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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on March 4, 2026 has been entered.
Response to Arguments
Applicant’s arguments and amendment have persuasively overcome the claim objection, almost all of the 112 rejections (including those related to 112f) and the prior art rejections (though the new mapping uses the same references).
The remaining issues are addressed below.
On the first page of remarks, Applicant makes a series of incorrect assertions. If these statements were accepted as is, the response would be non-responsive. For example, if Applicant’s remarks “are not necessarily related to patentability,” then the remarks fail to meet 37 C.F.R. 1.111(b)’s requirement that “the reply must present arguments pointing out the specific distinctions believed to render the claims, including any newly presented claims, patentable over any applied references,” among others. Further, Applicant cannot reserve the right to revoke views after prosecution closes. Compare, for example, Applicant’s remarks with the procedures for Supplemental Re-examination (including large entity fees of $4,965 for the request and $13,655 should the re-examination be ordered. For Applicant’s statements regarding IDSes, Applicant is reminded of the signature requirements in 37 C.F.R. 11.18. Lastly, the distinction between the Applicant and an entity with authority to prosecute is not clear, but if some aspect of Applicant’s response was not properly authorized, please make this of record so that it can be corrected.
The examiner has determined that because this filing is responsive other than these introductory remarks, rather than determining that this response is non-responsive, the better approach is to treat these introductory remarks as a mistake and ignore them. “The PTO properly can refuse to follow an impermissible instruction that would cause a mistake and loss of rights.” Exxon Corp. v. Phillips Petroleum Co., 265 F. 3d 1249 (Fed. Cir. 2001). Note that both in this situation and in Exxon, the issue was one of complying with USPTO regulations, not statutes.
Regarding Applicant’s 101 arguments, most of these points were addressed in the response section of the previous office action. Applicant is not claiming an improvement in computer technology because Applicant’s improvements are specific to this particular use case (i.e., they are not generally applicable). The relevance of Desjardins is not apparent because that was directed to training machine learning model, but the present invention is using standard training techniques.
Applicant’s prior art arguments are persuasive. A new mapping has been provided.
Claim Objections
Claim 1 is objected to because of the following informalities:
Claim 1 recites a quotation mark at the end of the sixth line.
Claim 1 recites “an magnetic,” but the “an” should be ‘a’.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-17 and 19-21 (all claims) are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claims 1, 9, and 21 recite “wherein the processor being configured to transform … in real-time during the procedure,” but this is new matter. Real-time processing is only disclosed in Specification, [0038] and that is directed to registration, but does not disclose the claimed transformations.
Dependent claims are likewise rejected.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-17 and 19-21 (all claims) are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea (mental process) without significantly more.
Step 1:
Claim 1 (and its dependents) recite a system, and machines are eligible subject matter.
Claim 9 (and its dependents) recite a method, and processes are eligible subject matter.
Claim 21 recites one or more non-transitory computer-readable media, and manufactures are eligible subject matter.
Step 2A, prong one: All of the elements of claims 1-21 are a mental process because a person can look at pictures of an eye and visualize how the entire eye looks. Further, the neural networks are also mental processes, see example 47, claim 2, element (d) (from the July 2024 AI subject matter eligibility examples). MPEP 2106.04(a)(2)(III)(C) explains that use of a generic computer or in a computer environment is still a mental process. In particular, this section begins by citing Gottschalk v. Benson, 409 US 63 (1972). “The Supreme Court recognized this in Benson, determining that a mathematical algorithm for converting binary coded decimal to pure binary within a computer’s shift register was an abstract idea.” In Benson the Supreme Court did not separately analyze the computer hardware at issue; the specifics of what hardware was claimed is only included in an appendix to the decision.
Because there are no additional elements, no further analysis is required for Step 2A, prong two or Step 2B.
The specification identifies the solution to the present problem. See, specification, [0023] “In some cases, deep learning approaches can be applied to image registration to increase the speed and accuracy of the registration process” and [0024] “Embodiments described herein provide systems and techniques for performing ophthalmic image registration using an interpretable deep learning based AI algorithm.” Along these lines, the specification admits that these techniques are otherwise conventional. See, e.g., specification [0001] and [0022]. Under the current eligibility guidance, use of deep learning (such as a neural network) is considered an abstract idea and thus insufficient for eligibility. In other words, this invention follows the analysis of Recentive.
Examiner Notes
1) Claims 1, 9, and 21 recite images being in a same coordinate system. While specification [0033] suggests that the intent is that the photos are all aligned (and presumably scaled, but this is not disclosed), the broadest reasonable interpretation of “being in a same coordinate system” in light of the specification would appear to encompass all of the images without transformations because coordinate systems are imaginary, and any given image can be assigned to a point in a shared cartesian coordinate system (e.g., if a photo is rotated to be upside down, it could be in the same coordinate system).
