DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 13 July 2026 was received and the information disclosure statement has been considered by the examiner.
Specification
The disclosure is objected to because of the following informalities:
[0062] line 5 "tissue composition vector 210" should read "target composition vector 210"
[0063] line 1 "tissue composition vector" should read "target composition vector"
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claim 1, item c) recites determining “a distance between the composition of the region and one or more target vectors”. It is unclear how to determine a distance between a composition and a target vector. A composition is understood as a qualitative definition of type while a vector is understood as an array of numbers or an expression of magnitude and direction. It is unclear how a person of ordinary skill in the art may determine a distance between these disparate items. For purpose of examination, the examiner interprets the composition as a "composition vector of the region".
Further regarding claim 1, line 9 recites “one or more target vectors” and lines 11-12 recite “one or more target composition vectors.” As both of these items are recited with regard to a calculated distance, it is unclear if they are separate items or if they are the same item. For the purpose of examination, the examiner interprets them as the same item and specifically interprets the “one or more target vectors” as “one or more target composition vectors”. Claims 2-16 depend on claim 1 and are rejected for failing to remedy the ambiguity of claim 1.
Regarding claim 10, claim 10 recites the limitation "the region composition vector" in line 4. There is insufficient antecedent basis for this limitation in the claim. Therefore, it is unclear what is intended by the term and it is further unclear if it is the same item as “a region composition” as introduced in claim 1. For the purpose of examination, the examiner interprets it as the same item as the “region composition” as recited in claim 1. Note, should the applicant amend claim 1 to recite determining “a region composition vector”, as interpreted in the rejection of claim 1 above regarding the determining a distance, then the current rejection of claim 10 would be resolved.
Regarding claim 17, item c) recites determining “a distance between the tissue composition of the region and one or more target composition vectors”. It is unclear how to determine a distance between a composition and a target vector. A composition is understood as a qualitative definition of type while a vector is understood as an array of numbers or an expression of magnitude and direction. It is unclear how a person of ordinary skill in the art may determine a distance between these disparate items. For purpose of examination, the examiner interprets the composition as a "tissue composition vector". Claims 18-20 depend on claim 17 and are rejected for failing to remedy the ambiguity of claim 17.
Regarding claim 18, claim 18 recites the limitation "the selected one or more portions" in line 1. There is insufficient antecedent basis for this limitation in the claim. While claim 17 is a "method for selecting on or more portions of a tissue", it does not explicitly recite selecting "portions" of the tissue. Claim 17 does however select "a candidate region". Therefore, it is unclear whether the "selected one or more portions" of claim 18 are the "a candidate region" of claim 17 or if it is some other item. Further contributing to the lack of clarity is that the "selected one or more portions" may be plural while the selected "a candidate region" is singular. Further, the "a candidate region" is a region of an image of tissue while "selected one or more portions of the tissue" may be understood as either portions of the tissue in the image or portions of the tissue itself. Therefore, the claim is unclear and it is unknown what the "selected one or more portions of the tissue" are. For the purpose of examination, the examiner is giving them a broad interpretation as portions of tissue in an image which are selected and isolated by classification or object recognition. Claims 19-20 depend on claim 18 and are rejected for failing to remedy the ambiguity of claim 18.
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 nonobviousness.
Claims 1-10, 13-14, and 16-17 are rejected under 35 U.S.C. 103 as being unpatentable over Tunstall et al. (US 20160063724 A1; hereafter, Tunstall) in view of Chung et al. (KR 20230097336 A; hereafter, Chung).
