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 .
Priority
Acknowledgement is made of Applicant’s claim of the present application claiming priority and benefit under 35 U.S.C. 119(e) to Provisional Patent Application No. 63/539,832 filed 09/22/2023.
Information Disclosure Statement
The information disclosure statement (“IDS”) filed on 03/31/2025 has been reviewed and the listed references were noted.
Drawings
The 6-page drawings have been considered and placed on record in the file.
Status of Claims
Claims 1-17 are pending.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-17 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter (an abstract idea without significantly more). The claims recite a method and a system for processing images by identifying regions including one or more villus(s), determining distances, and classifying a disease and the state of the disease. With respect to analysis of independent Claim 1:
Step 1:
With regard to Step 1, the instant claim is directed to an apparatus; and therefore, the claim is directed to one of the statutory categories of inventions.
Step 2A, Prong One:
With regard to 2A Prong One, the limitations of “segmenting the image to identify a region of interest that includes at least a portion of at least one villus; identifying a pathological feature of the image within the region of interest; determine a parameter pertaining to each of at least one instance of the identified pathological feature in the image; determining an aggregate parameter based on the determined parameter”, as drafted, recite an abstract idea, such as the combination of a method, making measurements, and performing calculations that, under their broadest reasonable interpretation, covers the performance of the limitation manually or in the mind of a medical professional. That is, a skilled technician or doctor may separate/segment the image into different regions that include a villus, identify a pathological feature, determine a microvillus length (using image magnification information and unit conversion), and calculate the average microvillus length. This is a concept that falls under the combination of a grouping of abstract ideas of mental processes and mathematical calculations, i.e., a concept performed in the human mind, evaluation, judgement, and/or opinion of a technician/doctor through mathematical calculations and measurements to obtain a report of microvilli length.
Step 2A, Prong Two:
The 2019 PEG defines the phrase “integration into a practical application” to require an additional element or a combination of additional elements in the claim to apply, rely on, or use the judicial exception. In the instant case, the additional elements/limitations in the claims, i.e., “receiving a digitized pathology image of a subject” and “outputting a report of the determined aggregate parameter” are regarded as elements directed to represent insignificant extra-solution activities, such as obtaining medical image data of a subject to perform a medical analysis and outputting a report of the result of that analysis. These limitations are regarded as insignificant extra solution activities of acquiring medical image data, i.e., gathering input information, and outputting information, which may not be considered as an indication of integration of the judicial exception into a practical application. Accordingly, the above-mentioned additional elements/limitations do not integrate the abstract idea into a practical application; and therefore, the claim recites an abstract idea.
Step 2B:
Because the claims fail under Step 2A, the claims are further evaluated under Step 2B. The claims herein do not include additional elements that are sufficient to amount to significantly more than the judicial exception, because as discussed above with respect to integration of the abstract idea into practical application, the additional elements/limitations, amount to no more than insignificant routine and conventional elements. The abstract operation/purpose of the method as listed in Claim 1, cannot provide an inventive concept. Therefore, independent Claim 1 is not patent eligible.
Furthermore, with regard to dependent claims 2-17, viewed individually, these additional elements/limitations, under their broadest reasonable interpretation, are regarded as either providing additional abstract idea (i.e., mathematical calculations or performing the limitations in the mind of a medical technician) or adding limitations that may not be considered as significantly more than the abstract idea; which do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. Accordingly, they are not patent eligible.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
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 nonobviousness.
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.
Claims 1-6 and 9-15 are rejected under 35 U.S.C. 103 as being unpatentable over VanDussen et al. (“Abnormal Small Intestinal Epithelial Microvilli in Patients with Chron’s Disease” - IDS), in view of Wang et al. (“Detection of Glands and Villi by Collaboration of Domain Knowledge and Deep Learning” - IDS).
