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 .
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “an image acquisition unit configured to acquire …; an exclusion region determination unit configured to set ...; and a calculation unit configured to calculate …” as recited in claim 1.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 7 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 7 recites that, in determining the exclusion region, “each of a region that satisfies Vt < μ − 3σ and a region that satisfies Vt > μ + 3σ” is determined as the exclusion region. However, claim 7 does not provide antecedent basis for “μ” and “σ”. Specifically, the claims define μV as an average value of the characteristic value of the plurality of regions and define δV as a standard deviation of the characteristic value of the plurality of regions, yet the inequalities in claim 7 use μ and σ rather than μV and δV, and do not otherwise define μ and σ. Accordingly, “μ” and “σ” in the recited inequalities lack antecedent basis and render the scope of claim 7 unclear (e.g., whether μ corresponds to μV and σ corresponds to δV, or whether different quantities are required), and the scope of claim 7 is therefore indefinite.
Typical amendment: replace μ and σ with the previously introduced variables, e.g., “Vt < μV − 3σV” and “Vt > μV + 3σV” or otherwise expressly define μ and σ in the claim.
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 1–20 are rejected under 35 U.S.C. §101 because the claimed invention is directed to an abstract idea without significantly more. The flow chart in MPEP §2106, Subject Matter Eligibility Test For Products and Processes, is referred to for establishing ineligible subject matter.
Step 1 (Statutory Category): Claim 1 recites an information processing system, which is categorized as a machine under the four recognized statutory categories.
Step 2A, Prong One (Judicial Exception): However, the claim is further directed to the abstract idea of (i) acquiring an image that includes a plurality of individual separated compartments, (ii) dividing the image into a plurality of regions, (iii) setting/ deriving a “characteristic value” for the regions, (iv) determining an exclusion region among the regions based on the characteristic value, and (v) calculating target-related information from the remaining regions after excluding the exclusion region. These recitations encompass mental processes (evaluation/ selection/ exclusion decisions that can be performed in the mind or by pen and paper) and mathematical concepts (e.g., statistical measures/ thresholding for determining exclusion regions), which are judicial exceptions (see MPEP §2106.04(a)(2) (mental processes; mathematical relationships/ formulas)).
Step 2A, Prong Two (Integration into a Practical Application): The additional elements consist of generic computer components and functional “units” (e.g., an image acquisition unit, exclusion region determination unit, and calculation unit) that merely perform the abstract processing and output results. The claim does not recite any particularized rule-based constraints, specific image-processing mechanisms, or improvements to the functioning of the computer or imaging/ assay hardware; rather, it uses functional units to perform the abstract processing. The recited “individual separated compartment” context amounts to a field-of-use environment for the abstract analysis. As such, the additional elements amount to merely applying the exception on a computer and do not integrate the judicial exception into a practical application (see MPEP §2106.05(d) (mere instructions to apply an exception) and §2106.05(f) (insignificant extra-solution activity)).
Step 2B (Significantly More/Inventive Concept): Considered individually and in combination, the additional claim elements do not amount to significantly more than the judicial exception, as explained above. The claims recite well-understood, routine, and conventional components performing their routine function in the field and are claimed at a high level of generality, without any non-conventional arrangement or improvement to the underlying computer technology (see MPEP §2106.05(d), (e), (h)). Therefore, claim 1 is ineligible under 35 U.S.C. §101.
Regarding claims 2–18, considered individually and in combination, the additional limitations (including, for example, recitations directed to statistical thresholding using μ and σ such as μ±3σ) do not amount to significantly more than the judicial exception, and therefore the claims are all ineligible.
Regarding claims 19–20: The rationale provided for claim 1 is incorporated herein. In addition, the information processing system of claim 1-18 correspond to the method of claim 19, as well as the non-transitory storage medium/program of claim 20, and perform the steps disclosed therein. Therefore, claims 19–20 are also ineligible under 35 U.S.C. §101.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-3, 5-7, 10-11, 17, and 19-20 are rejected under 35 U.S.C. 103 as obvious over Betschart (Betschart et al., US 2018/0230515 A1, 2018).
