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 .
Response to Amendment
This communication is in response to the action filed on 06/09/2026.
Claims 1-10, and 12-20 are currently amended. Claim 11 is canceled. Claims 1-10, and 12-20 are pending.
Response to Arguments
Applicant’s arguments filed on 06/09/2026 on pages 9-19, under REMARKS with respect to 35 U.S.C. 112(f) claim interpretations to claims 1-20 have been fully considered and are persuasive. The means plus function interpretations to the claims have been withdrawn.
Applicant’s arguments filed on 06/09/2026 on pages 9-19, under REMARKS with respect to 35 U.S.C. 101 claim rejections to claims 1-20 have been fully considered and are persuasive. The rejections to the claims have been withdrawn.
Applicant’s arguments filed on 06/09/2026 on pages 9-19, under REMARKS with respect to 35 U.S.C. 102 and 35 U.S.C. 103 have been fully considered but they are not persuasive. Regarding claim 1 applicants on page 17 states that:
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The examiner respectfully disagrees. The examiner would like to point to primary reference of record US 2020/0360312 A1 to HALL et al (hereinafter “HALL”), specifically sections figs 8A-8B; paragraphs [0203-0207], [0233-0236]; TABLE 4 which clearly discuss a feature given a feature value the image feature being tissue density of the breast tissue imaged using a medical imaging modality, and the density value is used for classification of the medical images. This clearly shows the acquired image feature finding being used as a way to determine the classification of the image as healthy tissue or unhealthy tissue among other classification types provided via the system which clearly constitutes an image processing condition used to observe the image finding which in this case is the density value. Further HALL at sections fig 1, element 500 and paragraph [0036] discusses the storage of produced/output data and images including the calculated/determined density values in a memory component containing a database configured to store data, programs, and instructions related to the image processing method/operation performed, and further includes a display 120 to display output data/images 400, which clearly comprises a display image having display conditions. Please see full rejections to the claims below.
Claim Objections
Claim 7 is objected to because of the following informalities: Claim 7 fails to end with a period, it is requested the applicant add a period to the end of the claim. Appropriate correction is required.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-7, 10-11, and 13-21 are rejected under 35 § U.S.C. 102(a)(1) as being anticipated by US 2020/0360312 A1 to HALL et al (hereinafter “HALL”).
As per claim 1, HALL discloses an image processing apparatus comprising: a memory storing instructions, and at least one processor configured to execute the instructions to (a computing system and corresponding method of operation to perform an image processing operation on a medical image(s) and performing medical diagnosis based on the images, where the computing system comprises computer components such as a memory and a processor to store and execute programs/instructions related to the image processing operations/method; abstract; figs 1-3; paragraphs [0036-0038]): acquire a medical image being a diagnosis target (the computing system adapted to receive a plurality of breast images and image metadata from an image acquisition unit 210 such as a mammography system, an x-ray system, an MRI and the like, or from an image storage unit or device 220, directly or using a network interface; abstract; figs 1-3; paragraph [0036]); acquire an image feature amount of the medical image by performing a feature extraction processing on the medical image (the computing system is adapted to perform a feature extraction procedure by determining the density feature value for the breast tissue of the medical image input into the system this breast tissue density value is used to classify the tissue; figs 8A-8B; paragraphs [0203-0207], [0233-0236]; TABLE 4); a plurality of imaging findings by using the feature amount of the medical image (the breast mammograms are classified in four different classes class A-D and the classes are determined by breast density from the mammogram image, and other related features; figs 1-3; paragraphs [0003], [0016-0018], [0108-0111], [0145], [0177-0180]); select at least one imaging finding from the plurality of imaging findings (the finding/image feature that is focused on in analysis of the mammogram images is breast density of the images, and is directly tied to breast cancer diagnosis and health monitoring and is carried out by an FDA approved density measurement device such as but not limited to a VuComp M-Vu tool acting as the finding selection tool and the findings can be sorted viewed and interacted with over a user interface provided by the computing system using a display and input tools; figs 1-3; paragraphs [0157], [0164], [0188],[0191]); determine, for the selected at least one imaging finding, an image processing condition suitable for observation of the selected imaging finding by referring to a database that is storing a correspondence between display conditions and an imaging findings (the computing system includes digital processor 100 which acts as a determining unit to make a plurality of determinations including calculating a breast compression score (image processing condition used for classification) directly related to the found density measurements and would be used to classify the breast images by density into the four discloses classes A, B, C, or D; figs 1, 3, 8A-B; paragraphs [0003], [0036], [0078], [0101], [0104-0112], [0255-0259]); and acquire a display image by subjecting the medical image data to image processing based on the determined image processing condition suitable for observation of the selected at least one imaging finding (the computing system includes a camera/or an image acquisition device database and the digital processing device includes a display to send visual information to a user and would be used to display the aligned breast images and used to determine density and classifications based on said density/compression score; figs 1-3; paragraphs [0020], [0027], [0078], [0162-0164], [0173]).