Regarding claim 1, Tunstall discloses:
A system comprising: a processor ([0020] and Fig. 1, item 22 a processor);
and a non-transitory computer readable medium comprising instructions that, when executed by a processor ([0020] and Fig. 1, item 24 a memory which stores data to perform a processing algorithm which is understood as instructions. [0047] memory 24 is non-volatile. See also [0170]), cause the processor to:
a) obtain or have obtained one or more images ([0029] and Fig. 3, an image is obtained);
b) determine one or more compositions of a plurality of regions within the one or more images (as stated in the rejection under 35 U.S.C. 112(b), the examine is interpreting this limitation as determining composition vectors of the regions. [0033] and Fig. 3, the image is divided into tiles which is understood as a plurality of regions. [0034] and [0036] and Fig. 3, components are detected in each region and formed into a feature vector, i.e. a composition vector);
c) for each region in the plurality of regions, determine a distance between the composition of the region and one or more target vectors (as stated in the rejection under 35 U.S.C. 112(b), the examiner is interpreting this limitation as reciting one or more target composition vectors. Further, in the claim, distance is not given a specific definition and therefore the examiner is applying a broad interpretation as a determination of the relationship between vectors characterized by determining differences or similarities between vectors in any manner. [0037] stored feature vectors are obtained which are understood as one or more target composition vectors. [0039] and Fig. 3, the feature vectors and stored vectors are compared in order to determine what class each tile belongs to which is understood as determining a distance. This comparison is understood as a distance because [0094] defines it as determining if they match within a tolerance which is understood as a distance);
Tunstall does not disclose expressly to select a candidate region having a minimum distance between the composition vector of the region and one or more target composition vectors.
Chung discloses:
and d) select a candidate region from the plurality of regions (pg. 3 para. 5, a region of interest is selected which is understood as a candidate region. See also pg. 6 para. 7 describing S430) the candidate region having a minimum distance between the composition of the region and one or more target composition vectors in comparison to determined distances of other regions in the plurality (pg. 3 para. 5, the region is selected "in order of increasing sum values". A person or ordinary skill in the art would understand a high sum value to represent a small distance because a high sum would indicate a high degree of similarity and a low different, i.e. small distance. Therefore, selecting the region at the top of the "order of increasing sum values" is understood as selecting the region having a minimum distance).
Tunstall and Chung are combinable because they are from the same field of endeavor of image analysis using feature vectors (Tunstall, [0036]; Chung pg. 2 para. 1).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to combine the region selection of Chung with the invention of Tunstall.
The motivation for doing so would have been “reducing the amount of computation required for object detection by selectively using some of the reference feature vectors” (Chung, pg. 3 para. 7).
Therefore, it would have been obvious to combine Chung with Tunstall to obtain the invention as specified in claim 1.
Regarding claim 2, Tunstall in view of Chung discloses the subject matter of claim 1.
Tunstall does not disclose expressly to select a portion of the image corresponding to candidate region.
Chung discloses:
The system of claim 1, wherein the non-transitory computer readable medium further comprises instructions that, when executed by the processor, cause the processor to select a portion of the image corresponding to the selected candidate region (pg. 3 para. 5, a region of interest is selected which is understood as a candidate region which is understood as selection a portion of the image).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to combine the region selection of Chung with the invention of Tunstall.
The motivation for doing so would have been “the accuracy of object detection can be increased” (Chung, pg. 7 para. 2).
Therefore, it would have been obvious to combine Chung with Tunstall to obtain the invention as specified in claim 2.
Regarding claim 3, Tunstall in view of Chung discloses the subject of claim 1.
Tunstall does not disclose expressly to deploy one or more machine learning model.
Chung discloses:
The system of claim 1, wherein the instructions that cause the processor to determine compositions of the plurality of regions within the image further comprises instructions that, when executed by the processor, cause the processor to deploy a machine learning model (pg. 3 para. 2, the detection network may be a Fater R-CNN which is understood as a machine learning model).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to combine the machine learning model of Chung with the invention of Tunstall.
The motivation for doing so would have been “the computing device may extract a target feature vector and detect an object using an artificial neural network based on Fater R-CNN,” (Chung, pg. 6 para. last).
Therefore, it would have been obvious to combine Chung with Tunstall to obtain the invention as specified in claim 3.
Regarding claim 4, Tunstall in view of Chung discloses the subject matter of claim 3.
Tunstall does not disclose expressly the machine learning model performing image classification.
Chung discloses:
The system of claim 3, wherein the machine learning model performs image classification on the one or more images (pg. 3 para. 5, the detection network, i.e. the Fater R-CNN, detects an object in the selected region of interest which is understood as image classification as the image of the object is classified as the detected object).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to combine the machine learning classification of Chung with the invention of Tunstall.
