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 08/30/2024 is being considered by the examiner.
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 limitations are: “reading means” and “processing means” in Claims 1 and 12.
Because these claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they 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 these limitations 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
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 5 recites the limitation "the area of the ink" in lines 1-2. There is insufficient antecedent basis for this limitation in the claim.
Claim 7 recites the limitation "the geometric factor and the lighting" in lines 1-2. There is insufficient antecedent basis for this limitation in the claim.
The term “correct” in Claim 7 is a relative term which renders the claim indefinite. The term “correct” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
Regarding Claim 8, the phrase "such as" in the limitation “applying adjustments such as color correction, contrast enhancement and denoising” renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
Regarding Claim 13, the phrase "such as" in the limitation “features of the chemical indicator such as color, geometry, homogeneity of the measured surface, color differences, regions of interest, contours and symbolically encoded information” renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
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 1-9 and 12-13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1
Step 1 – YES
Claim 1 discloses a process, and thus falls in one of the statutory categories.
Step 2A, Prong One – YES
Claim 1 recites an abstract idea. Claim 1 recites “analyzing the region of interest and extracting features of the chemical indicator by the processing means to determine the state of the chemical indicator and the result of the washing, disinfection and sterilization process.” Analysis of a chemical indicator, which under the broadest reasonable interpretation includes color changing indicators ([0003] of the instant application specification), may be performed by one of ordinary skill in the art by observation, judgment, evaluation, and opinion. Extracting features and determining the state of the chemical indicator and the result of the washing, disinfection and sterilization process may be performed in the mind of one of ordinary skill in the art by visual observation.
Step 2A, Prong Two – NO
Claim 1 does not recite additional elements that integrate the judicial exception into a practical application. Claim 1 recites “A method for monitoring a washing, disinfection and sterilization process using a chemical indicator, comprising the steps of: a) locating a two-dimensional reference code on the chemical indicator by reading means, and decoding the two-dimensional reference code so as to validate that the chemical indicator is compatible with processing means; b) capturing an image of the chemical indicator by the reading means to obtain a digitized image; c) performing a first cropping of the digitized image by the processing means to keep only the entire chemical indicator and remove unnecessary information; d) performing a second cropping of the image obtained after the first cropping by the processing means in order to obtain a region of interest of the chemical indicator” and “wherein the processing means uses an artificial intelligence model comprising a convolutional neural network to analyze the region of interest and extract features of the chemical indicator, and to determine the state of the chemical indicator and the result of the washing, disinfection and sterilization process.”
Steps a)-d) all amount to insignificant extra-solution activity. That is, the steps of locating and decoding a two-dimensional reference code, capturing an image, and cropping an image are well known techniques in image processing, do not impose meaningful limits on the claim such that it is not nominally or tangentially related to the invention, and amount to mere data gathering. The two-dimensional reference code decoding performed “to validate that the chemical indicator is compatible” does not impose meaningful limits, but rather is mere insignificant pre-solution activity.
The recitation of “an artificial intelligence model comprising a convolution neural network” to perform the abstract idea of analysis of the region of interest is recited at a high level of generality and amounts to mere instructions to “apply it.” That is, the recitation of an artificial intelligence model amounts to mere instructions to apply the analysis, feature extraction, and state determination on a computer. Merely applying the abstract ideas on a computer does not incorporate the abstract ideas into a practical application because the claim does not contain any recitation of particular features or steps that improve the function of the method; the specification must both set forth an improvement in technology ([0054]-[0066]) and the claim itself must reflect the disclosed improvement. Claim 1 does not reflect the disclosed improvements of the specification, instead merely reciting instructions to apply the abstract ideas on a computer.
Step 2B – NO
Claim 1 does not recite additional elements that amount to significantly more than the judicial exception. As stated above, Claim 1 recites only elements that amount to insignificant extra-solution activity (elements a)-d)) and an element that amounts to mere instructions to apply the abstract idea on a computer. Thus, these elements do not amount to significantly more than the judicial exception.
Thus, Claim 1 is not eligible subject matter.
