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 .
Response to Amendment
The Amendment filed June 22, 2026 has been entered. Claims 1-2, 4-12 and 14-22 remain pending in the application. Applicant’s amendments to the Claims have overcome each and every objection previously set forth in the Non-Final Office Action mailed February 26, 2026.
Claim Objections
Claim 12 is objected to because of the following informalities:
In claim 12 lines 1-2, “the stereo-image includes a first image portion and a second image portion” is duplicate matter and should be deleted
In claim 12 line 2, “being acquired” should read “is acquired”
In claim 12 line 3, “being acquired” should read “is acquired”
Appropriate correction is required.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-2, 4-5, 9-12, 14, 17-18 and 20-22 are rejected under 35 U.S.C. 103 as being unpatentable over Ramirez Luna et al. (US 2019/0327394 A1) in view of Wacey (US 2020/0084353 A1).
Regarding claim 1, Ramirez Luna discloses a method, comprising: receiving a plurality of stereo images comprising an object (Ramirez Luna paragraph 0014: “The stereoscopic camera is configured to record left and right images of a target surgical site for producing a stream of stereoscopic images of the target surgical site”); determining 3D positions of the object within a reference coordinate system based on the plurality of stereo-images (Ramirez Luna paragraph 0502: “The stereoscopic visualization camera 300 is set to visualize the spheres at the calibration target simultaneously and determine their position through the use of parallax in the stereoscopic image. The processor 4102 and/or the robotic arm controller 4106 records the positions of the spheres in an initial coordinate system, for example, X, Y, and Z with respect to a fiducial in the camera 300 (i.e. "camera space)”); generating a transformation matrix based on the determined 3D positions of the object with respect to a reference position (Ramirez Luna paragraph 0502: “The processor 4102 and/or the robotic arm controller 4106 are configured to perform a coordinate transformation between the camera space and robot space based on the positions of the spheres of the calibration target as recorded by the camera, and as the positions of the robotic arm 506 and/or coupling plate 3304”); and calibrating one or more motion control systems based on the determined transformation matrix (Ramirez Luna paragraph 0496: “The calibration procedure for the robotic arm 506”). However, Ramirez Luna fails to explicitly disclose each stereo image of the plurality of stereo images includes a first image portion and a second image portion, wherein, for each of the plurality of stereo-images, both the first image portion and the second image portion show the object, wherein the first image portion and the second image portion are obtained by a single imaging sensor; determining a first position value for the first image portion and a second position value for the second image portion for each of the plurality of stereo-images; and for each of the plurality of stereo-images, determining a 3D position of the object based on the first and second position values. In the related art of stereo imaging, Wacey discloses each stereo image of the plurality of stereo images includes a first image portion and a second image portion (Wacey FIG. 3, paragraph 0068: “a single frame of video, composed of two side-by-side binocular scenes (first and second frames 400, 430) with the synchronised timestamps are derived from the stereo camera 320”), wherein, for each of the plurality of stereo-images, both the first image portion and the second image portion show the object (Wacey FIG. 3: both of the frames 400, 430 show human 410, 440), wherein the first image portion and the second image portion are obtained by a single imaging sensor (Wacey paragraph 0048: “capture stereo disparity images in a side by side configuration on a single imaging sensor”); determining a first position value for the first image portion (Wacey paragraph 0069: “A first frame (for example, the Left hand Frame) 400 is used to identify the location of a potential candidate moving object that may represent a human intruder 410”) and a second position value for the second image portion for each of the plurality of stereo-images (Wacey paragraph 0058: “a pixel (or plurality of pixels), in one frame 400 is matched against a pixel (or plurality thereof) in a second frame 430”); and for each of the plurality of stereo-images, determining a 3D position of the object (Wacey paragraphs 0041, 0057: “construct three-dimensional volumetric image data from at least one frame of imaging data…determine a depth position of the at least one candidate moving object based on the volumetric image data” where “each pixel now has an X, Y and Z value in volumetric image data 648”) based on the first and second position values (Wacey paragraph 0058: “The distance between the matching pixels is called the disparity and the disparity is assumed to represent the Z depth of the object which created the pixel on the cameras' sensor”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ramirez Luna to incorporate the teachings of Wacey to reduce cost and the complexity with synchronization (Wacey paragraphs 0018, 0021, 0024, 0059-0060).