The motivation for doing so would have been “the computing device may extract a target feature vector and detect an object using an artificial neural network based on Fater R-CNN,” (Chung, pg. 6 para. last).
Therefore, it would have been obvious to combine Chung with Tunstall to obtain the invention as specified in claim 4.
Regarding claim 5, Tunstall in view of Chung discloses the subject matter of claim 4.
Tunstall does not disclose expressly that the machine learning model includes one of the listed algorithms.
Chung discloses:
The system of claim 4, wherein the machine learning model performs image classification one or more images using one or more of a convolutional neural network algorithm, logistic regression algorithm, k-nearest neighbor algorithm, support vector machine algorithm, decision tree algorithm, and random forest algorithm (pg. 3 para. 2, a person of ordinary skill in the art would understand an R-CNN as a recurrent convolutional neural network).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to combine the machine learning model of Chung with the invention of Tunstall.
The motivation for doing so would have been “the computing device may extract a target feature vector and detect an object using an artificial neural network based on Fater R-CNN,” (Chung, pg. 6 para. last).
Therefore, it would have been obvious to combine Chung with Tunstall to obtain the invention as specified in claim 5.
Regarding claim 6, Tunstall in view of Chung discloses the subject matter of claim 3.
Tunstall further discloses:
The system of claim 3, wherein the instructions that cause the processor to deploy the machine learning model further comprises instructions that, when executed by the processor, cause the processor to classify the one or more images for a plurality of region classes ([0039]-[0040] the image is classified into one or a plurality of classes).
Regarding claim 7, Tunstall in view of Chung discloses the subject matter of claim 6.
Tunstall further discloses:
The system of claim 6, wherein the plurality of region classes comprises at least two, at least three, at least four, or at least five region classes ([0040] there are three classes, namely background, tumor tissue, and non-tumor tissue).
Regarding claim 8, Tunstall in view of Chung discloses the subject matter of claim 3.
Tunstall further discloses:
The system of claim 3, wherein the instructions that cause the processor to deploy the machine learning model further comprises instructions that, when executed by the processor, cause the processor to generate target composition vectors of one or more regions of an image (in reviewing the claim language, "an image" as recited in this claim is understood as a separate image from the one or more images recited in claim 1. [0064] a learning model generates feature vectors from an image to serve as classification data, i.e. target composition vectors).
Regarding claim 9, Tunstall in view of Chung discloses the subject matter of claim 8.
Tunstall further discloses:
The system of claim 8, wherein the target composition vector is a vector summarizing the classifications of the plurality of region classes for a region ([0064] the feature vector includes "an indication of whether that feature vector relates to tumour or non-tumour image data." This is understood as summarizing the classifications of the plurality of classes for a region).
Regarding claim 10, Tunstall in view of Chung discloses the subject matter of claim 8.
Tunstall further discloses:
The system of claim 8, wherein the instructions that cause the processor to determine a distance between the composition of the region and the one or more target composition vectors further comprises instructions that, when executed by the processor, cause the processor to determine the distance between the region composition vector of the candidate region and the one or more target composition vectors ([0094] the comparison determines if the region matches the comparison data within a specified tolerance which is understood as determining a distance).
Regarding claim 13, Tunstall in view of Chung discloses the subject matter of claim 1.
Tunstall does not disclose expressly to generate a ranked list of candidate regions.
Chung discloses:
The system of claim 1, wherein the non-transitory computer readable medium further comprises instructions that, when executed by the processor, cause the processor to generate a ranked list of candidate regions comprising the selected candidate region and one or more additional candidate regions (pg. 3 para. 5, the regions are "in order of increasing sum values" which is understood as a ranked list of the candidate region and one or more additional candidate regions).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to combine the ranking of Chung with the invention of Tunstall.
The motivation for doing so would have been “selects region of interest according to the sum of values calculated for each region of interest” (Chung, pg. 3 para. 5). In other words, it would be obvious to order the regions by their distance, i.e. their similarity, in order to select the best region of interest.
Therefore, it would have been obvious to combine Chung with Tunstall to obtain the invention as specified in claim 13.
Regarding claim 14, Tunstall in view of Chung discloses the subject matter of claim 13.