2) The claims would be clearer if they recited that the images at issue were of the patient.
3) Claim 1’s MRI device does not invoke 112(f) because this refers to known structure.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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 1-7, 9-16 and 20 (all claims except those rejected for 103 below) are rejected under 35 U.S.C. 103 as being unpatentable over US20220058803A1 (“Bhattacharya”) in view of US20220044406A1 (Spizhevoy”).
1. An ophthalmic system for performing ophthalmic image registration during a procedure, comprising:
one or more ophthalmic imaging devices to generate a plurality of images of an eye of a user, each of the plurality of images comprising a different view of the eye, the one or more ophthalmic imaging devices selected from the group consisting of an optical coherence tomography (OCT) device, an optical biometer, a digital keratometer, a rotating camera, an magnetic resonance imaging (MRI) device, a digital microscope, a digital camera, and a digital fundus camera; (Bhattacharya, Fig. 22. [0095] “For example, the OCT system may be used with a surgical system or surgical microscope system for diagnostic or treatment purposes.” [0096] discusses artifacts in the image, this teaches that the microscope is a digital microscope. See also, [0045] regarding fundus imagers.)
a memory comprising executable instructions; and (Bhattacharya, [0119] “Processor Cmp1 includes hardware for executing instructions, such as those making up a computer program.”)
a processor in data communication with the memory and configured to execute the executable instructions to: (Bhattacharya, [0119] “Processor Cmp1 includes hardware for executing instructions, such as those making up a computer program.”)
determine, within each image of the plurality of images, one or more regions of interest corresponding to anatomical eye features within the image, based on evaluating the image with one or more neural networks; (Bhattacharya, Fig. 8. See the below combination regarding skin and sclera (though Fig. 8 teaches other anatomical features))
determine, within each image of the plurality of images, a set of point features of the eye being located within the one or more regions of interest, based on evaluating the image with at least one of the one or more neural networks, the one or more regions of interest of the image including a plurality of points and the set of point features of the eye for the image including only a subset of the plurality of points in the one or more regions of interest of the image; (Bhattacharya, [0032] “FIGS. 17A and 17B illustrate that the presently trained NN model learns the structure of vessels of an eye.” See specification, [0045] “The point features 216 generally include a set of feature within the respective image that can be used to uniquely identify the image. In some examples, the unique features may correspond to different blood vessels of the eye that are visible within the respective image.”)
generate a set of transformation information for transforming at least one of the plurality of images, based on performing one or more image processing operations on the set of point features within each image of the plurality of images; and (Bhattacharya, [0065] “transform parameters”)
transform the at least one of the plurality of images, in real-time during the procedure, based on the set of transformation information, wherein the processor being configured to transform the at least one of the plurality of images comprises at least one of scaling the at least one of the plurality of images, translating the at least one of the plurality of images, or rotating the at least one of the plurality of images, such that the plurality of images with the different views, including the intra-operative image, are in a same coordinate system in real-time during the procedure. (Bhattacharya, claim 5 “applies an image registration technique to the plurality of second images to produce image alignment settings.” [0095] states that this is used with a surgical system, teaching the claimed timing.)
Bhattacharya is not relied on for the below claim language.
However, Spizhevoy teaches the one or more regions of interest including regions of skin and of sclera, (Spizhevoy, abstract, “In one aspect, after receiving an eye image, a device such as an augmented reality device can process the eye image using a convolutional neural network with a merged architecture to generate both a segmented eye image and a quality estimation of the eye image. The segmented eye image can include a background region, a sclera region, an iris region, or a pupil region.” [0028] “Eye images can include the periocular region of the eye, which includes … skin surrounding the eye.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply the teachings of Spizhevoy to the teachings of Bhattacharya such that where Bhattacharya is non-specific about parts of an eye (e.g., Bhattacharya, claim 26, “image sets of different target ophthalmic regions”), Spizhevoy teaches the various parts of the eye that can have maladies. For example, Bhattacharya [0045] “Ophthalmic images, in general, are an integral part of diagnosing a particular eye-related malady” but does not name scleritis.
Based on the above, this is an example of “combining prior art elements according to known methods to yield predictable results.” MPEP 2143.
2. The ophthalmic system of claim 1, wherein the processor is further configured to execute the executable instructions to extract, from at least one of the one or more neural networks, a set of features associated with each of the plurality of images. (Bhattacharya, [0059] “The individual scans (S1S1 to S1Sn) may be registered by identifying characteristic features”)
3. The ophthalmic system of claim 2, wherein the set of features associated with each of the plurality of images is extracted from a middle layer of the at least one of the one or more neural networks. (Bhattacharya, Fig. 2, Image Registration 17)
4. The ophthalmic system of claim 3, wherein the processor is further configured to execute the executable instructions to:
determine an amount of similarity between the plurality of images, based on comparing the sets of features; and (Bhattacharya, [0059] “The individual scans (S1S1 to S1Sn) may be registered by identifying characteristic features.” Bhattacharya’s registering teaches the claimed determining similarity.)
provide an indication of the amount of similarity. (Bhattacharya, [0059] “The individual scans (S1S1 to S1Sn) may be registered by identifying characteristic features.” Bhattacharya’s registering teaches the claimed indicating similarity.)