Regarding claim 1, VanDussen teaches, “A method comprising: receiving a digitized pathology image of a subject;” (VanDussen, Page 5 “Imaging” discloses; “Image acquisition and quantification was performed in a blinded fashion for all histological metrics. Brightfield images were acquired with an Olympus BX51 microscope equipped with UPlanFL 10X/0.30, 20X/0.50, 40X/0.75, and 100X/1.30 Oil Iris objective lenses, an Olympus DP70 or DP22 camera and DP Controller or cellSens Standard v1.17 software. Confocal images were obtained with a Zeiss LSM880 laser scanning confocal microscope equipped with a 63X/1.4 Zeiss Plan Apochromat oil objective lens. TEM images were acquired with a JEOL model 1400EX electron microscope and AMT Advantage HR (Advanced Microscopy Technology) high definition CCD, 11 megapixel TEM camera. “) “(VanDussen, Page 2 “Results” discloses; “One cluster encoded genes associated with the enterocyte brush border, leading us to investigate microvilli.” Examiner interprets microvilli to be a pathological feature.) “determine a parameter pertaining to each of at least one instance of the identified pathological feature in the image;” (VanDussen, Page 7 “Microvilli gene expression and length are reduced in uninflamed Chron’s ileum” discloses; “To determine if the transcriptional alterations in microvilli-associated genes corresponded to histological alteration of microvilli, we performed a quantitative analysis of microvilli length using serial tissue sections adjacent to those used for transcriptional analysis.” Examiner interprets microvilli length to be a parameter.) “determining an aggregate parameter based on the determined parameter;” (VanDussen, Page 7 “Microvilli gene expression and length are reduced in uninflamed Chron’s ileum” discloses; “CD enterocytes had a ~11% decrease in average microvilli length compared to Non-IBD (Figure 4A, B). To support our ability to precisely determine average microvilli length, we performed rigorous statistical validation of our sampling method (Figure S3 and Figure S4) and demonstrated high inter-observer reproducibility (Figure S5).” Examiner interprets average microvilli length to be an aggregate parameter.) “and outputting a report of the determined aggregate parameter.” (VanDussen, Page 10 “Impact of UST on the microvilli gene signature and microvilli length” discloses; “A significant increase in the average microvilli length was also observed in the UST-treated subjects at I-Wk8 compared to baseline (Figure 6B). Patients who received placebo did not show significant alterations in core Cluster 5 gene set enrichment or microvilli length (Figure 6B, C).” Examiner interprets the observed significant increase in the average microvilli length as outputting a report of the aggregate parameter.) VanDussen does not explicitly teach, “segmenting the image to identify a region of interest that includes at least a portion of at least one villus”. Since VanDussen does not explicitly disclose this limitation, Examiner relies on the teachings of Wang in an analogous field of endeavor. Specifically, Wang teaches, “segmenting the image to identify a region of interest that includes at least a portion of at least one villus” (Wang, Page 22, Section 2.1 discloses; “We first obtain a superpixel segmentation [1] (Fig. 2(b)) of the image.” And Wang Page 21 discloses; “In this paper, we propose to combine domain knowledge and deep learning to simultaneously detect glands and villi (since they are closely related) in H&E histology tissue images.” Examiner interprets these disclosures to teach segmenting an image and identifying/detecting a villus.)
VanDussen and Wang are both considered to be analogous to the claimed invention because they are in the same field of processing medical images of a villus region. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified VanDussen to incorporate the teachings of Wang in order to segment the medical image to identify a villus. One of ordinary skill in the art would have been motivated to combine the previously described method of VanDussen with the teachings of Wang to ensure that the image includes a region containing at least a portion of a villus. Accordingly, it would have been obvious to combine VanDussen and Wang to obtain the above specified limitations.
Regarding claim 2, the combination of VanDussen and Wang teaches, “The method according to claim 1, wherein the pathological feature is a microvillus” (VanDussen, Page 2 “Results” discloses; “One cluster encoded genes associated with the enterocyte brush border, leading us to investigate microvilli.” Examiner interprets microvilli to be a pathological feature.)
