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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 12/05/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to Preliminary Amendment
The preliminary amendment filed 12/05/2024 have been acknowledged
Claims 1-14 have been cancelled.
Claims 15-28 are new.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
Such claim limitation(s) is/are:
“Obtaining a plurality of consecutive images of the anatomical structure using a device for capturing images that is in movement and that bears a light source, the light source being configured to illuminate the anatomical structure" in claim 1 as well as “means for producing a three-dimensional model of the anatomical structure from the images obtained, means for identifying anatomical sub-structures of the anatomical structure in the images obtained, and means for comparing the three-dimensional shape of the anatomical sub-structures of the obtained images with the models of sub-structures stored in a database.” in claim 27
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f), they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f), applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f).
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 16 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Claim 16 depends on cancelled claim 1. MPEP 608.01(n)(V) states “If the base claim has been canceled, a claim which is directly or indirectly dependent thereon should be rejected as incomplete”
Claim 21 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Claim 21 recites “preferably photometric loss, structure similarity loss as well as depth smoothing.” The use of the term “preferably” creates confusion regarding the actual boundaries of the invention. The use of the term “preferably” leaves it uncertain whether the preferred sub-range or feature is a mandatory requirement of the claim or merely an optional, non-binding preference.
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.
Claim 21 is rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the enablement requirement. The claim contains subject matter which was not described in the specification in such a way as to enable one skilled in the art to which it pertains, or with which it is most nearly connected, to make and/or use the invention. The specification fails to teach a person of ordinary skill in the art how to clearly and adequately make use of the claimed invention without undue experimentation. The specification simply merely recites “shape retention loss” by name without describing its formulation, its input, or implementation. “Shape retention loss” has no indisputably well recognized, standard meaning within the art. The disclosure provides no sufficient guidance for a skilled artisan to implement the claimed modeling process. The only support in for the term “Shape retention loss” is Line 6 on page 4 in the specification.
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 24 and 25 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter as follows. Claim 24 and 25 defines a “computer program” and “computer-readable recording medium” respectively, which embodies functional descriptive material. However, the claim does not define a non-transitory computer-readable medium or memory and is thus non-statutory for that reason (i.e., “examination the pending claims must be interpreted as broadly as their terms reasonably allow). The broadest reasonable interpretation of a claim drawn to a computer readable medium (also called machine readable medium and other such variations) typically covers forms of non-transitory tangible media and transitory propagating signals per se in view of the ordinary and customary meaning of computer readable media, particularly when the specification is silent. See MPEP 2111.01.
When the broadest reasonable interpretation of a claim covers a signal per se, the claim must be rejected under 35 U.S.C. § 101 as covering non-statutory subject matter. See In see Official Gazette Notice 1351 OG212, February 23,2010). That is, the scope of the presently claimed “computer program product ” typically covers forms of non-transitory tangible media and transitory propagating signals per se. The examiner suggests amending the claim to embody the program on a “computer readable medium” and adding the limitation ”non-transitory ” to the claim or equivalent in order to make the claim statutory. Any amendment to the claim should be commensurate with its corresponding disclosure.
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 15, 16, 20 , 22 , 23, 25, 27, 28 are rejected under 35 U.S.C. 103 as being unpatentable over Bérard et al (Bérard “High-Quality Capture of Eyes”.) in view of Medioni et al (Medioni hereinafter US 20070183653 A1)
As per claim 15
Bérard teaches A method for modeling an anatomical structure of the human body in three dimensions that is computer-implemented (Figure 1, Figure 2, Figure 12, Figure 13, Figure 17) said method comprising the following steps: obtaining a plurality of consecutive images of the anatomical structure (4.3 Image acquisition “ we acquire a series of images that contain a variety of eye poses,” ) using a device for capturing images … (4.2 Capture Setup: “To get the best coverage in the space available, we place six cam eras (Canon 650D)…” DSLR cameras have an internal reflex mirror that physically flips up and a shutter mechanism that opens and closes every time you take a picture. ) that bears a light source (Figure 4, Capture Setup: “The main flash light consist of three elements: a conventional flash (Canon 600EX-RT), a cardboard aperture mask and a lens. This assembly allows us to intensify and control the shape of the light”) the light source being configured to illuminate the anatomical structure (Figure 1, Figure 4 “color LEDs (4) that produce highlights on the cornea.”) identifying