5. The ophthalmic system of claim 4, wherein the at least one of the plurality of images is transformed upon determining that the amount of similarity satisfies a predetermined condition. (Bhattacharya, [0059] “The individual scans (S1S1 to S1Sn) may be registered by identifying characteristic features”)
6. The ophthalmic system of claim 1, wherein the one or more neural networks is a single neural network. (Bhattacharya, [0016] “FIG. 1 illustrates a neural network architecture in accord with the present invention.”)
7. The ophthalmic system of claim 1, wherein the one or more neural networks comprises
(i) a first neural network configured to provide an indication of the one or more regions of interest of the eye and (Bhattacharya, Fig. 8)
(ii) a second neural network configured to provide an indication of the set of point features. (Bhattacharya, [0113] (as mapped above) is shown in Fig. 27, which is a neural network for a single image, see, e.g., [0112] or [0115] discussing 128x128 patches)
Claims 9-15 and 21 are rejected as per the corresponding system claims.
16. The computer-implemented method of claim 9, wherein each of the one or more neural networks is based on a U-net architecture. (Bhattacharya, [0010] “The present architecture, however, builds on the basic U-Net architecture”)
20. The computer-implemented method of claim 9, wherein each of the plurality of images was at least one of: (i) captured at a different time instance; (Bhattarcharya, [0090] “The light may be scanned, typically with a scanner 107 between the output of the optical fiber 105 and the sample 110, so that the beam of light (dashed line 108) is scanned laterally (in x and y) over the region of the sample to be imaged.” Bhattacharya’s scanning teaches the claimed different time instances.)
(ii) capturing using a different modality; or
(iii) captured at a different angle. (Bhattarcharya, Fig. 8. Because photos are taken from a point, and each patch is in a slightly different position than the other patches, each of the image patches is a slightly different angle than the others)
Claims 8, 17, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over US20220058803A1 (“Bhattacharya”) in view of US20220044406A1 (Spizhevoy”) further in view of US20180028355A1 (“Raksi”).
8. Bhattacharya and Spizhevoy teach the ophthalmic system of claim 1, but is not relied on for the below claim language.
However, Raksi teaches wherein the processor is further configured to execute the executable instructions to generate an image overlay comprising the at least one transformed image of the plurality of images and one or more non-transformed images of the plurality of images. (Raksi, [0043] “For example, image capture system 108 may comprise a processor configured to execute feature detection and/or eye tracking algorithms to identify features of eye 101 within an image and, based on an analysis of image data, generate visual indicator overlays for display to a surgeon via display system 100.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply the teachings of Raksi to the teachings of the combination of Bhattacharya and Spizhevoy such that Bhattacharya’s OCT is used with Raksi’s OCT for the purpose of performing ophthalmic surgery. Raksi, abstract.
Based on the above, this is an example of “combining prior art elements according to known methods to yield predictable results.” MPEP 2143.
Claim 17 is rejected as per claim 8.
19. Bhattacharya teaches the computer-implemented method of claim 9, but is not relied on for the below claim language.
However, Raksi teaches wherein the plurality of images further comprises (i) a first set of images captured with a first imaging sensor of a stereo camera and (Raksi, [0038] “In certain embodiments, surgical microscope 102 comprises a high resolution, high contrast stereo viewing surgical microscope. One example of a surgical microscope 102 is the LuxOR™ LX3 with Q-VUE™ Ophthalmic Microscope, available from Alcon.” Bhattacharya [0095] teaches the role of the surgical microscope – “For example, the OCT system may be used with a surgical system or surgical microscope system for diagnostic or treatment purposes.”)
(ii) a second set of images captured with a second imaging sensor of the stereo camera. (Raksi, [0038] “In certain embodiments, surgical microscope 102 comprises a high resolution, high contrast stereo viewing surgical microscope. One example of a surgical microscope 102 is the LuxOR™ LX3 with Q-VUE™ Ophthalmic Microscope, available from Alcon.” Bhattacharya [0095] teaches the role of the surgical microscope – “For example, the OCT system may be used with a surgical system or surgical microscope system for diagnostic or treatment purposes.”)
Raksi is combined as per claim 8.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 11298017 B2 – claim 1
US 10878576 B2 – claim 1
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/DAVID ORANGE/
Primary Examiner, Art Unit 2663
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