pending
Career history
680
Total Applications
across all art units

Statute-Specific Performance

§101
3.8%
-36.2% vs TC avg
§103
56.1%
+16.1% vs TC avg
§102
16.7%
-23.3% vs TC avg
§112
17.1%
-22.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 635 resolved cases

Office Action

§103
DETAILED ACTION The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Claims 1-20 are pending. Claim Rejections - 35 USC § 103 The following is a quotation of pre-AIA 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action: (a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102 of this title, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negatived by the manner in which the invention was made. Claim(s) 1-8 and 19-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kuang et al (Breaking the Diffraction Barrier, 2013). Regarding claims 1, 10 and 19-20, Kuang teaches a computer-implemented image processing method with a computer processor and computer memory, comprising: accessing, from the computer memory, a non-toroidal beam image component comprising a set of pixel intensities across an imaging area and a toroidal beam image component comprising a set of pixel intensities across the imaging area that are obtained with a detector, (Kuang, Fig. 1c, confocal (single peak), non-doughnut-shaped image after pinhole filtering; Fig. 1d, negative confocal (multi-peak), doughnut-shaped image after pinhole filtering, “In FED (fluorescence emission difference microscopy), two different scanning images must be processed. One is the conventional confocal image acquired when the sample is illuminated by a solid excitation pattern; the other, the negative confocal image, is obtained when the sample is illuminated by a doughnut-shaped excitation pattern that can be generated by modulating the illumination beam with a vortex 0–2 phase plate. Both images are detected by the same pinhole, which works as a spatial filter”, p2:c1; “The fiber is attached to an avalanche photodiode ... which detects the intensity of the fluorescence beam. The detected fluorescence data are processed by a counting module ... and saved to a PC”, p5:c2-p6:c1; use a photodiode to detect light) wherein the non-toroidal beam image component includes one or more pixel intensities that are at a saturating level of the detector; identifying a peak non-toroidal imaging pixel intensity across the imaging area that is the highest non-toroidal beam imaging pixel intensity below the saturating level of the detector; (Kuang, Fig. 2(d) shows normalized negative confocal beam profiles (=> “toroidal”) in which the normalized detector saturation level is “1”; two beam profiles of ζ=3, and ζ=3 are saturated; the beam profile of ζ=1 shows a normalized peak intensity I_n(peak) just below saturation for the negative confocal beam I_n; I_n or I_n(peak) is unitless and corresponds to real intensity power P_n or P_n(peak), respectively, with power measurement unit (e.g., mW); obviously, similar behavior can be seen for confocal beam profiles (=> “non-toroidal”) with a normalized peak intensity I_c(peak) just below saturation for the confocal beam I_c which corresponds to real intensity P_c or P_c(peak), respectively, with power measurement unit (e.g., mW)) scaling, with the computer processor, an image intensity of at least one pixel of the toroidal beam image component without scaling the non-toroidal beam image component, by a scaling ratio that is defined as a ratio between the peak non-toroidal beam imaging pixel intensity across the imaging area and a peak toroidal beam imaging intensity across the imaging area to produce a scaled image intensity; and (Kuang, “The final super-resolution FED image is constructed by intensity subtraction of these two images, PNG media_image1.png 28 244 media_image1.png Greyscale where I_c, I_n, I_fed are the normalized intensity distributions of the confocal, negative confocal and FED images, respectively and r is the subtractive factor”, p2:c1; In equation (1), both the confocal (I_c, non-toroidal) and negative confocal (I_n, toroidal/doughnut-shaped) images are normalized intensities corresponding to real power P_c and , which requires scaling the maximum pixel intensity (the peak) of each of I_c and I_n to 1 before calculating the intensity difference; data normalization is well defined in the art (e.g., see Thakur, “Normalization Formula”, 2022, (https://web.archive.org/web/20221001053816/https://www.educba.com/normalization-formula/); in Thakur, let x_min =0, then, normalized x_new(normalized to x_max) = x/x_max; apply this general normalization formula to I_n, we have I_n = P_n/P_n(peak) = P_n/P_n(peak) * (P_c(peak)/P_c(peak)); so that I_n * P_c(peak) = (P_c(peak)/P_n(peak))*P_n; note that left side represents the P_n scaled to reference P_c(peak); That is, P_n(scaled) = I_n * P_c(peak) = (P_c(peak)/P_n(peak))*P_n, eq. (2); in eq. (2), when P_n = P_n(peak), P_n(scaled) is scaled to being P_c(peak), that is, P_n(scaled, peak) = P_c(peak), meaning that the normalized I_c and I_n with max intensity “1” correspond to P_n(scaled, peak) and P_c(peak) are the same; also in eq. (2), only P_n, not P_c, is scaled) determining a difference between the scaled image intensity of the at least one pixel of the toroidal image component and an image intensity of a corresponding pixel of the non-toroidal image components to form at least a portion of an image. (Kuang, “The final super-resolution FED image is constructed by intensity subtraction of these two images, I(fed) = I(c) – r*I(n), eq. (1); where I(c), I(n), I(fed) are the normalized intensity distributions of the confocal, negative confocal and FED images, respectively and r is the subtractive factor”, p2:c1; when r=1, I_fed of eq. (1) represents the difference between the normalized I_c and I_n; using eq. (2) to convert eq.