Regarding claim 3, the combination of VanDussen and Wang teaches, “The method according to claim 1, wherein the pathological feature is a cell nucleus” (VanDussen, Page 18, Figure 3 caption discloses; “Nuclei are visualized with bisbenzimide (blue).” Examiner interprets this disclosure, as well as Figure 3, to teach identifying a cell nucleus in an image.)
Regarding claim 4, the combination of VanDussen and Wang teaches, “The method according to claim 1, wherein the pathological feature is a goblet cell” (VanDussen, Page 8, Para. 1 discloses; “We also examined the proportions of goblet cells and Paneth cells, which have been implicated in CD pathogenesis 32 and are the next most common epithelial subsets in the small intestine.” Examiner interprets this disclosure to teach identifying goblet cells in an image.)
Regarding claim 5, the combination of VanDussen and Wang teaches, “The method according to claim 1, wherein the parameter is a microvillus length” (VanDussen, Page 7 “Microvilli gene expression and length are reduced in uninflamed Chron’s ileum” discloses; “To determine if the transcriptional alterations in microvilli-associated genes corresponded to histological alteration of microvilli, we performed a quantitative analysis of microvilli length using serial tissue sections adjacent to those used for transcriptional analysis.” Examiner interprets microvilli length to be a parameter.)
Regarding claim 6, the combination of VanDussen and Wang teaches, “The method according to claim 1, wherein the identified pathological feature is a villus,” (Wang, Abstract discloses; “we propose to combine deep learning and domain knowledge in a unified framework, to simultaneously detect (the closely related) glands and villi in H&E histology tissue images.”) “wherein identifying at least one pathological feature comprises identifying contours corresponding to inner and outer edges of a brush border of at least one villi in the region of interest,” (Wang, Figure 1 caption discloses; “(a) A 3-D illustration of the dual glands and villi: Villi (top) are evagination of epithelium (green) into lumen (blue), and glands (bottom) are invagination of epithelium into extracellular material (red);” Figure 1A shows contours corresponding to the inner and outer edges of a brush border (green-red border and green-blue border).) “wherein determining the parameter comprises determining a distance between the contours,” (VanDussen, Figure 3 caption discloses; “(A) Representative images of H&E-stained ileal tissue regions used to measure microvilli length. Bars, 10 μm. A magnified view of the boxed region in each image is shown to the right; brackets indicate microvilli length.” Figure 3A shows a distance being measured between 2 contours as the microvilli lengths.) “and wherein the parameter is the distance between the contours.” (VanDussen, Figure 3 caption discloses; “(A) Representative images of H&E-stained ileal tissue regions used to measure microvilli length. Bars, 10 μm. A magnified view of the boxed region in each image is shown to the right; brackets indicate microvilli length.” This microvilli length is considered to be the parameter.) The proposed combination as well as the motivation for combining the VanDussen and Wang references in the rejection of claim 1, apply to claim 6 and are incorporated herein by reference. Thus, the method of claim 6 is met by VanDussen and Wang.
Regarding claim 9, the combination of VanDussen and Wang teaches, “The method according to claim 1, further comprising: classifying or predicting a state or a degree of a disease of the subject based on the aggregate parameter” (VanDussen, Page 11, Para. 2 discloses; “however, the literature supports that reduced microvilli length and stability are also detrimental to human intestinal homeostasis. For example, microvillous inclusion disease (caused by deleterious gene mutations in Myosin 5b (MYO5B) and in Syntaxin 3 (STX3)) presents as patchy loss of microvilli and is associated with persistent diarrhea and failure to thrive 36, 37.” And Wang, Page 20 “Introduction” discloses; “Architecture distortions of glands and villi are strong signs of chronic inflammation [9]. Also, a quantitative measurement of the degree of such distortions may help determine the severity of the chronic inflammation.” Examiner interprets these disclosures to teach that microvilli length (or architecture distortion of villi) is associated with determining severity of a disease. It would have been obvious to combine these disclosures to obtain this limitation.) The proposed combination as well as the motivation for combining the VanDussen and Wang references in the rejection of claim 1, apply to claim 9 and are incorporated herein by reference. Thus, the method of claim 9 is met by VanDussen and Wang.