anatomical sub-structures of the anatomical structure in the obtained images (Figure 3, Figure 6 5.1 Image Segmentation “As indicated in Section 3, the individual components of the eye re quire dedicated treatment, and thus the first step is to segment the input images to identify skin, sclera, iris, and pupil regions.”) carrying out three-dimensional modeling of the anatomical structure based on the obtained images (Figure 3) comparing the three-dimensional shape of the anatomical sub-structures of the obtained images with models of anatomical sub-structures stored in a database (Figure 18, Figure 20 “We show a comparison with Francois et al. [2009] on the left. They employ a generic eyeball model combined with a heuristic to synthesize the iris morphology. Note how our results shown on the right faithfully capture the intricacies of this particular eye, such as its asymmetric shape, the small surface variation, and the non-circular iris-sclera transition”) wherein the step of carrying out three-dimensional modeling of the anatomical structure is based on the obtained images comprising predicting the depth of the anatomical structure (Figure 9, section 6.1 Theory; “This creates a surface normal field defined by all possible viewing ray direction and depth combinations. A similar surface normal field is produced from refractions (Figure 9a, red)…. The reflection and refraction surface normal fields of different views only coincide at the position of the actual surface as illustrated in Figure 9b. We use this property to reconstruct the cornea” This shows a trend created from the correlation of depth and ray direction is manipulated to reconstruct the cornea. 5.1 Image Segmentation: “We therefore employ a nearest-neighbor classification. We manually segment one of the images into skin, sclera, iris and pupil regions (Figure 6a).” Segmentation of anatomical parts through machine learning automation are widely considered a prediction through model inference)
Bérard does not teach predicting the movement of the image-capturing device being used to carry out the three dimensional modeling of the anatomical structure. Bérard's also does not establish that his capture devices are in movement.
Medioni teaches predicting the movement of the image-capturing device (Figure 1 Paragraph [0032] “As described above, the multiple images are first analyzed at 100 to determine an initial estimate of camera pose among the images. This initial estimate uses information indicative of a face, e.g. prior face knowledge or a generic face, to carry out the estimate.” Medioni Camera’s pose is critical in the 3D reconstruction. ) Medioni also teaches A method for modeling an anatomical structure of the human body in three dimensions that is computer-implemented (Figure 1) as well as using a device for capturing images that is in movement (Paragraph [0031] “In an embodiment, the process assumes that the head is static and that the camera is moving or moved with respect to the head. “)
Accordingly, a person of ordinary skill in the art at the time this invention was effectively filed would have found it obvious to modify Bérard's methodology with Medioni’s concept of using the prediction of the movement of the image capturing device. A person of ordinary skill in the art would have been motivated to incorporate the moving camera acquisition and camera to pose estimation of Medioni into Bérard's anatomical eye capture system in order to accurately register eye images acquired from different viewpoints and determine relative movement of the image capturing device. This would improve recovery of the depth and geometric correspondence across images. Thereby improving the accuracy and completeness of Bérard's reconstructed 3D eye structure. Bérard already employs a sophisticated image acquisition system using synchronized high speed cameras and controlled capture timing. A person of ordinary skill in the art would therefore have recognized that incorporating the known moving camera pose estimation of Medioni’s into Bérard's image acquisition pipeline would have been a straightforward enhancement to improve multi view registration and three dimensional reconstruction.
As per claim 16
Bérard and Medioni teach all claim limitations previously rejected in claim 15’s 1023 rejection. See claim 15’s 103 rejection.
Medioni teaches wherein the step of obtaining a plurality of consecutive images of the anatomical structure comprises recording a video followed by cutting this video into a plurality of consecutive images. (Paragraph [0017] “large amounts of data can be obtained from a single camera that operates to obtain multiple images. For example, this may use frames of video which collectively form a moving sequence of images. “ Paragraph [0020] “extracts information from a sequence of images, e.g. a video sequence, a sequence of stop motion style images from the video sequence” Examiner interprets this disclosure as describing a process of video segmentation and or -frame extraction, where a continuous stream is deconstructed into smaller components to manage large amounts of data.)
As per claim 20
Bérard and Medioni teach all claim limitations previously rejected in claim 15’s 103 rejection. See claim 15’s 103 rejection.
Bérard's teaches wherein the step of performing a three- dimensional modeling of the anatomical structure from the images is a modeling of the identified anatomical sub-structures. (FIGURE 6, Figure 7, Figure 11, Figure 12, Figure 14, Figure 15, Figure 13, )
As per claim 22
Bérard and Medioni teach all claim limitations previously rejected in claim 15’s 103 rejection. See claim 15’s 103 rejection.
Bérard teaches the method being a three-dimensional eye modeling method (Figure 3, Figure 5 and Figure 13)
As per claim 23
Bérard and Medioni teach all claim limitations previously rejected in claim 22’s 103 rejection. See claim 22’s 103 rejection.