Regarding claim 2, Ramirez Luna, modified by Wacey, discloses the method of claim 1, further comprising: acquiring the plurality of stereo-images at a fixed distance between the object and the single imaging sensor (Ramirez Luna paragraph 0501: “The processor 4102 and/or the robotic arm controller 4106 move the stereoscopic visualization camera 300 to a start position, which may include a stow position, a reorientation position, or a surgical position. The stereoscopic visualization camera 300 then moves the camera from the start position to a position that approximately visualizes a calibration target located on the stationary base 3404 of the robotic arm 506”).
Regarding claim 4, Ramirez Luna, modified by Wacey, discloses the method of claim 1, wherein generating the transformation matrix comprises: determining a displacement value from the reference position for each of the first image portion and the second image portion for each of the plurality of stereo-images (Wacey paragraph 0057: “The disparity map 648 can provide the depth of each pixel relative to an origin, so that each pixel now has an X, Y and Z value in volumetric image data 648”).
Regarding claim 5, Ramirez Luna, modified by Wacey, discloses the method of claim 4, wherein determining 3D positions comprises template matching (Wacey paragraph 0058: “the sum of the absolute difference between pixel(s) in each frame is calculated to find the best candidate match pixel(s)”).
Regarding claim 9, Ramirez Luna, modified by Wacey, discloses the method of claim 4, wherein determining 3D positions comprises using a corner or edge detection method (Ramirez Luna paragraph 0373: “The example processor 1562 may measure and verify optimal focus by monitoring a signal relating to the focus of one or both of the right and left images...The signal changes as focus changes and may be determined from…an edge detection analysis program”).
Regarding claim 10, Ramirez Luna discloses a method, comprising: receiving a plurality of stereo images comprising an object (Ramirez Luna paragraph 0014: “The stereoscopic camera is configured to record left and right images of a target surgical site for producing a stream of stereoscopic images of the target surgical site”); determining a 3D position of an object within a reference coordinate system based on a stereo-image of the object (Ramirez Luna paragraph 0502: “The stereoscopic visualization camera 300 is set to visualize the spheres at the calibration target simultaneously and determine their position through the use of parallax in the stereoscopic image. The processor 4102 and/or the robotic arm controller 4106 records the positions of the spheres in an initial coordinate system, for example, X, Y, and Z with respect to a fiducial in the camera 300 (i.e. "camera space)”); generating a 3D offset value between the determined 3D position and a reference location of the object (Ramirez Luna paragraph 0502: “The processor 4102 and/or the robotic arm controller 4106 are configured to perform a coordinate transformation between the camera space and robot space based on the positions of the spheres of the calibration target as recorded by the camera, and as the positions of the robotic arm 506 and/or coupling plate 3304”); updating the 3D position using the 3D offset value (Ramirez Luna paragraphs 0507-0508: “The three-dimensional space shown in FIG. 49 is modeled using a sequence of ten homogeneous transformations, which may include matrix multiplications…to calculate position of the frames R1 to R10 to determine the three-dimensional position of the robotic arm 506, the coupling plate 3304, and/or the camera 300”); and positioning the object based on the corrected 3D position (Ramirez Luna paragraph 0506: “the processor 4102 and/or the robotic arm controller 4106 may use the mathematical model to determine, for example, a current position of the robotic arm 506 and/or camera 300, which may be used for calculating how joints are to be rotated based on intended movement provided by an operator”). However, Ramirez Luna fails to explicitly disclose each stereo image of the plurality of stereo images includes a first image portion and a second image portion, wherein, for each of the plurality of stereo-images, both the first image portion and the second image portion show the object, wherein the first image portion and the second image portion are obtained by a single imaging sensor; determining a first position value for the first image portion and a second position value for the second image portion for each of the plurality of stereo-images; and for each of the plurality of stereo-images, determining a 3D position of the object based on the first and second position values. In related art, Wacey discloses each stereo image of the plurality of stereo images includes a first image portion and a second image portion (Wacey FIG. 3, paragraph 0068: “a single frame of video, composed of two side-by-side binocular scenes (first and second frames 400, 430) with the synchronised timestamps are derived from the stereo camera 320”), wherein, for each of the plurality of stereo-images, both the first image portion and the second image portion show the object (Wacey FIG. 3: both of the frames 400, 430 show human 410, 440), wherein the first image portion and the second image portion are obtained by a single imaging sensor (Wacey paragraph 0048: “capture stereo disparity images in a side by side configuration on a single imaging sensor”); determining a first position value for the first image portion (Wacey paragraph 0069: “A first frame (for example, the Left hand Frame) 400 is used to identify the location of a potential candidate moving object that may represent a human intruder 410”) and a second position value for the second image portion for each of the plurality of stereo-images (Wacey paragraph 0058: “a pixel (or plurality of pixels), in one frame 400 is matched against a pixel (or plurality thereof) in a second frame 430”); and for each of the plurality of stereo-images, determining a 3D position of the object (Wacey paragraphs 0041, 0057: “construct three-dimensional volumetric image data from at least one frame of imaging data…determine a depth position of the at least one candidate moving object based on the volumetric image data” where “each pixel now has an X, Y and Z value in volumetric image data 648”) based on the first and second position values (Wacey paragraph 0058: “The distance between the matching pixels is called the disparity and the disparity is assumed to represent the Z depth of the object which created the pixel on the cameras' sensor”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ramirez Luna to incorporate the teachings of Wacey to reduce cost and the complexity with synchronization (Wacey paragraphs 0018, 0021, 0024, 0059-0060).