Regarding claim 10, the combination of VanDussen and Wang teaches, “The method according to claim 1, further comprising: quantifying an intestinal health of the subject based on the aggregate parameter” (VanDussen, Page 11, Para. 2 discloses; “however, the literature supports that reduced microvilli length and stability are also detrimental to human intestinal homeostasis. For example, microvillous inclusion disease (caused by deleterious gene mutations in Myosin 5b (MYO5B) and in Syntaxin 3 (STX3)) presents as patchy loss of microvilli and is associated with persistent diarrhea and failure to thrive 36, 37.” And Wang, Page 20 “Introduction” discloses; “Architecture distortions of glands and villi are strong signs of chronic inflammation [9]. Also, a quantitative measurement of the degree of such distortions may help determine the severity of the chronic inflammation.” Examiner interprets these disclosures to teach that microvilli length (or architecture distortion of villi) can be used as a “quantitative measurement of the degree of such distortions” (or intestinal health). It would have been obvious to combine these disclosures to obtain this limitation.) The proposed combination as well as the motivation for combining the VanDussen and Wang references in the rejection of claim 1, apply to claim 10 and are incorporated herein by reference. Thus, the method of claim 10 is met by VanDussen and Wang.
Regarding claim 11, the combination of VanDussen and Wang teaches, “The method according to claim 1, further comprising: identifying a treatment protocol for the subject based on the aggregate parameter.” (VanDussen, Page 9, Para. 1 discloses; “UST phase 3 studies established that UST, a monoclonal antibody to the p40 subunit of interleukin-12 and interleukin-23, is an effective treatment for moderate-to-severe CD” This disclosure teaches a suggested protocol for a subject. This suggestion came after the reference found that microvilli length is different in subjects with diseases. Therefore, this reference discloses suggesting a treatment based on microvilli length.)
Regarding claim 12, the combination of VanDussen and Wang teaches, “The method according to claim 11, further comprising: treating the subject based on the treatment protocol.” (VanDussen, “We next tested if core Cluster 5 gene set enrichment differed between placebo and UST treated subjects. In subjects who received UST induction therapy, the enrichment score was higher (i.e. more similar to Non-IBD controls) at I-Wk8 compared to I-Wk0 (Figure 6A). A significant increase in the average microvilli length was also observed in the UST-treated subjects at I-Wk8 compared to baseline (Figure 6B). The disclosure teaches treating based on the treatment protocol as described in the rejection of claim 11.)
Regarding claim 13, the combination of VanDussen and Wang teaches, “The method according to claim 1, wherein the outputted report comprises a heatmap of the determined parameter or the determined aggregate parameter overlaid on the digitized image.” (VanDussen, Figure 3A caption discloses; “A magnified view of the boxed region in each image is shown to the right; brackets indicate microvilli length” Figure 3A shows microvilli length (parameter) being overlaid on the digital image.)
Regarding claim 14, the combination of VanDussen and Wang teaches, “The method according to claim 1, further comprising: comparing the determined parameter or the determined aggregate parameter across a plurality of regions of interest or a plurality of digitized images” (VanDussen, Page 18, Figure 3 caption discloses; “(A) Representative images of H&E-stained ileal tissue regions used to measure microvilli length. Bars, 10 μm. A magnified view of the boxed region in each image is shown to the right; brackets indicate microvilli length. (B) Graph of average microvilli length (μm) with the same data displayed side-by-side as scatterplots and as box-and-whisker plots for Non IBD (n=26; blue) and CD (n=34; red) samples.” Figures 3A and 3B show obtaining microvilli lengths from different sections (3A), and then comparing the lengths (3B points).)