Bérard teaches The modeling method according to claim 22, wherein the anatomical sub-structures are the cornea and the sclera. (Figure 5, Cornea 3D reconstruction disclosed in entirety of section 6 Sclera 3D reconstruction disclosed in entirety of section 5. )
As per claim 25
Bérard and Medioni teach all claim limitations previously rejected in claim 15’s 103 rejection. See claim 15’s 103 rejection.
Medioni teaches A computer-readable recording medium comprising instructions which, when executed by a computer, cause the latter to implement the steps of the method according to claim 15. (Paragraph [0063] “ The programs may be resident on a storage medium, e.g., magnetic or optical, e.g. the computer hard drive, a removable disk or media such as a memory stick or SD media, or other removable medium”)
As per claim 27
Bérard and Medioni teach all claim limitations previously rejected in claim 15’s 103 rejection. See claim 13’s 103 rejection.
Claim 27 is the device claim that parallels claim 15 and will be rejected under the same premise.
As per claim 28
Bérard and Medioni teach all claim limitations previously rejected in claim 27’s 103 rejection. See claim 27’s 103 rejection.
Medioni teaches wherein the image-capturing device is formed by a camera configured to record video (Paragraph [0019] “The computer receives raw or processed image data from one or more cameras 215, e.g. still cameras or video cameras. “)
Claim 17, 18, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Bérard et al ( Bérard “High-Quality Capture of Eyes”.) in view of Medioni et al (Medioni hereinafter US 20070183653 A1) in further view of Li et al (Li hereinafter US 20210287430 A1)
As per claim 17
Bérard and Medioni teach all claim limitations previously rejected in claim 15’ s 103 rejection. See claim 15’s 103 rejection.
Bérard nor Medioni the modeling method being a self- supervised method.
Li teaches the modeling method being a self- supervised method (Figure 11, Figure 61 Paragraph [0081] “ self-supervised, single-view 3D reconstruction model to predict, determine, or estimate, a 3D mesh shape, a texture, and a camera pose of a target object after training” Paragraph [0096] “n at least one embodiment, the 3D reconstruction model utilizes self-supervised cross-instance correspondence learning via part segments and/or canonical surface mapping…The 3D reconstruction model, despite having a focus on 3D reconstruction, may also learn 2D to 3D correspondences as well.” Paragraph [0155] “a 3D reconstruction model is utilized to reconstruct 3D shape, texture and camera pose from single-view images, with only a category-specific collection of images and silhouettes as supervision. The self-supervised framework may enforce semantic consistency between the reconstructed meshes and images and may largely reduce ambiguities in the joint prediction of 3D shape and camera pose” Paragraph [0170] “one or more systems depicted in FIG. 30 are utilized in a self-supervised, single-view 3D reconstruction model that predicts the 3D mesh shape, texture, and camera pose of a target object “ Paragraph [0619] “…in at least one embodiment, one or more systems depicted in FIG. 61 are utilized to implement a 3D reconstruction network. In at least one embodiment, one or more systems depicted in FIG. 61 are utilized in a self-supervised, single-view 3D reconstruction model that predicts the 3D mesh shape, texture, and camera pose of a target object with a collection of 2D images and silhouettes.”
Accordingly, a person of ordinary skill in the art would have found it obvious to further modify the Bérard/Medioni methodology with Li’s concept of using a self-supervised method for the 3D anatomical modeling. A person of ordinary skill in the art is aware that the Bérard/Medioni methodology as well as Li’s methodology all service the purpose of reconstructing anatomical structures from media sources. A person of ordinary skill in the art would find it advantageous to substitute the semi supervised model showcased in the image segmentation within the Bérard/Medioni methodology with Li’s supervised model because a person of ordinary skill in the art is aware that unsupervised models removes the need for manual data labeling. They are aware it allows training on a larger unlabeled dataset, and a faster adaptation when ground truth labels are unavailable or biased. A person of ordinary skill in the art is also aware an unsupervised model eliminates human bias and enables flexible discovery where grouping data by features is possible rather than a predefined target class.
As per claim 18
Bérard, Medioni and Li teach all claim limitations previously rejected in claim 17’ s 103 rejection. See claim 17’s 103 rejection.
Bérard teaches comprising a step of feeding an artificial intelligence with sub-structure models stored in a database. (Figure 5, 5.1 Image segmentation: “As indicated in Section 3, the individual components of the eye require dedicated treatment, and thus the first step is to segment the input images to identify skin, sclera, iris, and pupil regions. We acquire approximately 140 images for a single eye dataset, considering all the poses, pupil dilations and multiple cameras, which would make manual segmentation tedious. Therefore, a semi-supervised method is proposed to automate the process… We therefore employ a nearest-neighbor classification. We manually segment one of the images into skin, sclera, iris and pupil regions (Figure 6a). These serve as examples, from which the algorithm labels the pixels of the other images automatically by assigning the label of the most similar example pixel.”)