Tunstall does not disclose expressly to rank the candidate region corresponding to determined distances.
Chung discloses:
The system of claim 13, wherein the instructions that cause the processor to generate the ranked list of candidate regions further comprises instructions that, when executed by the processor, cause the processor to rank the candidate region and one or more additional candidate regions according to their corresponding determined distances (pg. 3 para. 5, the region is selected "in order of increasing sum values". A person of ordinary skill in the art would understand a high sum value to represent a small distance because a high sum indicates a high degree of similarity or a low difference, i.e. a low distance. Therefore, ranking in order of the increasing sum values is understood as ranking in order of decreased distances or corresponding to determined distances).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to combine the ranking of Chung with the invention of Tunstall.
The motivation for doing so would have been “selects region of interest according to the sum of values calculated for each region of interest” (Chung, pg. 3 para. 5). In other words, it would be obvious to order the regions by their distance, i.e. their similarity, in order to select the best region of interest.
Therefore, it would have been obvious to combine Chung with Tunstall to obtain the invention as specified in claim 14.
Regarding claim 16, Tunstall in view of Chung discloses the subject matter of claim 1.
Tunstall further discloses:
The system of claim 1, wherein the one or more images comprise one or more images of a tissue ([0029] the obtained image is a tissue sample).
Regarding claim 17, Tunstall discloses:
A method for selecting one or more portions of a tissue, the method comprising: a) obtaining or having obtained one or more images of the tissue ([0029] and Fig. 3, an image of tissue is obtained);
b) determining one or more tissue compositions of a plurality of regions within the one or more images (as stated in the rejection under 35 U.S.C. 112(b), the examine is interpreting this limitation as determining composition vectors of the regions. [0033] and Fig. 3, the image is divided into tiles which is understood as a plurality of regions. [0034] and [0036] and Fig. 3, tissue components are detected in each region and formed into a feature vector, i.e. a composition vector);
c) for each region in the plurality of regions, determining a distance between the tissue composition of the region and one or more target composition vectors (as stated in the rejection under 35 U.S.C. 112(b), the examiner is interpreting this limitation as reciting one or more target composition vectors. Further, in the claim, distance is not given a specific definition and therefore the examiner is applying a broad interpretation as a determination of the relationship between vectors characterized by determining differences or similarities between vectors in any manner. [0037] stored feature vectors are obtained which are understood as one or more target composition vectors. [0039] and Fig. 3, the feature vectors and stored vectors are compared in order to determine what class each tile belongs to which is understood as determining a distance. This comparison is understood as a distance because [0094] defines it as determining if they match within a tolerance which is understood as a distance);
Tunstall does not disclose expressly to select a candidate region having a minimum distance among the distances of candidate regions.
Chung discloses:
d) selecting a candidate region from the plurality of regions (pg. 3 para. 5, a region of interest is selected which is understood as a candidate region. See also pg. 6 para. 7 describing S430), the candidate region having a minimum distance between the tissue composition of the region and one or more target composition vectors in comparison to determined distances of other regions in the plurality (pg. 3 para. 5, the region is selected "in order of increasing sum values". A person or ordinary skill in the art would understand a high sum value to represent a small distance. Therefore, selecting the region at the top of the "order of increasing sum values" is understood as selecting the region having a minimum distance).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to combine the region selection of Chung with the invention of Tunstall.
The motivation for doing so would have been “reducing the amount of computation required for object detection by selectively using some of the reference feature vectors” (Chung, pg. 3 para. 7).
Therefore, it would have been obvious to combine Chung with Tunstall to obtain the invention as specified in claim 17.
Claims 11 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Tunstall et al. (US 20160063724 A1; hereafter, Tunstall) in view of Chung et al. (KR 20230097336 A; hereafter, Chung) in further view of Rambach et al. (US 20250225779 A1; hereafter, Rambach).
Regarding claim 11, Tunstall in view of Chung discloses the subject matter of claim 10.
Tunstall in view of Chung does not disclose determining a cosine distance.
