Prosecution Insights
Last updated: April 19, 2026
Application No. 18/864,329

IDENTIFYING A REGION OF INTEREST OF A SAMPLE

Non-Final OA §103
Filed
Nov 08, 2024
Examiner
DANG, HUNG Q
Art Unit
2484
Tech Center
2400 — Computer Networks
Assignee
Cellavision AB
OA Round
1 (Non-Final)
68%
Grant Probability
Favorable
1-2
OA Rounds
3y 1m
To Grant
87%
With Interview

Examiner Intelligence

Grants 68% — above average
68%
Career Allow Rate
1257 granted / 1841 resolved
+10.3% vs TC avg
Strong +18% interview lift
Without
With
+18.3%
Interview Lift
resolved cases with interview
Typical timeline
3y 1m
Avg Prosecution
95 currently pending
Career history
1936
Total Applications
across all art units

Statute-Specific Performance

§101
4.2%
-35.8% vs TC avg
§103
54.1%
+14.1% vs TC avg
§102
23.6%
-16.4% vs TC avg
§112
11.6%
-28.4% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1841 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. Claims 1-12 are rejected under 35 U.S.C. 103 as being unpatentable over Peng et al. (US 2020/0372235 A1 – hereinafter Peng) and Kang (US 2004/0114688 A1 – hereinafter Kang). Regarding claim 1, Peng discloses a method for identifying a region of interest of a sample (Fig. 1; [0039]; [0053] – a method for detecting a region of interest of a tissue sample), the method comprising: capturing, by an image sensor, a plurality of digital image data sets, each digital image data set comprising pixels and pertaining to a position of a plurality of positions of the sample (Fig. 1; [0039] – capturing, by a camera within a scanner, a digital image, which is the second digital magnified image at step 120 of Fig. 2 – the digital image data comprise a plurality of digital image data sets, which is equal to a number of pixels in the down-sampled image described at least in [0046], each of such digital image data sets comprising corresponding pixels in the original digital image data which are reduced to a corresponding pixel in the down-sampled image at corresponding position); forming a common compressed digital representation ([0046] – forming a down-sampled image data which corresponds to a common compressed representation of the original image); and identifying a region of interest of the sample based on a pixel value of the common compressed digital representation ([0053] – in case the second image is down-sampled, detecting a region of interest of the sample based on the pixels’ intensity of the down-sampled image). However, Peng does not disclose for each digital image data set: forming a set of combined pixels, each combined pixel having a pixel value, and wherein each pixel value is determined based on at least one of an intensity value and a color value pertaining to a subset of pixels of the digital image data set, and forming a compressed digital representation comprising the set of combined pixels; arranging the compressed digital representations in a data structure, thereby forming a common compressed digital representation of the sample, wherein the data structure for each compressed digital representation includes information pertaining to a position of the plurality of positions of the sample of the digital image data set associated with the compressed digital representation. Kang discloses for each digital image data set: forming a set of combined pixels, each combined pixel having a pixel value, and wherein each pixel value is determined based on at least one of an intensity value and a color value pertaining to a subset of pixels of the digital image data set ([0067] – for each group of several pixels, forming a set of combined pixels comprising at least a single pixel having the average pixel value of the group), and forming a compressed digital representation comprising the set of combined pixels ([0067] – generating a compressed digital representation comprising the new pixel having average pixel value of the corresponding group); arranging the compressed digital representations in a data structure, thereby forming a common compressed digital representation of the sample, wherein the data structure for each compressed digital representation includes information pertaining to a position of the plurality of positions of the sample of the digital image data set associated with the compressed digital representation ([0067] – arranging the compressed digital representations in a data structure, which is the down-sampled image by substituting each of the new pixels in the appropriate place in an approximated image, which is a data structure and thereby forming the common compressed digital representation). One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to incorporate the teachings of Kang into the method taught by Peng to down-sample the second image to effectively lower the image resolution while minimizing noise and preserving overall trends of pixel values in the original image. Regarding claim 2, see the teachings of Peng and Kang as discussed in claim 1 above, in which Kang also discloses each pixel value of the sets of combined pixels is an average value, a median value, or a sum of the subset of pixels of the respective digital image data set ([0067] – at least an average value). The motivation for incorporating the teachings of Kang into the method has been discussed in claim 1 above. Regarding claim 3, Peng in view of Kang also discloses the method according to claim 1, wherein each set of combined pixels consists of one combined pixel ([0046] –each of such digital image data sets comprising corresponding pixels in the original digital image data which are reduced to a corresponding pixel in the down-sampled image at corresponding position). Regarding claim 4, Peng in view of Kang also discloses the method according to any one of claims 1, wherein the subset of pixels of the digital image data set consists of all pixels of the digital image data set ([0046] – each of such digital image data sets comprising corresponding pixels in the original digital image data which are reduced to a corresponding pixel in the down-sampled image at corresponding position). Regarding claim 5, Peng in view of Kang also discloses the method according to any one of claims 1, wherein the subset of pixels ([0046] – the subset of pixels is selected is a predetermined subset of pixels according to a specific selected sub-sampling, i.e. which specific “several pixels” are selected for a group). Claim 6 is rejected for the same reason as discussed in claim 1 above in view of Peng also disclosing a device for identifying a region of interest of a sample (Fig. 1 – a device shown in Fig. 1), comprising: an image sensor ([0039] – a camera); and circuitry configured to execute the recited functions (see discussion of claim 1 above). Claim 7 is rejected for the same reason as discussed in claim 2 above. Claim 8 is rejected for the same reason as discussed in claim 3 above. Claim 9 is rejected for the same reason as discussed in claim 4 above. Claim 10 is rejected for the same reason as discussed in claim 5 above. Regarding claim 11, Peng in view of Kang also discloses the according to claim 6, wherein the device is a camera ([0039]). Claim 12 is rejected for the same reason as discussed in claim 1 above in view of Peng also disclosing a non-transitory computer-readable storage medium comprising program code portions that, when executed on a device comprising processing capabilities and an image sensor, performs the method according to claim 1 ([0032] - implemented by appropriate computer programs carried on tangible carrier media (e.g. disks) run on computers). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to HUNG Q DANG whose telephone number is (571)270-1116. The examiner can normally be reached IFT. 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, Thai Q Tran can be reached at 571-272-7382. 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. /HUNG Q DANG/Primary Examiner, Art Unit 2484
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Prosecution Timeline

Nov 08, 2024
Application Filed
Feb 26, 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
68%
Grant Probability
87%
With Interview (+18.3%)
3y 1m
Median Time to Grant
Low
PTA Risk
Based on 1841 resolved cases by this examiner. Grant probability derived from career allow rate.

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