As per claim 2, HALL discloses the image processing apparatus according to claim 1, wherein the at least one processor is further configured to acquire an imaging finding obtained through inference performed on the medical image (the computing system is adapted to perform analysis (which is synonyms with inference) in order to use a compression score algorithm to determine data on breast image density in order to sort the image after alignment into corresponding breast density classes in order to perform further processing to determine breast cancer disease presence and periodic monitoring of disease progression based on the processed medical images; paragraphs [0138-0140]).
As per claim 3, HALL discloses the image processing apparatus according to claim 1, wherein the at least one processor is further configured to select the at least one imaging finding based on a likelihood of an imaging finding inferred by using the feature amount of the medical image (the diagnostic output comprises a change in the breast density in a subject the prognostic (diagnostic) output comprises a likelihood of recurrence of the breast cancer (findings based on found image feature of breast density which is the feature calculated and receives a value and a classification based on said feature value) in the subject or designation of the subject as a responder or a non-responder to therapy such as to neo-adjuvant or adjuvant therapy comprising of chemotherapy or endocrine therapy; paragraph [0144]).
As per claim 4, HALL discloses the image processing apparatus according to claim 3, wherein the at least one processor is further configured to convert the image feature amount of the medical image being the diagnosis target into the plurality of imaging findings having the likelihood assigned thereto (the diagnostic output comprises a change in the breast density in a subject the prognostic (diagnostic) output comprises a likelihood of recurrence of the breast cancer (plurality of findings based on found image feature of breast density classification) in the subject or designation of the subject as a responder or a non-responder to therapy such as to neo-adjuvant or adjuvant therapy comprising of chemotherapy or endocrine therapy and would assign the likelihood based on the classification results of the aligned images being classified based on breast density wherein classes C and D are stated to be indicators of breast disease BIRADS; paragraphs [0104-0109], [0144]).
As per claim 5, HALL discloses the image processing apparatus according to claim 1, wherein the at least one processor is further configured to: acquire an influence degree on diagnosis of an imaging finding, and select the at least one imaging finding by using the acquired influence degree (the computing system comprising the processing unit 100 is adapted to perform he function of accounting for influence factors on breast density scores such as BMI this is accounted for in the compression determination algorithm as the input BMI value will influence the resulting density value used for classification based on the compression score which is stated to be directly influence/correlated to BMI values; paragraphs [0183], [0236-0239], [0249]).
As per claim 6, HALL discloses the image processing apparatus according to claim 5, wherein the at least one processor is further configured to; infer a diagnosis name by using an imaging finding as input (the computing system comprises a processing unit 100 configured to determine diagnose and predict breast cancer severity and progression of the disease and is further adapted to diagnose breast disease such as cancers and BIRADS based on input images and image feature information related to density of the breast imaged via mammogram methods; abstract; paragraphs [0030-0031], [0085] [0108]; claims 23-24), and acquire, as the influence degree on the diagnosis, an influence degree of the imaging finding on the inferred diagnosis name (the BMI influence factor is input to the compression score algorithm and is included in the diagnosis made about the subjects breast cancer based on the breast images input into the model/computing system; paragraphs [0183], [0236-0239], [0249]).