Regarding claim 1, Betschart teaches an information processing system using an individual separated compartment for detecting a target through use of the individual separated compartment ([0007] – [0008]: Betchart performs dPCR in each reaction area (partition/ compartment) of an array of reaction areas and quantifies nucleic acid concentration from the set of reaction area, where each reaction location is separated interrogated by imaging to determine presence of a target analyte), the information processing system comprising:
an image acquisition unit configured to acquire an image including, as an object, a plurality of individual separated compartments in which a target is includable
(Betschart discloses analyzing optical signals, which are detected by registering photons which produces a recordable output usually as an electrical signal [0044], in each reaction area and separated from reaction areas having an optical artefact from calculating amount or concentration of a target of interest [0007]; FIGS. 1A-1C illustrate steps processing from an acquired source image to an image containing the partitions’ center; optical signal corresponding to an acquired source image comprising pixel data [0043])
an exclusion region determination unit configured to set, based on the image ([0007]: distribution of the optical signals (images) in each reaction area is analyzed), a characteristic value for determining an exclusion region to be excluded from among a plurality of regions of the image (Betschart extracts characteristic statistics that a suitable threshold level may be determined and derived in standard deviation [0053], Betschart also expressly teaches characterizing the distribution using mean, median, standard deviation, largest and lowest signal, etc., pixel based image processing [0050]), and determine the exclusion region based on the characteristic value of the plurality of regions (Betschart teaches identifying an exclusion region (invalid reaction area) if the distribution is unequal [0052]); and
a calculation unit configured to calculate information relating to the target from an image of individual separated compartments included in each region for calculation obtained by excluding the exclusion region from the image (Betschart’s optical signal corresponding to an acquired source image comprising pixel data [0043] corresponds to the recited “an image of individual separated compartments”, wherein the amount or concentration of the nucleic acid of interest is calculated on valid reaction areas [areas not identified as invalid] by eliminating the reaction area identified as invalid in the optical signal / acquired source image [corresponding to the recited “by excluding the exclusion region from the image”], [0009], [0014], [0052] & [0057]),
Although different embodiments of Betschart have been referred to, it would have been exceedingly obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Betschart by combining Betschart’s similar embodiments in order to not limit the embodiments to themselves but include other evident combinations and extensions thereof (see Betschart, [0142]).
Regarding claim 2, Betschart teaches the information processing system according to claim 1, wherein the exclusion region determination unit is configured to acquire the characteristic value for each of the plurality of regions (in [0050], Betschart explicitly determines characteristic value of distribution for each reaction area and computes values used for exclusion or invalidation).
Regarding claim 3, Betschart teaches the information processing system according to claim 1, wherein the characteristic value comprises any one selected from a group consisting of:
a number of positive individual separated compartments ([0003], [0025]: Betschart teaches that dPCR partitions (reaction areas) yield positive reactions when the target molecule is present and that nucleic acids may be quantified by counting the regions that contain PCR end-product positive reactions);
a ratio of the number of positive individual separated compartments to the number of individual separated compartments;
an average value of brightness of the individual separated compartments;
a median value of brightness of the individual separated compartments;
a maximum value of brightness of the individual separated compartments; and
a minimum value of brightness of the individual separated compartments,
where the positive individual separated compartment represents an individual separated compartment indicating that the individual separated compartment includes a target and a negative individual separated compartment represents an individual separated compartment indicating that the individual separated compartment does not include a target.
(Given claim 3 is satisfied by any one of the listed characteristics values, Betschart fully teaches the limitations of claim 3. Furthermore, Applicant is directed to Betschart’s other discussions, from which it is readily apparent that Betschart also discloses other listed types of characteristic values for identifying invalid reaction areas.)
Regarding claim 5, Betschart teaches the information processing system according to claim 1, wherein the exclusion region determination unit is configured to determine the exclusion region through statistical processing from the characteristic value of each of the plurality of regions and the characteristic value of the plurality of regions (in [0050-0054], Betschart uses statistical parameter processing (e.g., mean, standard deviation, distribution-shape assessment, deviations vs thresholds; deriving thresholds from typical values in the same array) to determine which regions are invalid or excluded).
Regarding claim 6, Betschart teaches the information processing system according to claim 1, wherein the exclusion region determination unit is configured to determine the exclusion region based on Vt, μv, and δV, where Vt represents the characteristic value of each of the plurality of regions, μv represents an average of the characteristic value of the plurality of regions, and δV represents a standard deviation of the characteristic value of the plurality of regions (in [0050-0054], Betschart uses statistical parameter processing (e.g., mean, standard deviation, distribution-shape assessment, deviations vs thresholds; deriving thresholds from typical values in the same array) to determine which regions are invalid or excluded. Betschart further teaches that the statistical characteristics include mean & standard deviation to determine the exclusion area).