Rambach discloses:
The system of claim 10, wherein the instructions that cause the processor to determine the distance further comprises instructions that, when executed by the processor, cause the processor to determine a cosine distance ([0069] calculate a cosine similarity between feature vectors. A person of ordinary skill in the art would understand the relationship between cosine distance and cosine similarity as Distance = 1 - Similarity. Therefore, calculating the cosine similarity is understood as also calculating the cosine distance).
Rambach is combinable with Tunstall in view of Chung because it solves a similar problem in image processing of training region detection by using feature vectors (Rambach, [0069]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to combine the cosine distance of Rambach with the invention of Tunstall in view of Chung.
The motivation for doing so would have been so that “The samples which match best may be selected" (Rambach, [0069]).
Therefore, it would have been obvious to combine Rambach with Tunstall in view of Chung to obtain the invention as specified in claim 11.
Regarding claim 15, Tunstall in view of Chung discloses the subject matter of claim 14.
Tunstall in view of Chung does not disclose to rank the candidate region in ascending order of cosine distances.
Rambach discloses:
The system of claim 14, wherein the ranked list of candidate regions ranks the candidate region and one or more additional candidate regions in ascending order of cosine distances ([0069] a cosine similarity is calculated which is understood to teach for a person of ordinary skill in the art a cosine distance. When viewed in combination with Tunstall in view of Chung it would be obvious to adapt the ranking of Chung with the cosine distance of Rambach).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to combine the cosine distance of Rambach with the ranking of Tunstall in view of Chung.
The motivation for doing so would have been that doing so would have been a simple substitution for one known element, the ranked distances of Tunstall in view of Chung, for another, the cosine distance of Rambach, to obtain predictable results, a ranked list according to cosine distances. The prior art, Tunstall in view of Chung, differed from the claimed invention by the distance not being expressly recited as a cosine distance. It was found that the missing component, a cosine distance, is known in the art, see Rambach [0069]. One of ordinary skill in the art could have substituted one known element for another, the distances in the ranked list of Tunstall in view of Chung for the cosine distance of Rambach, and the results of the substitution would have been predictable, namely, a ranked list of cosine distances.
Therefore, it would have been obvious to combine Rambach with Tunstall in view of Chung to obtain the invention as specified in claim 15.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Tunstall et al. (US 20160063724 A1; hereafter, Tunstall) in view of Chung et al. (KR 20230097336 A; hereafter, Chung) in further view of Van Leeuwen et al. (US 11232565 B2; hereafter, Van Leeuwen).
Regarding claim 12, Tunstall in view of Chung discloses the subject matter of claim 1.
Tunstall in view of Chung does not disclose expressly that the one or more target composition vectors indicate target percentages of a plurality of region classes.
Van Leeuwen discloses:
The system of claim 1, wherein each of the one or more target composition vectors indicate target percentages of a plurality of region classes (col. 4 line 25-31, extract characteristics of a reference region for comparison to other regions. Therefore, the characteristics of the reference region may be understood as one or more target composition vectors. Col. 2 line 56-67, the characteristics may include "the local amount/percentage of a particular cell type or tissue type", therefore, the target composition vector is understood to comprise percentages of classes, i.e. the particular cell type or tissue type).
Van Leeuwen is combinable with Tunstall in view of Chung because it is from the same field od endeavor of tissue sample image analysis (Van Leeuwen, col. 1 line 16-21).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to combine the composition vector, i.e. region characteristics, of Van Leeuwen with the invention of Tunstall in view of Chung.
The motivation for doing so would have been "If alternative candidate regions are detected, the user can be made aware of them by means of visual feedback. Alternative regions can be highlighted on the screen with a specific colour" (Van Leeuwen, col. 2 line 28-31). In other words, alternative candidate regions can be detected which match the composition of the reference region, i.e. the target composition vector.
Therefore, it would have been obvious to combine Van Leeuwen with Tunstall in view of Chung to obtain the invention as specified in claim 12.
Claims 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Tunstall et al. (US 20160063724 A1; hereafter, Tunstall) in view of Chung et al. (KR 20230097336 A; hereafter, Chung) in further view of Karaçali et al. ("Automated detection of regions of interest for tissue microarray experiments: an image texture analysis" full reference on PTO-892; hereafter, Karacali).