As per claim 7, HALL discloses the image processing apparatus according to claim 1, wherein the at least one processor is further configured to: acquire at least one other imaging finding corresponding to a medical image that corresponds to the medical image being the diagnosis target and has a different imaging period from the medical image being the diagnosis target (the breast images are compared and tracked over a plurality of features including density, and compression score and other image features, the images used for comparison are captured at different periodic time points in order to accurately track progression of the disease; figs 8A-B; paragraphs [0020], [0027], [0044]; CLAIMS 15-16), and select the at least one imaging finding based on the plurality of imaging findings and the at least one other imaging finding (the computing system comprising processing unit 100 is adapted to based on the instructions and programs provide use the density values and compression scores to distribute the aligned breast images into 4 classes based on density value of the images; figs 8A-B; paragraphs [0020], [0027], [0044], [0253]; CLAIMS 15-16)
As per claim 10, HALL discloses the image processing apparatus according to claim 1, wherein the at least one processor is further configured to determine the image processing condition based on an item of the selected at least one imaging finding and a value of the selected at least one imaging finding (the computing system is adapted to classify the images based on the resulting density values of the breast images; paragraphs [0003], [0021], [0028], [0065], [0075-0078], [0108]; CLAIM 5).
As per claim 13, HALL discloses the image processing apparatus according to claim 1, wherein the at least one processor is further configured to acquire the display image based on the image processing condition from a plurality of images subjected to different types of image processing (a plurality of mammogram images are processed in a plurality of ways and include density values of the breast images used to classify the images for further processing, high density images will further be analyzed for breast cancer and low density images may be determined to be background images and not further processed; figs 1-3; paragraphs [0003], [0016-0018], [0108-0111], [0145], [0177-0180]).
As per claim 14, HALL discloses the image processing apparatus according to claim 1, wherein the at least one processor is further configured to cause a display to display the medical image being the diagnosis target (the computing system includes a display keyboards, mouse and controls for viewing and interacting with the user interface in order to view results and make image comparisons; fig 1; paragraphs [0036], [0178]).
As per claim 15, HALL discloses the image processing apparatus according to claim 14, wherein the at least one processor is further configured to; generate, when the medical image being the diagnosis target is displayed, a partial medical image including a region corresponding to the selected at least one imaging finding from the display image satisfying the determined image processing condition, and cause the display unit to display the partial medical image (the computing system is adapted to display partial regions of images corresponding to regions of interest for diagnostic and out/viewing purposes and may output only a region of the breast image tissue that is relevant to diagnosis; fig 1-2; paragraphs [0036], [0067-0069], [0178]).
As per claim 16, HALL discloses the image processing apparatus according to claim 15, wherein the at least one processor is further configured to cause, when the image processing condition applied to display of the medical image being the diagnosis target is different from the determined image processing condition, the display to display a superimposition image obtained by superimposing the partial medical image onto the medical image being the diagnosis target (the computing system is further adapted to perform the method of superimposing regions oof interest of the breast image in order to output important information to the user of the diagnostic images; fig 1-2; paragraphs [0036], [0067-0069], [0178]).
As per claim 17, HALL discloses the image processing apparatus according to claim 15, wherein the at least one processor is further configured to cause, when the image processing condition applied to display of the medical image being the diagnosis target is different from the determined image processing condition, the display to display the partial medical image so as to be comparable to the medical image being the diagnosis target (the computing system is adapted to via a computer processor and display multiple images of mammogram images used for comparison purposes to show the progression of disease in different images captured a time period part and is further adapted to superimpose regions of interest of both of the images; figs 1-2; paragraphs [0067-0069, [0089], [0108-0112]).
As per claim 18, HALL discloses the image processing apparatus according to claim 1, wherein the at least one processor is further configured to cause, when the image processing condition applied to display of the medical image being the diagnosis target is different from the determined image processing condition, a display to display the display image so as to be comparable to the medical image being the diagnosis target (the computing system is adapted to include a display and a keyboard and mouse to control the user interface provided and via the user interface allowing the user to compare the two breast medical images and their related density information; figs 1-2; paragraphs [0036], [0067-0069, [0089], [0108-0112], [0178]).