Regarding claim 7, Betschart teaches the information processing system according to claim 1, wherein the exclusion region determination unit is configured to determine, as the exclusion region, each of a region that satisfies Vt<μ−3σ and a region that satisfies Vt>μ+3σ, where Vt represents the characteristic value of each of the plurality of regions, μV represents an average of the characteristic value of the plurality of regions, and δV represents a standard deviation of the characteristic value of the plurality of regions (Betschart teaches an exclusion/ invalid-region determination based on image-derived characteristic values and teaches characterizing optical-signal distributions using statistical parameters including mean (μ) and standard deviation (σ), and determining invalid reaction areas using a threshold selected based on such characteristic values. [0050]–[0053]).
Betschart further teaches that, with respect to threshold selection, a POSITA would be able to select a suitable threshold, and that invalid reaction areas (exclusion regions) can be identified when the distribution deviates from expected behavior ([0051]–[0052]). It would have been obvious to a POSITA, when implementing Betschart’s taught threshold-based invalidation using μ and σ, to define the threshold as μ±3σ (i.e., to designate as exclusion regions those regions having characteristic values Vt satisfying Vt < μ−3σ or Vt > μ+3σ), because the 3-sigma rule is a well-known, standard outlier-rejection criterion in statistical quality control and analytical data processing for removing anomalous data points or regions. Applying that conventional 3σ rule in Betschart’s framework would have been a predictable choice for excluding aberrant regions while leaving the underlying assay and image-processing approach unchanged, thereby improving robustness of Betschart’s quantification by rejecting statistical outliers.
Regarding claim 10, Betschart teaches the information processing system according to claim 1, wherein the image comprises at least any one of a bright-field image or a fluorescent image (in [0043-0045], Betschart’s optical signals are imaged derived from pixel values and Betschart discloses imaging method via bright-field or fluorescence mode).
Regarding claim 11, Betschart teaches the information processing system according to claim 1, wherein the image includes 10 or more and 1,000 or less regions among the plurality of regions (in [0041], Betschart uses target regions are quantified approximately 100 to 200, 200 to 300, 300 to 400, 700 or more reaction areas, and further teaches that each reaction region is analyzed by detecting optical-signals from sub-areas arranged as pixels where the image is a dot matrix data structure [0043])
Regarding claim 17, Betschart teaches the information processing system according to claim 1, wherein the individual separated compartment comprises one of a well or a liquid droplet (Betschart explicitly lists reaction areas including microwell or nanowell and also discusses droplet-based dPCR (droplets); [0038], [0039]).
Regarding claims 19–20. The rationale provided for claim 1 is incorporated herein. In addition, the information processing system of claim 1 corresponds to the method of claim 10, as well as the computer-readable recording medium of claim 20, and performs the steps disclosed herein. Therefore, the claims are all ineligible.
Claims 4, 8, 9 and 16 are rejected by Betschart (Betschart et al, US 2018/0230515 A1, 2018) in view of Duffy (Duffy et al, US 2012/0277114 A1, 2012).
Regarding claim 4, with deficiencies of Betschart noted in square brackets [], Betschart teaches the information processing system according to claim 1,
[wherein the information processing system is configured to use a target-capturing substance for capturing a target], and
wherein the characteristic value comprises any one selected from a group consisting of:
a number of positive individual separated compartments (Betschart teaches that dPCR partitions (reaction areas) yield positive reactions when the target molecule is present and that nucleic acids may be quantified by counting the regions that contain PCR end-product positive reactions [0003], [0025]); In addition, Duffy also teaches determining the number of reaction vessels containing an analyte molecule, a count of “positive” compartments [0008]);
a ratio of the number of positive individual separated compartments to the number of individual separated compartments that include target-capturing substances;
an average value of brightness of the individual separated compartments;
a median value of brightness of the individual separated compartments;
a maximum value of brightness of the individual separated compartments;
a minimum value of brightness of the individual separated compartments;
an average value of brightness of the individual separated compartments that do not include target-capturing substances;
a median value of brightness of the individual separated compartments that do not include target-capturing substances;
a maximum value of brightness of the individual separated compartments that do not include target-capturing substances;
a minimum value of brightness of the individual separated compartments that do not include target-capturing substances;
a standard deviation of brightness of the individual separated compartments that do not include target-capturing substances;
an average value of brightness of the individual separated compartments that include target-capturing substances;
a median value of brightness of the individual separated compartments that include target-capturing substances;
a maximum value of brightness of the individual separated compartments that include target-capturing substances;
a minimum value of brightness of the individual separated compartments that include target-capturing substances;
a standard deviation of brightness of the individual separated compartments that include target-capturing substances;
a number of target-capturing substances;
a value obtained by dividing the number of positive individual separated compartments by the number of individual separated compartments that include target-capturing substances; and
a target-capturing substance filling rate,
where the positive individual separated compartment represents an individual separated compartment indicating that the individual separated compartment includes a target-capturing substance and includes a target, a negative individual separated compartment represents an individual separated compartment indicating that the individual separated compartment includes a target-capturing substance and does not include a target, and the target-capturing substance filling rate represents a value obtained by dividing the number of individual separated compartments that include target-capturing substances by the number of individual separated compartments.