Dependent Claims 2-9 recite modifications to steps a)-e) of Claim 1 but do not contain additional elements that incorporate the abstract ideas into a practical application or amount to significantly more than the judicial exception, but rather the additional elements of claims 2-7 and 9 merely further describe elements of insignificant extrasolution activity in a manner nominally or tangentially related to the invention. Claim 8 recites “applying adjustments” “prior to the extraction of the features” in step e), but the step amounts to insignificant extrasolution activities because recited color correction, contrast enhancement, and denoising are well known and do not impose meaningful limits on the claim. Thus, Claims 2-9 are also rejected under 35 U.S.C. 101.
Claim 12 recites a system with elements corresponding to the method of Claim 1; Claim 12 contains the additional element of a “A system for monitoring a washing, disinfection and sterilization process” and “processing means in data communication with the reading means.” However, these elements are generic computer components and thus do not amount to significantly more than the abstract ideas and does not integrate the abstract idea into a practical application. Thus, Claim 12 is also rejected under 35 U.S.C. 101.
Dependent Claim 13 recites an abstract idea: “wherein the processing means allows to directly or indirectly obtain from the digitized image features of the chemical indicator such as color, geometry, homogeneity of the measured surface, color differences, regions of interest, contours and symbolically encoded information.” Color, geometry, homogeneity, color difference, regions of interest, contours, and symbolically encoded information may all be obtained from a digitized image by observation and judgment in the mind of one of ordinary skill in the art. Claim 13 does not contain any additional elements that integrate the abstract ideas into a practical application or amount to significantly more than the judicial exception. Thus, Claim 13 is also rejected under 35 U.S.C. 101.
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 1-10, 12, and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Decker et al. (US 2016/0232421 A1) in view of Rowe et al. (US 2022/0084659 A1), further in view of Ma et al. (US 11462319 B2).
Regarding Claim 1, Decker teaches “A method for monitoring a washing, disinfection and sterilization process using a chemical indicator, comprising the steps of:
a) locating a two-dimensional reference code on the chemical indicator by reading means” (Decker, [0045] discloses “A frame is captured from the onboard camera and fed into the image processing pipeline.” Decker, [0047] discloses “The frame is fed into the code detection algorithm to search for QR codes”; where an onboard camera is a reading means; where a QR code is a two-dimensional reference code), “and decoding the two-dimensional reference code so as to validate that the chemical indicator is compatible with processing means” (Decker, [0047]-[0051] discloses “The frame is fed into the code detection algorithm to search for QR codes. If no QR code is found, the pipeline is exited and a new frame is captured. 4) If a QR code is found, the QR code is verified against predefined criteria such as: Correct form or format Acceptable manufacturer The calibration strip is not expired”);
“b) capturing an image of the chemical indicator by the reading means to obtain a digitized image” (Decker, [0045] discloses “A frame is captured from the onboard camera and fed into the image processing pipeline”; where a frame is an image; see Fig. 4, Fig. 10);
e) analyzing the region of interest and extracting features of the chemical indicator by the processing means to determine the state of the chemical indicator and the result of the washing, disinfection and sterilization process” (Decker, [0058] discloses “Extract the hue of each test square. [0059] 11) Determine the meaning of the square hue via an internal lookup or and external data source (database or file)”),
Decker does not explicitly teach “c) performing a first cropping of the digitized image by the processing means to keep only the entire chemical indicator and remove unnecessary information; d) performing a second cropping of the image obtained after the first cropping by the processing means in order to obtain a region of interest of the chemical indicator” and “wherein the processing means uses an artificial intelligence model comprising a convolutional neural network to analyze the region of interest and extract features of the chemical indicator, and to determine the state of the chemical indicator and the result of the washing, disinfection and sterilization process.”