Regarding claim 11, Ramirez Luna, modified by Wacey, discloses the method of claim 10, wherein the 3D offset value is obtained by: determining a plurality of 3D positions of the object within the reference coordinate system based on analysis of a plurality of stereo-images comprising the object (Ramirez Luna paragraph 0502: “The stereoscopic visualization camera 300 is set to visualize the spheres at the calibration target simultaneously and determine their position through the use of parallax in the stereoscopic image. The processor 4102 and/or the robotic arm controller 4106 records the positions of the spheres in an initial coordinate system, for example, X, Y, and Z with respect to a fiducial in the camera 300 (i.e. "camera space)”); generating a transformation matrix based on the determined 3D positions of the object with respect to a reference position (Ramirez Luna paragraph 0502: “The processor 4102 and/or the robotic arm controller 4106 are configured to perform a coordinate transformation between the camera space and robot space based on the positions of the spheres of the calibration target as recorded by the camera, and as the positions of the robotic arm 506 and/or coupling plate 3304”); and determining the 3D offset value in accordance with the transformation matrix (Ramirez Luna paragraphs 0507-0508: “The three-dimensional space shown in FIG. 49 is modeled using a sequence of ten homogeneous transformations, which may include matrix multiplications…to calculate position of the frames R1 to R10 to determine the three-dimensional position of the robotic arm 506, the coupling plate 3304, and/or the camera 300”).
Regarding claim 12, Ramirez Luna, modified by Wacey, discloses the method of claim 10, wherein the first image portion is acquired via a first light beam and the second image portion is acquired via a second light beam (Wacey FIG. 1; paragraphs 0020, 0022: “first and second light beams respectively entering the first and second apertures are reflected by…first and second mirrors for respectively reflecting the first and second light beams onto a third mirror that reflects the first and second light beams side by side to form the composite image”).
Regarding claim 14, Ramirez Luna, modified by Wacey, discloses the method of claim 10, wherein determining the 3D offset value comprises: determining a displacement value based on a difference between the first position value and the second position value and respective values of the reference location of the object (Wacey paragraph 0057: “The disparity map 648 can provide the depth of each pixel relative to an origin, so that each pixel now has an X, Y and Z value in volumetric image data 648”).
Regarding claim 17, Ramirez Luna, modified by Wacey, discloses the method of claim 14, wherein the displacement value for each of the first image portion and the second image portion is determined by: using a corner or edge detection method (Ramirez Luna paragraph 0373: “The example processor 1562 may measure and verify optimal focus by monitoring a signal relating to the focus of one or both of the right and left images...The signal changes as focus changes and may be determined from…an edge detection analysis program”).
Regarding claim 18, Ramirez Luna, modified by Wacey, discloses the method of claim 11, wherein determining the transformation matrix comprises: determining a set of calibration displacement values from the reference position for the plurality of stereo-images (Ramirez Luna paragraph 0502: “The processor 4102 and/or the robotic arm controller 4106 are configured to perform a coordinate transformation between the camera space and robot space based on the positions of the spheres of the calibration target as recorded by the camera, and as the positions of the robotic arm 506 and/or coupling plate 3304”).
Regarding claim 20, Ramirez Luna, modified by Wacey, discloses the method of claim 11, further comprising: acquiring one or a plurality of stereo-images comprising the object at a fixed distance between the object and the single imaging sensor (Ramirez Luna paragraph 0501: “The processor 4102 and/or the robotic arm controller 4106 move the stereoscopic visualization camera 300 to a start position, which may include a stow position, a reorientation position, or a surgical position. The stereoscopic visualization camera 300 then moves the camera from the start position to a position that approximately visualizes a calibration target located on the stationary base 3404 of the robotic arm 506”).