(Given claim 4 is satisfied by any one of the listed characteristics values, Betschart fully teaches the limitations of claim 4. Furthermore, Applicant is directed to Betschart’s other discussions, from which it is readily apparent that Betschart also discloses other listed types of characteristic values for identifying invalid reaction areas.)
As noted above in square brackets, Betschart does not teach, but Duffy teaches:
wherein the information processing system is configured to use a target-capturing substance for capturing a target ([0008]: Duffy teaches capturing substances as beads, exposing them to analyte molecules so some beads bind analyte while others do not, and spatially segregating beads into reaction vessels/wells for optical interrogation, a target-capturing substance used to capture a target as analyte)
It would have been prima facie obvious to a POSITA, before the effective filing date of the claimed invention, motivated to modify Betschart’s system to incorporate Duffy’s use of target-capturing substances (e.g., capture beads, including magnetic beads) and bead-occupancy, because both references are directed to improving the reliability of quantitative results obtained from imaged, compartmentalized assay arrays. Betschart teaches determining characteristic values from optical images (mean, median, standard deviation, min, max signal features) and using thresholds to identify and exclude invalid regions / reaction areas from subsequent target quantification, including artefacts related to improper filling or abnormal signal distributions. Duffy teaches bead-based compartment assays in which capture beads are distributed into wells or locations and optical interrogation distinguishes (i) compartments containing capture beads, (ii) compartments in which beads are associated with analyte (positive), and (iii) compartments lacking beads, and further uses such determinations for quantitative analysis. A POSITA would have been motivated to adopt Duffy’s capture-bead implementation into Betschart’s system so that Betschart’s taught image-derived characteristic values and exclusion logic could be applied not only to signal artefacts but also to bead subset, occupancy conditions (e.g., bead vs no-bead compartments) that predictably affect measurement accuracy, thereby improving robustness and reducing bias from poorly loaded or otherwise unreliable regions before calculating target-related information, without changing their core functions.
Regarding claim 8, the combination of Betschart and Duffy teaches the information processing system according to claim 4, wherein the exclusion region determination unit is configured to set the characteristic value to the target-capturing substance filling rate and determine, as the exclusion region, each of a region in which the target-capturing substance filling rate is less than 4% and a region in which the target-capturing substance filling rate exceeds 40% (Duffy teaches capture-object's filling rate is “about 4% … about 40% … of the capture objects are spatially segregated into the plurality of locations,” [0078], that there is an optimal bead occupancy window to supports selecting lower and upper filling-rate thresholds and excluding regions outside those bounds [0076]).
Regarding claim 9, the combination of Betschart and Duffy teaches the information processing system according to claim 4, wherein the target-capturing substance comprises a magnetic particle, wherein the particle has a particle diameter of 1 μm or more and 10 μm or less (Duffy teaches using magnetic beads (capture objects) having diameter ~2.8 μm and coated with capture antibodies, which fall within 1–10 μm, as target-capturing substances [0228]).
Regarding claim 16, the combination of Betschart and Duffy teaches the information processing system according to claim 1, wherein each of the plurality of regions includes 100 or more and 100,000 or less individual separated compartments (Duffy teaches arrays comprising between about 10,000 and about 100,000 reaction vessels [0140], and also provides a concrete example of an array having 50,000 microwells, which is within the claimed 100–100,000 range [0239]).