However, in an analogous field of endeavor, Rowe teaches “c) performing a first cropping of the digitized image by the processing means to keep only the entire chemical indicator and remove unnecessary information” (Rowe, [0084] discloses “The image 910 may be roughly cropped to a region of interest 920 that surrounds the diagnostic test. This region of interest 920 may be located, for example, by identifying a set of three or more spatial markers, such as with built-in functions of OpenCV or other suitable computer vision software packages. The area bounded by these spatial markers can be subject to further analysis”; where cropping to a region of interest using markers is performing a first cropping to keep only the entire chemical indicator);
“d) performing a second cropping of the image obtained after the first cropping by the processing means in order to obtain a region of interest of the chemical indicator” (Rowe, [0100] discloses “As an example of an automated manner of performing a rough crop of the image to isolate the test region, FIG. 11 illustrates a variation of performing a rough crop of the image depicting a diagnostic test including a test strip in a cassette. In some variations, assuming that the test strip is somewhat centered within an on-screen reticle displayed on a camera device (e.g., on a mobile computing device), the rough crop may remove a predetermined portion (e.g., percentage) of the image perimeter. For example, the rough crop may remove an outer 30% of the image perimeter, though the percentage to be cropped may be any suitable value”; where removing a predetermined portion of the image perimeter to isolate the test region is performing a second cropping to obtain a region of interest).
It would have been obvious to one of ordinary skill in the art before the effective filing
date of the claimed invention to have modified Decker to incorporate the teachings of Rowe by performing cropping on a diagnostic test kit. The prior art Decker contained a ‘base’ method upon which the claimed invention can be seen as an ‘improvement.’ The prior art Rowe contained a ‘comparable’ method that has been improved in the same way as the claimed invention; that is, Rowe teaches a method of analyzing an image of a diagnostic test, including steps of first cropping the image to a test region. One of ordinary skill in the art could have applied the known ‘improvement’ technique of Rowe in the same way to the ‘base’ method of Decker and the results would have been predictable to one of ordinary skill in the art. That is, it would have been obvious to one of ordinary skill in the art that the cropping techniques applied to the diagnostic test images of Rowe may be applied to the test strip images of Decker with the predictable results of cropping the image to a test region (or region of interest).
The combination of Decker and Rowe does not explicitly teach “wherein the processing means uses an artificial intelligence model comprising a convolutional neural network to analyze the region of interest and extract features of the chemical indicator, and to determine the state of the chemical indicator and the result of the washing, disinfection and sterilization process.”
However, in an analogous field of endeavor, Ma teaches “wherein the processing means uses an artificial intelligence model comprising a convolutional neural network to analyze the region of interest and extract features of the chemical indicator, and to determine the state of the chemical indicator and the result of the washing, disinfection and sterilization process” (Ma, column 10, lines 5-16 discloses “In the second instance above, the vision system 100 would be used to detect and log the actual result (pass/fail) from that chemical indicator 134 automatically providing updates to the record 132 for the instrument 112. The chemical indicator 134 can use a similar detection method as the instrument 112. The chemical indicator 134 shape can be treated as another shape to detect. A machine learning classifier, for example a multiclass logistic regression classifier, would be trained to distinguish multiple surgical instruments 112 from each other, and be able to distinguish the appearance of the chemical indicator 134 from that of the surgical instrument 112”; where detecting and logging the result from the chemical indicator using a machine learning classifier is using an artificial intelligence model to analyze the region of interest and extract features and to determine the state of the chemical indicator and the result. Ma, Claim 31 also recites “wherein the neural network is a convolutional neural network.” Ma, column 26, lines 56-61 discloses “generate a set of feature values based on a visual representation of the first surgical instrument in the image, wherein the set of feature values correspond to features usable to determine an instrument type of the surgical instrument, wherein at least one of the set of feature values is the chemical indicator”; where generating feature values of the chemical indicator is extracting features of the chemical indicator).
It would have been obvious to one of ordinary skill in the art before the effective filing
date of the claimed invention to have modified the combination of Decker and Rowe to incorporate the teachings of Ma by using a convolutional neural network to determine the state of a chemical indicator. Decker teaches a ‘base’ method upon which the claimed invention can be seen as an ‘improvement.’ The prior art Ma contained a ‘comparable’ method that has been improved in the same way as the claimed invention. That is, Ma teaches a method of sterilization process management that has been improved by neural network processing. One of ordinary skill in the art could have applied the known ‘improvement’ technique in the same way to the ‘base’ method and the results would have been predictable to one of ordinary skill in the art. That is, applying the teachings of Ma to the teachings of Decker by substituting the data table lookup method of Decker ([0030]) for the neural network system to detect and log chemical indicator result would have been obvious to one of ordinary skill in the art. Accordingly, the combination of Decker, Rowe, and Ma discloses the invention of Claim 1.