Regarding claim 21, Ramirez Luna, modified by Wacey, discloses the method of claim 1, wherein the single image sensor is configured to obtain the first image portion and the second image portion simultaneously (Wacey paragraph 0049: “capture side by side images on a single sensor 80 so that these images are automatically synchronised”).
Regarding claim 22, Ramirez Luna, modified by Wacey, discloses the method of claim 10, wherein the single image sensor is configured to obtain the first image portion and the second image portion simultaneously (Wacey paragraph 0049: “capture side by side images on a single sensor 80 so that these images are automatically synchronised”).
Claim(s) 6-7 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Ramirez Luna and Wacey in view of Matta et al. (US 2019/0367012 A1).
Regarding claim 6, Ramirez Luna, modified by Wacey, discloses the method of claim 5. However, Ramirez Luna and Wacey fail to explicitly disclose the template matching is performed via a pre-annotated template. In the related art of template matching, Matta discloses the template matching is performed via a pre-annotated template (Matta paragraphs 0045-0047, 0059: “template matching is performed on this binary image using a template image” where the template is pre-annotated with corners based on its shape, e.g., T-shaped, Z-shaped, L-shaped, etc.). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ramirez Luna and Wacey to incorporate the teachings of Matta to ensure matches are detected with desired accuracy and prevent false detection (Matta paragraphs 0046, 0050).
Regarding claim 7, Ramirez Luna, modified by Wacey and Matta, discloses the method of claim 6, wherein the pre-annotated template comprises at least two corners of the template pre-annotated for determining a center position of the object in each of the first image portion and the second image portion that is being matched with the pre-annotated template (Matta paragraph 0048: “At 409, the process finds the center of the marker for which the coordinates of the template region and corners obtained from template matching and Harris detection respectively are used. As shown in FIG. 3(d), four points surrounding the center are obtained by mathematical operation on the dimensions of the template region window to define a square-shaped search window for the center. The corner coordinates output from Harris detection are iterated over, to find the coordinate that lies in this search window and the point obtained is the center of the marker”).
Regarding claim 15, Ramirez Luna, modified by Wacey, discloses the method of claim 14, wherein the displacement value for each of the first image portion and the second image portion is determined by template matching (Wacey paragraph 0058: “the sum of the absolute difference between pixel(s) in each frame is calculated to find the best candidate match pixel(s)”). However, Ramirez Luna and Wacey fail to explicitly disclose the template matching is performed via pre-annotated template comprising at least two corners of the template pre-annotated for determining a center position of the object that is being matched with the pre-annotated template. In related art, Matta discloses the template matching is performed via pre-annotated template (Matta paragraphs 0045-0047, 0059: “template matching is performed on this binary image using a template image” where the template is pre-annotated with corners based on its shape, e.g., T-shaped, Z-shaped, L-shaped, etc.) comprising at least two corners of the template pre-annotated for determining a center position of the object that is being matched with the pre-annotated template (Matta paragraph 0048: “At 409, the process finds the center of the marker for which the coordinates of the template region and corners obtained from template matching and Harris detection respectively are used. As shown in FIG. 3(d), four points surrounding the center are obtained by mathematical operation on the dimensions of the template region window to define a square-shaped search window for the center. The corner coordinates output from Harris detection are iterated over, to find the coordinate that lies in this search window and the point obtained is the center of the marker”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ramirez Luna and Wacey to incorporate the teachings of Matta to ensure matches are detected with desired accuracy and prevent false detection (Matta paragraphs 0046, 0050).
Claim(s) 8, 16 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Ramirez Luna and Wacey in view of Qiu (US 2021/0034911 A1).
Regarding claim 8, Ramirez Luna, modified by Wacey, discloses the method of claim 4, wherein the displacement value for each of the first image portion and the second image portion is determined by: matching an area of interest (AOI) in each of the first image portion and the second image portion (Wacey paragraph 0058: “a pixel (or plurality of pixels), in one frame 400 is matched against a pixel (or plurality thereof) in a second frame 430”); determining a center position for each of the first image portion and the second image portion upon matching the AOIs of the first image portion and the second image portion (Wacey paragraph 0085: “determine a centroid for each labeled moving object in the labeled object data 644”); and calculating the displacement value by determining a difference between the center position and the reference position of the object in each of the first image portion and the second image portion (Wacey paragraphs 0057, 0069: “The disparity map 648 can provide the depth of each pixel relative to an origin, so that each pixel now has an X, Y and Z value in volumetric image data 648…identify the location of a potential candidate moving object that may represent a human intruder 410”). However, Ramirez Luna and Wacey fail to explicitly disclose using a fast Fourier transform (FFT) template method to match the area of interest (AOI) with a mask template of the object. In the related art of template matching, Qiu discloses using a fast Fourier transform (FFT) template method to match the area of interest (AOI) with a mask template of the object (Qiu paragraph 0009: “image data for the template image and multi-directional image searching area within the source image may be transformed from the 2-dimensional (2D) domain to 1D representations using…fast Fourier transform (FFT)…Searching for the template image may thus be performed in the searching area along the multiple (e.g., vertical and horizontal) directions of the multi-directional searching pattern by correlating the appropriate 1D representations of the template image and the searching area within the source image”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ramirez Luna and Wacey to incorporate the teachings of Qiu to facilitate highly efficient searching within the source image (Qiu paragraph 0009).