Claims 12-15 are rejected by Betschart (Betschart et al, US 2018/0230515 A1, 2018) in view of Yip (Yip et al, US 2020/0258223 A1, 2017).
Regarding claim 12, with deficiencies of Betschart noted in square brackets [], Betschart teaches the information processing system according to claim 1, [wherein the plurality of regions of the image have mutually equivalent areas].
As noted above in square brackets, Betschart does not teach, but Yip teaches:
wherein the plurality of regions of the image have mutually equivalent areas (Yip explicitly teaches dividing an imaged tissue region into fixed-size regions, including large non-overlapping 4096×4096 input windows and a grid of 32×32 tiles within the windows (uniform, mutually equivalent areas); [0358], [0359], [0368]).
It would have been prima facie obvious to a POSITA, before the effective filing date of the claimed invention, motivated to implement Betschart’s exclusion/ validity determination and downstream calculation (based on image-derived characteristic values) using a fixed-size tiling/ window scheme as taught by Yip, because Yip teaches that multi-tile processing (including overlap handling) improves computational efficiency by reducing redundancy while still preserving spatial context (Yip, [0353]), and Betschart already relies on deriving characteristic values and distributions from image data to identify invalid or excluded regions before calculating target-related results (Betschart, [0050]–[0053]). Using Yip’s fixed-size regions (tiles/ windows) would have been a predictable implementation choice to standardize region-wise computation in Betschart’s image processing pipeline.
Regarding claim 13, the combination of Betschart and Yip teaches the information processing system according to claim 1, wherein the plurality of regions of the image have overlapping portions that overlap with each other (Yip teaches that annotated regions of the image are tiled into overlapping tiles (466×466 pixels) with a stride of 32 pixels, which necessarily creates overlap between neighboring regions/tiles [0367]; and Yip also describes overlap context in multi-tile processing as part of its region analysis [0353]).
Regarding claim 14, the combination of Betschart and Yip teaches the information processing system according to claim 1, wherein the image is covered with all the plurality of regions of the image (Yip teaches dividing the tissue region into non-overlapping 4096×4096 input windows, and that “typically, between 10–30 input windows are needed to cover the tissue,”, the set of regions collectively covers the (target) image or tissue region [0358]).
Regarding claim 15, the combination of Betschart and Yip teaches the information processing system according to claim 1, wherein the image is inhibited from being covered with all the plurality of regions of the image (Yip teaches performing tissue segmentation using a tissue masking algorithm to contour tissue and produce a bounding box around the tissue of interest, and dividing the tissue region (not the entire slide/ image background) into windows [0358]; Yip also teaches passing an assembled probability map through a tissue mask to remove background and marker area; both inhibiting full-image coverage [0360]).
Claim 18 are rejected by Betschart (Betschart et al, US 2018/0230515 A1, 2018) in view of Noji (Noji et al, US 2013/0345088 A1, 2013).
Regarding claim 18, with deficiencies of Betschart noted in square brackets [], Betschart teaches the information processing system according to claim 1, [wherein the individual separated compartment has a volume of 0.1 fL or more and 1,000 fL or less].
As noted above in square brackets, Betschart does not teach, but Noji teaches:
wherein the individual separated compartment has a volume of 0.1 fL or more and 1,000 fL or less (Noji teaches femtoliter scale chambers used as individual separated compartments, including receptacles with a capacity up to 1,000 fL, which falls within the claimed range [0003]).
It would have been prima facie obvious to a POSITA, before the effective filing date of the claimed invention, motivated to implement Betschart’s image-based exclusion/ quantification system using femtoliter-scale compartments as taught by Noji, because both references concern analyzing targets in a plurality of individually separated compartments and improving reliability and accuracy of such analyses. Using Noji’s taught femtoliter-volume receptacles (including up to 1,000 fL) in Betschart’s partition-based imaging workflow would have been a predictable design choice to obtain known benefits of small-volume compartmentalization (single-molecule/ assay operation and high sensitivity) while still applying Betschart’s taught image-derived characteristic value evaluation and exclusion of invalid compartments to improve measurement accuracy.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KEN KUDO whose telephone number is (571)272-4498. The examiner can normally be reached M-F 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, Vincent Rudolph can be reached at 571-272-8243. 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.
KEN KUDO
Examiner
Art Unit 2671
/KEN KUDO/Examiner, Art Unit 2671
/VINCENT RUDOLPH/Supervisory Patent Examiner, Art Unit 2671