Regarding Claim 2, the combination of Decker, Rowe, and Ma teaches “The method according to claim 1, wherein the two-dimensional reference code is a datamatrix or a QR code” (Decker, [0047] discloses “The frame is fed into the code detection algorithm to search for QR codes”).
Regarding Claim 3, the combination of Decker, Rowe, and Ma teaches “The method according to claim 1, wherein in step a) information within the two-dimensional reference code is decoded, said information comprising the indicator type, batch, expiration and date of manufacture” (Decker, [0088] discloses “In addition to the squares 10-20, this embodiment of the test strip includes a first QR code 22-A and a second QR code 22-B located on a handle of the test strip. In accordance with an aspect of the invention, QR code 22-A and/or QR code 22-B encode all of the strip metadata (e.g., strip manufacturer, expiration date, tracking information, etc.) at a lower resolution than an embodiment utilizing a single QR code”).
Regarding Claim 4, the combination of Decker, Rowe, and Ma teaches “The method according to claim 1, wherein step c) further comprises rotating the image with respect to the two-dimensional reference code so that the indicator is in a natural reading orientation for its subsequent analysis” (Decker, [0018] discloses “For example, a code readable by a mobile device can be use such as a bar code or a QR code if the strip is wide enough to accommodate the minimum QR code size to get sufficient resolution for readability. Placing a code on the test strip allows the APP to simply search for a code initially, rotate the image based on the code, and then apply advanced object detection routines to determine a location and color of the test strip pads.”)
Regarding Claim 5, the combination of Decker, Rowe, and Ma teaches “The method according to claim 1, wherein the region of interest comprises the area of the ink reactive to the process to which the chemical indicator was subjected” (Decker, [0080] discloses “The test strip in the embodiment illustrated by FIG. 4 includes squares 10, 12, 14, 16, 18, and 20 including chemical reagents associated with pH and a code 22 (e.g., bar code, QR code, etc.)”; where squares including chemical reagents are ink reactive to processes).
Regarding Claim 6, the combination of Decker, Rowe, and Ma teaches “The method according to claim 1, wherein the second cropping is performed using image processing techniques, such as blurring, edge detection and color transformations” (Rowe, [0096] discloses “For example, one or more of edge detection (e.g., Canny, Diriche, Differential, Sobel, Prewitt, Roberts cross, etc.), ridge detection (e.g., Hough transforms, etc.), blob detection (e.g., LoG, DoG, DoH, MSER, PCBR, etc.), feature detection (e.g., affines, SIFT, SURF, GLOH, HOG, etc), and/or deep learning techniques may be used to determine the outline of a target region.”) The proposed combination as well as the motivation for combining the Decker, Rowe, and Ma references presented in the rejection of Claim 1, apply to Claim 6 and are incorporated herein by reference. Thus, the apparatus recited in Claim 6 is met by Decker, Rowe, and Ma.
Regarding Claim 7, the combination of Decker, Rowe and Ma teaches “The method according to claim 1, wherein between step c) and step d), the geometric factor and the lighting are validated to ensure that the image obtained is correct, and components detected in the image are controlled to be within certain color ranges” (Decker, [0022] discloses “The APP can use the manufacturer information encoded on the code to look up (e.g., utilize a look-up table in a cloud database) the test square layout, including a number and size of the squares, and what the different colors mean to determine test results”; where a number and size of squares is a geometric factor. Rowe, [0092] discloses “One or more various aspects of the image may be validated for quality, including but not limited to lighting level, color balance, exposure level, noise level, image blur level, presence of shadows, and/or presence of glare in the received image”; where lighting level is lighting; where validating quality including lighting level and color balance is ensuring the components are controlled to be within certain color ranges). The proposed combination as well as the motivation for combining the Decker, Rowe, and Ma references presented in the rejection of Claim 1, apply to Claim 7 and are incorporated herein by reference. Thus, the apparatus recited in Claim 7 is met by Decker, Rowe, and Ma.