Regarding claim 16, Ramirez Luna, modified by Wacey, discloses the method of claim 14, wherein the displacement value for each of the first image portion and the second image portion is determined by: matching an area of interest (AOI) in each of the first image portion and the second image portion (Wacey paragraph 0058: “a pixel (or plurality of pixels), in one frame 400 is matched against a pixel (or plurality thereof) in a second frame 430”); determining a center position for each of the first image portion and the second image (Wacey paragraph 0085: “determine a centroid for each labeled moving object in the labeled object data 644”); and calculating the displacement value by determining a difference between the center position and the reference position of the object in each of the first image portion and the second image portion (Wacey paragraphs 0057, 0069: “The disparity map 648 can provide the depth of each pixel relative to an origin, so that each pixel now has an X, Y and Z value in volumetric image data 648…identify the location of a potential candidate moving object that may represent a human intruder 410”). However, Ramirez Luna and Wacey fail to explicitly disclose using a fast Fourier transform (FFT) template method to match the area of interest (AOI) with a mask template of the object. In related art, Qiu discloses using a fast Fourier transform (FFT) template method to match the area of interest (AOI) with a mask template of the object (Qiu paragraph 0009: “image data for the template image and multi-directional image searching area within the source image may be transformed from the 2-dimensional (2D) domain to 1D representations using…fast Fourier transform (FFT)…Searching for the template image may thus be performed in the searching area along the multiple (e.g., vertical and horizontal) directions of the multi-directional searching pattern by correlating the appropriate 1D representations of the template image and the searching area within the source image”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ramirez Luna and Wacey to incorporate the teachings of Qiu to facilitate highly efficient searching within the source image (Qiu paragraph 0009).
Regarding claim 19, Ramirez Luna, modified by Wacey, discloses the method of claim 18, wherein the set of calibration displacement values are determined by: matching an area of interest (AOI) in each of the plurality of stereo-images (Wacey paragraph 0058: “a pixel (or plurality of pixels), in one frame 400 is matched against a pixel (or plurality thereof) in a second frame 430”); determining a center position for each of the plurality of stereo-images (Wacey paragraph 0085: “determine a centroid for each labeled moving object in the labeled object data 644”); and calculating the set of calibration displacement values by determining a difference between the center position for each of the plurality of stereo-images and the reference position (Wacey paragraphs 0057, 0069: “The disparity map 648 can provide the depth of each pixel relative to an origin, so that each pixel now has an X, Y and Z value in volumetric image data 648…identify the location of a potential candidate moving object that may represent a human intruder 410”) utilizing a corner or edge detection method (Ramirez Luna paragraph 0373: “The example processor 1562 may measure and verify optimal focus by monitoring a signal relating to the focus of one or both of the right and left images...The signal changes as focus changes and may be determined from…an edge detection analysis program”). However, Ramirez Luna and Wacey fail to explicitly disclose using a fast Fourier transform (FFT) template method to match the area of interest (AOI) with a mask template of the object. In related art, Qiu discloses using a fast Fourier transform (FFT) template method to match the area of interest (AOI) with a mask template of the object (Qiu paragraph 0009: “image data for the template image and multi-directional image searching area within the source image may be transformed from the 2-dimensional (2D) domain to 1D representations using…fast Fourier transform (FFT)…Searching for the template image may thus be performed in the searching area along the multiple (e.g., vertical and horizontal) directions of the multi-directional searching pattern by correlating the appropriate 1D representations of the template image and the searching area within the source image”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ramirez Luna and Wacey to incorporate the teachings of Qiu to facilitate highly efficient searching within the source image (Qiu paragraph 0009).
Response to Arguments
Applicant’s arguments with respect to independent claim(s) 1 and 10 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
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/C.Z./ Examiner, Art Unit 2677
/ANDREW W BEE/ Supervisory Patent Examiner, Art Unit 2677
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