Regarding claim 15, the combination of VanDussen and Wang teaches, “The method according to claim 1, wherein the aggregate parameter is determined based on a comparison of the determined parameter across a plurality of the identified pathological features, a plurality of regions of interest, or a plurality of digitized images” VanDussen, Page 18, Figure 3 caption discloses; “(A) Representative images of H&E-stained ileal tissue regions used to measure microvilli length. Bars, 10 μm. A magnified view of the boxed region in each image is shown to the right; brackets indicate microvilli length. (B) Graph of average microvilli length (μm) with the same data displayed side-by-side as scatterplots and as box-and-whisker plots for Non IBD (n=26; blue) and CD (n=34; red) samples.” Figures 3A and 3B show obtaining microvilli lengths from different sections (3A), and then calculating the average length across a plurality of images (3B box-and-whisker plot).)
Claims 7 and 16-17 are rejected under 35 U.S.C. 103 as being unpatentable over VanDussen et al., in view of Wang et al., in further view of Fan et al. (US 2004/0197015 A1).
Regarding claim 7, the combination of VanDussen and Wang teaches, “The method according to claim 1, wherein the identified pathological feature is a villus,” (Wang, Abstract discloses; “we propose to combine deep learning and domain knowledge in a unified framework, to simultaneously detect (the closely related) glands and villi in H&E histology tissue images.”)) “wherein identifying at least one pathological feature comprises: identifying a contour corresponding to an edge of at least one villi in the region of interest;” (Wang, Figure 1 caption discloses; “(a) A 3-D illustration of the dual glands and villi: Villi (top) are evagination of epithelium (green) into lumen (blue), and glands (bottom) are invagination of epithelium into extracellular material (red);” Figure 1A shows contours corresponding to the edge of a villi (green-blue border).)) “and segmenting the contour;” (Wang, Figure 2 caption discloses; “(a) Image samples; (b) superpixel segments;” Figure 2(b) shows segmentation of the image contours.) “wherein determining the parameter comprises, for each contour segment: determining a direction toward an intracellular compartment of an epithelial cell corresponding to the segment;” (Wang, Page 22-23, Section 2.1 (2.a) discloses; “We first find the lumen (LM) and extracellular material (EM) within a distance of d = S(i) × LS from this epithelium superpixel (ES), if any. (2.b) For each class and each scale, we map the ES to some locations, based on the following observation for choosing the mapping/voting direction (which narrows down the voting space to be covered): If the ES is part of a gland, then the gland is likely to lie on the same side as LM, but on the opposite side from EM (found in (2.a) near this ES); if it is actually part of a villus, then due to the “duality” of glands and villi, the villus is likely to lie on the same side as EM, but on the opposite side from LM (see Fig. 2(e)). More specifically, the ES would vote for the points in a circle (of a radius d/4) centered at the (x,y) coordinates, which are of a distance d away from the center of the ES, towards the chosen directions accordingly, for respectively glands and villi, and the 8 scales (see Fig. 2(f)).”) “(VanDussen, Figure 3 caption discloses; “(A) Representative images of H&E-stained ileal tissue regions used to measure microvilli length. Bars, 10 μm. A magnified view of the boxed region in each image is shown to the right; brackets indicate microvilli length.” This microvilli length is considered to be the parameter determined in a different way as disclosed by Fan.) The combination of VanDussen and Wang does not explicitly teach, “determining a distance between the segment and a pixel having a drop in intensity greater than a threshold along a path that extends normal to the segment in the determined direction”. Since the combination of VanDussen and Wang does not explicitly disclose these limitations, Examiner relies on the teachings of Fan in an analogous field of endeavor. Specifically, Fan teaches, “determining a distance between the segment and a pixel having a drop in intensity greater than a threshold along a path that extends normal to the segment in the determined direction” (Fan, Para. [0035] discloses; “Using a region growing algorithm, the intensity of pixels adjacent to the selected pixel or the current region are compared to a threshold. If the pixel intensity is above a threshold, an initial boundary location is identified. If the pixel intensity is below the threshold, the process continues to a next adjacent pixel until an initial boundary is located in a given direction.” It would be obvious to make the criteria for an edge to be below a threshold instead of above. Additionally, it would be obvious to perform this method in the direction disclosed by VanDussen. Fan, Para. [0036] discloses; “Alternatively, curve fitting using all the initial boundary points or identification of the two closest border locations on opposite sides of the region grown border as the minor axes of an ellipse and the distance between two locations”)
VanDussen, Wang, and Fan are considered to be analogous to the claimed invention because they are in the same field of processing medical images. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of VanDussen and Wang to incorporate the teachings of Fan in order to determine the distance between 2 contours in the image. One of ordinary skill in the art would have been motivated to combine the previously described method of VanDussen and Wang with the teachings of Fan to accurately determine the distance by using a pixel intensity threshold. Accordingly, it would have been obvious to combine VanDussen, Wang, and Fan to obtain the above specified limitations.