(1) to real power in reference (scaled) to P_c(peak) leads to: I_fed*P_c(peak) = I_c*Pc(peak) - I_n*P_c(peak); then scaling eq. (1) to P_c(peak) becomes: P_fed(scaled) = P_c – P_n(scaled), eq. (3) ; only P_n and the resulting P_fed, not P_c, are scaled) Regarding claims 4 and 13, Kuang teaches its/their respective base claim(s). Kuang further teaches the method of claim 1, further comprising acquiring the non-toroidal beam image component and the toroidal beam image component by: directing a non-toroidal beam to a sample area and detecting non-toroidal beam induced response light from the sample area, wherein the detected non-toroidal beam induced response light corresponds to the non-toroidal beam image component; and directing a toroidal beam to the sample area and detecting toroidal beam induced response light from the sample area, wherein the detected toroidal beam induced response light corresponds to the toroidal image component. (Kuang, Fig. 1; “In FED, two different scanning images must be processed. One is the conventional confocal image acquired when the sample is illuminated by a solid excitation pattern; the other, the negative confocal image, is obtained when the sample is illuminated by a doughnut-shaped excitation pattern that can be generated by modulating the illumination beam with a vortex 0–2 PNG media_image2.png 9 10 media_image2.png Greyscale phase plate. Both images are detected by the same pinhole, which works as a spatial filter”, p2:c1) Regarding claims 5 and 14, Kuang teaches its/their respective base claim(s). Kuang further teaches the method of claim 4, wherein the non-toroidal beam comprises a Gaussian intensity profile at the sample area and the toroidal beam comprises a toroidal intensity profile at the sample area. (Kuang, Figs. 1(a) and 1(c); Gaussian beam distribution; “intensity distributions with a Gaussian function”, p6:c1 Regarding claims 6 and 15, Kuang teaches its/their respective base claim(s). Kuang further teaches the method of claim 4, wherein the directing the toroidal beam to the sample area comprises directing a source beam through a vortex phase plate to produce the toroidal beam. (Kuang, “whereas in the negative confocal case, where the illumination beam is phase-modulated by a vortex 0–2pi phase plate, f(θ, φ)”, p5:c2) Regarding claim 8, Kuang teaches its/their respective base claim(s). Kuang further teaches the method of claim 1, wherein the formed image is a super-resolution image. (Kuang, the FED shown in Fig. 1(d) is a “The final super-resolution FED image”, p2:c1) Regarding claim 16, Kuang teaches its/their respective base claim(s). Kuang further teaches the apparatus of claim 15, wherein the beam source comprises an azimuthal polarizer and a spatial light modulator situated to produce the toroidal beam. (Kuang, “f(θ, φ) is the phase modulation function for the incident beam. In the confocal case, f(θ, φ) = 0, whereas in the negative confocal case, where the illumination beam is phase-modulated by a vortex 0–2pi phase plate, f(θ, φ) = φ”, p5:c2; φ is azimuth variable) Regarding claim 18, Kuang teaches its/their respective base claim(s). Kuang further teaches the apparatus of claim 10, wherein the formed image is a super-resolution light scattering image, phosphorescence image, or a fluorescence image. (Kuang, the FED shown in Fig. 1(d) is a “The final super-resolution FED image”, “fluorescence emission difference microscopy (FED)”, p2:c1) Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kuang et al (Breaking the Diffraction Barrier, 2013) in view of Wang et al (WF Super-Resolved Raman Imaging, 2021). Regarding claim 9, Kuang teaches its/their respective base claim(s). Kuang does not expressly disclose but Wang teaches the method of claim 8, wherein the super-resolution image is a Raman scattering image. (Wang, Fig. 1, structured illumination Raman microscopy) Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate the teachings of Wang into the system or method of Kuang in order to use Raman spectroscopy for rapid, non-destructive molecular analysis with high specificity and minimal sample preparation. The combination of Kuang and Wang also teaches other enhanced capabilities. Response to Arguments Applicant's arguments filed on 1/5/2026 with respect to one or more of the pending claims have been fully considered but they are not persuasive. Regarding claim(s) 1, 10 and 20, Applicant, in the remarks, argues that the cited reference(s) fails to teach the newly amended limitations in the claims. The Examiner respectfully disagreed. The office action has been updated to address applicant’s argument. See the updated review comments for details. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to JIANXUN YANG whose telephone number is (571)272-9874. The examiner can normally be reached on MON-FRI: 8AM-5PM Pacific Time. 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, Amandeep Saini 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. /JIANXUN YANG/ Primary Examiner, Art Unit 2662 2/7/2026
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Prosecution Timeline

Apr 06, 2023
Application Filed
May 07, 2025
Non-Final Rejection — §103
Aug 12, 2025
Response Filed
Oct 01, 2025
Final Rejection — §103
Dec 15, 2025
Interview Requested
Dec 22, 2025
Examiner Interview Summary
Dec 22, 2025
Applicant Interview (Telephonic)
Jan 05, 2026
Request for Continued Examination
Jan 05, 2026
Response after Non-Final Action
Jan 07, 2026
Response after Non-Final Action
Feb 08, 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

3-4
Expected OA Rounds
74%
Grant Probability
93%
With Interview (+18.6%)
2y 9m
Median Time to Grant
High
PTA Risk
Based on 635 resolved cases by this examiner. Grant probability derived from career allow rate.

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