Regarding claim 18, Tunstall in view of Chung discloses the subject matter of claim 17.
Tunstall in view of Chung does not disclose expressly isolating the selected portions of the tissue and processing the selected portions to generate a tissue microarray.
Karacali discloses:
The method of claim 17, further comprising: isolating the selected one or more portions of the tissue (pg. 7 col. 1 para. 3, image regions are classified as cancerous, normal or both. The classifying of tissue may be understood as isolating or separation the portions of tissue);
processing the selected one or more portions of the tissue to generate a tissue microarray (pg. 9 col. 1 para. 4, the image regions comprised of cancer specific blocks "are considered as regions of interest and this information is utilized in sampling of the tumor tissue for constructing tissue microarrays").
Karacali is combinable with Tunstall in view of Chung because it is from the same field of endeavor of tissue image analysis (Karacali, pg. 2 col. 2 para. 3).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to combine the tissue selection of Karacali with the invention of Tunstall in view of Chung.
The motivation for would have been “sampling of the tumor tissue for constructing tissue microarrays with significant clinical relevance” (Karacali, pg. 9 col. 1 para. 4).
Therefore, it would have been obvious to combine Karacali with Tunstall in view of Chung to obtain the invention as specified in claim 18.
Regarding claim 19, Tunstall in view of Chung in further view of Karacali discloses the subject matter of claim 18.
Tunstall in view of Chung does not disclose expressly that isolating the portions comprises sampling one or more tissue cores.
Karacali discloses:
The method of claim 18, wherein isolating the selected one or more portions comprises sampling one or more tissue cores (pg. 19 col. 1 para. 2, the assembly of microarrays includes tissue cores. A person of ordinary skill in the art would understand that to "play a similarly positive role in sampling tissue for tissue microarrays" would be done by sampling selected portions via tissue cores).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to combine the sampling of Karacali with the invention of Tunstall in view of Chung.
The motivation for doing so would have been “The region of interest information gathered from the whole section images will guide the excision of tissue for high throughput profiling of global gene expression” (Karacali, pg. 19 col. 1 para. 1).
Therefore, it would have been obvious to combine Karacali with Tunstall in view of Chung to obtain the invention as specified in claim 19.
Regarding claim 20, Tunstall in view of Chung in further view of Karacali discloses the subject matter of claim 18.
Tunstall in view of Chung does not disclose expressly generating a paraffin embedding of the selected portions, sectioning the paraffin embedding, and performing tissue staining of the sectioned paraffin embedding.
Karacali discloses:
The method of claim 18, wherein processing the selected one or more portions to generate a tissue microarray comprises: generating a paraffin embedding of the one or more selected portions (pg. 19 col. 1 para. 2, the identified regions of the method, i.e. the selected portions, may be embedded in paraffin blocks);
sectioning the paraffin embedding of the one or more selected portions (pg. 19 col. 1 para. 2, the paraffin block is made up of thousands of separate tissue cores which is understood as sectioning the paraffin embedding of the one or more selected portions);
and performing tissue staining of the sectioned paraffin embeddings (pg. 19 col. 1 para. 2, the paraffin block is analyzed for biomarker presence including fluorescence which a person of ordinary skill in the art would understand as including tissue staining of the sectioned paraffin embedding).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to combine the paraffin embedding of Karacali with the invention of Tunstall in view of Chung.
The motivation would have been “The technique proposed here can also be utilized as an initial screening phase of an automated image analysis for which the second phase focuses on more advanced techniques evaluating nuclei morphology” (Karacali, pg. 19 col. 1 para. 2).
Therefore, it would have been obvious to combine Karacali with Tunstall in view of Chung to obtain the invention as specified in claim 20.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Wang et al., US 20210110180 A1, discloses a system for object recognition in images depending on probability vectors which contain a probability of a region belonging to a particular classification.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOSHUA B CROCKETT whose telephone number is (571)270-7989. The examiner can normally be reached Monday-Thursday 8am-5pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, John M Villecco can be reached at (571) 272-7319. 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.
/JOSHUA B. CROCKETT/Examiner, Art Unit 2661
/AARON W CARTER/Primary Examiner, Art Unit 2661
Prosecution Insights