Regarding claim 16, the combination of VanDussen, Wang, and Fan teaches, “A system comprising: at least one memory and processor configured to execute the method of claim 1.” (Fan, Para. [0025] discloses; “The system 10 includes an imaging system 12, a memory 14, a processor 16, a display 18 and a user input.”) The proposed combination as well as the motivation for combining the VanDussen, Wang, and Fan references in the rejection of claim 7, apply to claim 16 and are incorporated herein by reference. Thus, the method of claim 16 is met by VanDussen, Wang, and Fan.
Regarding claim 17, the combination of VanDussen and Wang teaches, “The system according to claim 16, wherein the at least one processor comprises at least one trained machine learning system” (Wang, Page 24, Section 2.2 discloses; “We first apply graph search [5] (which uses high level priors) to conduct segmentation for object proposals (generated based on PPMs), and then feed two small image patches containing the same object proposal (with or without the background masked out) to respectively two convolutional neural networks (CNN) with the same architecture, to verify whether the class of that object proposal is the one claimed by PPMs.”) The proposed combination as well as the motivation for combining the VanDussen, Wang, and Fan references in the rejection of claim 7, apply to claim 17 and are incorporated herein by reference. Thus, the method of claim 17 is met by VanDussen, Wang, and Fan.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over VanDussen et al., in view of Wang et al., in further view of Fan et al., and still in view of Fabrizio Musacchio (“Image Segmentation and Feature Extraction”).
Regarding claim 8, the combination of VanDussen, Wang, and Fan does not explicitly teach, “The method according to claim 7, wherein the threshold is based on an average greatest pixel intensity drop across all of the segments.” Since the combination of VanDussen, Wang, and Fan does not explicitly disclose this limitation, Examiner relies on the teachings of Musacchio in an analogous field of endeavor. Specifically, Musacchio teaches, “The method according to claim 7, wherein the threshold is based on an average greatest pixel intensity drop across all of the segments.” (Musacchio, the 3rd page discloses; “Mean thresholding sets the threshold as the average intensity of the image. It calculates the mean intensity of all the pixels and separates them into foreground and background based on this threshold.” It would be obvious to use the pixel drop as disclosed by Fan in the rejection of claim 7.)
VanDussen, Wang, Fan, and Musacchio are considered to be analogous to the claimed invention because they are in the same field of processing medical images. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of VanDussen, Wang, and Fan to incorporate the teachings of Musacchio in order to determine the threshold based on an average greatest pixel intensity drop. One of ordinary skill in the art would have been motivated to combine the previously described method of VanDussen, Wang, and Fan with the teachings of Musacchio to ensure that the method accurately detects the edges using pixel intensity. Accordingly, it would have been obvious to combine VanDussen, Wang, Fan, and Musacchio to obtain the above specified limitations.
Conclusion
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/JUSTIN M OAKES/Examiner, Art Unit 2662
/Siamak Harandi/Primary Examiner, Art Unit 2662
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