As per claim 19, HALL discloses the image processing apparatus according to claim 14, wherein the at least one processor is further configured to cause, when a plurality of imaging findings are selected and image processing conditions are determined for each of the plurality of imaging findings, respectively, the display to display, together with the medical image being the diagnosis target, display images satisfying the plurality of the image processing conditions, respectively, in a switchable manner (the prior mention computer peripheral such as keyboard and mouse would be used to access the computer interface and switch the viewable image on the display in order to perform image comparison steps; figs 1-2; paragraphs [0067-0070], [0075], [0091-0093], [0122-0127], [0164]).
As per claim 20, HALL discloses an image processing method comprising (a computing system and corresponding method of operation to perform an image processing operation on a medical image(s), where the computing system comprises computer components such as a memory and a processor to store and execute programs/instructions related to the image processing operations/method; abstract; figs 1-3; paragraphs [0036-0038]): acquiring a medical image being a diagnosis target (the computing system performing the method of operation adapted to receive a plurality of breast images and image metadata from an image acquisition unit 210 such as a mammography system, an x-ray system, an MRI and the like, or from an image storage unit or device 220, directly or using a network interface; abstract; figs 1-3; paragraph [0036]); acquiring an image feature amount of the medical image by performing a feature extraction processing on the medical image (the computing system is adapted to perform a feature extraction procedure by determining the density feature value for the breast tissue of the medical image input into the system this breast tissue density value is used to classify the tissue; figs 8A-8B; paragraphs [0203-0207], [0233-0236]; TABLE 4); acquiring, a plurality of imaging findings by using the feature amount of the medical image (the computing system adapted to receive a plurality of breast images and image metadata from an image acquisition unit 210 such as a mammography system, an x-ray system, an MRI and the like, or from an image storage unit or device 220, directly or using a network interface; abstract; figs 1-3; paragraph [0036]); selecting at least one imaging finding from the plurality of imaging findings (the finding/image feature that is focused on in analysis of the mammogram images is breast density of the images, and is directly tied to breast cancer diagnosis and health monitoring and is carried out by an FDA approved density measurement device such as but not limited to a VuComp M-Vu tool acting as the finding selection tool and the findings can be sorted viewed and interacted with over a user interface provided by the computing system using a display and input tools; figs 1-3; paragraphs [0157], [0164], [0188],[0191]); determining, for the selected at least one imaging finding, an image processing condition suitable for observation of the selected imaging finding by referring to a database that is storing a correspondence between display conditions and an imaging findings (the computing system includes digital processor 100 which acts as a determining unit to make a plurality of determinations including calculating a breast compression score (image processing condition used for classification) directly related to the found density measurements and would be used to classify the breast images by density into the four discloses classes A, B, C, or D; figs 1, 3, 8A-B; paragraphs [0003], [0036], [0078], [0101], [0104-0112], [0255-0259]); and acquiring a display image by subjecting the medical image data to image processing based on the determined image processing condition suitable for observation of the selected at least one imaging finding (the computing system includes a camera/or an image acquisition device database and the digital processing device includes a display to send visual information to a user and would be used to display the aligned breast images and used to determine density and classifications based on said density/compression score; figs 1-3; paragraphs [0020], [0027], [0078], [0162-0164], [0173]).
As per claim 21, HALL discloses a recording medium for recording a program for executing each of the steps of the image processing method of claim 20 when being executed by a computer (the computing system which runs the operation method includes a computer memory component which stores programs, instructions, and data in order to execute them using a processor and to perform the methods descried; abstract; fig 1; paragraphs [0026], [0164], [0178]).
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or non-obviousness.
Claims 8-9 are rejected under 35 § U.S.C. 103 as being obvious over US 2020/0360312 A1 to HALL et al (hereinafter “HALL”) in view of US 2024/0029251 A1 to ICHINOSE (hereinafter “ICHINOSE”).
As per claim 8, HALL discloses the image processing apparatus according to claim 1. HALL fails to disclose wherein the at least one processor is further configured to; select the at least one imaging finding based on the plurality of imaging findings and another imaging finding obtained based on a medical image corresponding to the medical image being the diagnosis target.