As per claim 19
Bérard, Medioni and Li teach all claim limitations previously rejected in claim 15’ s 103 rejection. See claim 15’s 103 rejection.
Li teaches the modeling being carried out in real time (Paragraph [0225] “ In at least one embodiment, RISC cores may interact with image sensors (e.g., image sensors of any cameras described herein), image signal processor(s)…RISC cores may execute a real-time operating system (“RTOS”).” Paragraph [0240] “processor(s) 3310 may further include a real-time camera engine that may include, without limitation, a dedicated processor subsystem for handling real-time camera management” Paragraph [0584] “In at least one embodiment, hardware 5922 may include GPUs, CPUs, graphics cards, an AI/deep learning system (e.g., an AI supercomputer, such as NVIDIA's DGX supercomputer system) Paragraph [0603] “… some models may have a real-time (TAT less than one minute) priority …In at least one embodiment, model execution times may be measured from requesting institution or entity and may include partner network traversal time, as well as execution on an inference service.” Paragraph [0615] …though illustrated as consecutive application in deployment pipeline 6010A, CT reconstruction 6108 and organ segmentation 6110 applications may be processed in parallel in at least one embodiment…parallel computing platform 6030 may be used to perform parallel processing for applications to decrease run-time of deployment pipeline 6010A to provide real-time results.” Paragraph [0617] “on-premise installation may allow for high-bandwidth uses (via, for example, higher throughput local communication interfaces, such as RF over Ethernet) for real-time processing. In at least one embodiment, real-time or near real-time processing may be particularly useful where a virtual instrument supports an ultrasound device or other imaging modality where immediate visualizations are expected or required for accurate diagnoses and analyses” Paragraph [00627] “In at least one embodiment, one or more systems depicted in FIGS. 62A-62B are utilized to implement a 3D reconstruction network. In at least one embodiment, one or more systems depicted in FIGS. 62A-62B are utilized in a self-supervised, single-view 3D reconstruction model that predicts the 3D mesh shape, texture,’
Claim 26 is rejected under 35 U.S.C. 103 as being unpatentable over Bérard et al ( Bérard “High-Quality Capture of Eyes”.) in view of Medioni et al (Medioni hereinafter US 20070183653 A1) in further view of Mercut et al (Mercut hereinafter “Three-Dimensional Model of the Human Eye Development based on Computer Tomograph Images”)
As per claim 26
Bérard and Medioni teach all claim limitations previously rejected in claim 15’s 103 rejection. See claim 13’s 103 rejection.
Bérard and Medioni do not teach A method for detecting a pathology resulting from the observation of a structure of the human body comprising: a pathology diagnosis step based on the modeling performed.
Mercut A method for detecting a pathology resulting from the observation of a structure of the human body comprising: a pathology diagnosis step based on the modeling performed. (Introduction:” Developing a virtual 3D eye model was made possible through interdisciplinary collaboration between researchers in various medical and informational fields in order to reach a better understanding of the optical performance of the healthy and diseased eye. Using the same model, pathological, surgical or post-surgical conditions may be analyzed…” Discussion: “Our model allows analyzing various normal, pathological, pre or post-operative conditions.”)
Accordingly, a person of ordinary skill in the art, at the time this invention was effectively filed, would have found it obvious to further modify the Bérard/ Medioni methodology with Mercut’s concept of using the 3D anatomy model to analyze pathology. Bérard teaches acquiring images of the human eye and reconstructing anatomically accurate 3D eye models from those images. Medioni teaches improving 3D anatomical reconstruction by estimating the movement (pose) of the capturing device which enables an accurate reconstruction from a series of image acquisitions. Mercut teaches that a 3D model of the human eye gives better understanding of the optical performance of a healthy and diseased eye and expressly states that the model may be used for analysis of pathological, conditions. A person of ordinary skill in the art would have seen it obvious to use the 3D modeling method of Bérard modified by the prediction of camera movement technique of Medioni to perform a pathology diagnosis/analysis based on the resulting 3D model as suggested by Mercut. The newly modified Bérard /Medioni/Mercut combination gives a more geometrically accurate 3D model that improves the analysis and evaluation of pathological conditions thereby facilitating a more relative pathology diagnosis and clinical assessment.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHANE WRENSFORD CODRINGTON whose telephone number is (571)272-8130. The examiner can normally be reached 8:00am-5pm.
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, Matthew Bella can be reached at (571) 272-7778. 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.
/SHANE WRENSFORD CODRINGTON/Examiner, Art Unit 2667
/MATTHEW C BELLA/Supervisory Patent Examiner, Art Unit 2667
Prosecution Insights