ICHINOSE discloses wherein the at least one processor is further configured to: select the at least one imaging finding based on the plurality of imaging findings and another imaging finding obtained based on a medical image corresponding to the medical image being the diagnosis target (the first analysis unit 42C inputs a partial image of a region including the abnormal shadow in the diagnosis target image to the trained model M3 the trained model M3 outputs findings having a degree of certainty of findings equal to or greater than a predetermined threshold value TH2 such as a certainty value over 0.5 as shown in FIG. 22 an example in which five findings are output from the trained model M3 which includes a first and second finding based on a medical image and the diagnoses target of model M3; fig 22; paragraph [0115]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify HALL to have configured to select the at least one imaging finding based on the first imaging finding group and a second imaging finding of ICHINOSE reference. The Suggestion/motivation for doing so would have been to provide the total amount of findings in the partial image over a user set threshold to ensure all findings of interest are accounted for as suggested by ICHINOSE at paragraph [0115]. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine ICHINOSE with HALL to obtain the invention as specified in claim 8.
As per claim 9, HALL discloses the image processing apparatus according to claim 1. HALL fails to disclose wherein the at least one processor is further configured to: identify an abnormal shadow from the medical image being the diagnosis target, and determine the image processing condition for an imaging finding relating to the abnormal shadow, and acquire an image satisfying the image processing condition and including the abnormal shadow as the display image.
ICHINOSE discloses wherein the at least one processor is further configured to: identify an abnormal shadow from the medical image being the diagnosis target, and determine the image processing condition for an imaging finding relating to the abnormal shadow and acquire an image satisfying the image processing condition and including the abnormal shadow as the display image (the model M3 is adapted to point out finding within a input partial image based on a user defined thresholds wherein the findings are related to abnormal shadows of the partial input image and determines which image to display; fig 22; paragraphs [0115]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify HALL to have an identification unit configured to identify an abnormal shadow from the medical image of ICHINOSE reference. The Suggestion/motivation for doing so would have been to provide the total amount of findings related to abnormal shadows in the partial image over a user set threshold to ensure all findings of interest are accounted for as suggested by ICHINOSE at paragraph [0115]. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine ICHINOSE with HALL to obtain the invention as specified in claim 9.
Claim 12 is rejected under 35 § U.S.C. 103 as being obvious over US 2020/0360312 A1 to HALL et al (hereinafter “HALL”) in view of US 2017/0164830 A1 to HUANG et al. (hereinafter “HUANG”).
As per claim 12, HALL discloses the image processing apparatus according to claim 1. HALL fails to disclose wherein the image processing that is based on the image processing condition is at least one of luminance level changing processing, gradation converting processing, resolution converting processing, or cropping processing.
HUANG discloses wherein the image processing that is based on the image processing condition is at least one of luminance level changing processing, gradation converting processing, resolution converting processing, or cropping processing (the computing system is adapted to perform a plurality of image processing techniques on the input images including, resizing/cropping, generating a new image in a greater resolution in the vicinity of the detected point or with a different imaging mode like by using a different wavelength camera or a different illumination or a camera of a more accurate imaging area; paragraph [0063]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify HALL to have the image processing condition is at least one of luminance level changing processing, gradation converting processing, resolution converting processing, or cropping processing of HUANG reference. The Suggestion/motivation for doing so would have been to provide for a more accurate imaging representation of the region of interest of the medical image by applying known image improvement techniques as suggested by paragraph [0063] of HUANG. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine HUANG with HALL to obtain the invention as specified in claim 12.
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.
Examiner's Note: Examiner has cited figures, and paragraphs in the references as applied to the claims above for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested for the applicant, in preparing the responses, to fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner. Examiner has also cited references in PTO892 but not relied on, which are relevant and pertinent to the applicant’s disclosure, and may also be reading (anticipatory/obvious) on the claims and claimed limitations. Applicant is advised to consider the references in preparing the response/amendments in-order to expedite the prosecution.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DEVIN JACOB DHOOGE whose telephone number is (571) 270-0999. The examiner can normally be reached 7:30-5:00.
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, Andrew Bee can be reached on (571) 270-5183. 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.
/D J DHOOGE/Examiner, Art Unit 2677
/ANDREW W BEE/Supervisory Patent Examiner, Art Unit 2677
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