Regarding Claim 8, the combination of Decker, Rowe, and Ma teaches “The method according to claim 1, wherein step e) further comprises applying adjustments such as color correction, contrast enhancement and denoising, by means of the processing means, to improve image quality prior to the extraction of the features” (Rowe, [0126] discloses “Once the reference color blocks have been located, images of those color blocks may be converted to a color space that is best suited for the analysis of their color. Descriptive statistics representing the color blocks may be calculated similar to that as described above. These descriptive statistics may be used to generate a color correction matrix, which can be applied to the entire image or just the region of interest.”) The proposed combination as well as the motivation for combining the Decker, Rowe, and Ma references presented in the rejection of Claim 1, apply to Claim 8 and are incorporated herein by reference. Thus, the apparatus recited in Claim 8 is met by Decker, Rowe, and Ma.
Regarding Claim 9, the combination of Decker, Rowe, and Ma teaches “The method according to claim 1, wherein the chemical indicator features obtained are at least one of the presence of reactive ink, the color of the reactive ink, the homogeneity of the color of the reactive ink, the change patterns of the reactive ink, the presence of reflections and/or stains, the color texture and color temperature detected in the image” (Decker, [0093]-[0094] discloses “instructions configured to determine a color of each located pad; instructions configured to compare the determined color to a reference”).
Regarding Claim 10, the combination of Decker, Rowe, and Ma teaches “The method according to claim 1, further comprising the step: f) digitally recording the result and information of the indicator, allowing local or remote access thereto” (Decker, [0061] discloses “In one embodiment, the test strip APP 116 can be configured to store test strip data readings (e.g., pad/square color) or other data input by a user in a data store 120, such as in memory device 110, or to store the data at a remote location such as a remote data store 122 on a site by site basis (cloud or otherwise)”).
Regarding Claim 12, Claim 12 recites a system with elements corresponding to the steps recited in Claim 1. Therefore, the recited elements of this claim are mapped to the proposed combination in the same manner as the corresponding steps in its corresponding method claim. Additionally, the rationale and motivation to combine the Decker, Rowe, and Ma references, presented in rejection of Claim 1, apply to this claim. Finally, the combination of Decker, Rowe, and Ma references discloses “processing means in data communication with the reading means” (Decker, [0028] discloses “In an exemplary embodiment, the APP includes processor-executable instructions, stored in a computer-readable storage medium and executed by a processor of a computing device (e.g., a tablet or a smart phone), for acquiring visual image data of the test strip via the camera.”)
Regarding Claim 13, the combination of Decker, Rowe, and Ma discloses “The system according to claim 12, wherein the processing means allows to directly or indirectly obtain from the digitized image features of the chemical indicator such as color, geometry, homogeneity of the measured surface, color differences, regions of interest, contours and symbolically encoded information” (Decker, [0022] discloses “The APP can use the manufacturer information encoded on the code to look up (e.g., utilize a look-up table in a cloud database) the test square layout, including a number and size of the squares, and what the different colors mean to determine test results”; where a number and size of squares is a geometry feature).
Allowable Subject Matter
Claims 11 and 14 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Claims 15-20 are allowed.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding Claims 11 and 14, Claims 11 and 14 recite “wherein the state of the chemical indicator is determined with a sensitivity above 89% and a specificity above 92%,” Claim 11 dependent on Claim 1 and Claim 14 dependent on Claim 12. Although sensitivity and specificity are well known metrics in the field of machine learning, the specific metrics of a sensitivity above 89% and a specificity above 92%, with respect to the state of the chemical indicator, is not recited in the cited prior art. Thus, none of the previously cited references, alone or in combination provide a motivation to teach the ordered combinations of “The method according to claim 1, wherein the state of the chemical indicator is determined with a sensitivity above 89% and a specificity above 92%” and “The system according to claim 12, wherein the state of the chemical indicator is determined with a sensitivity above 89% and a specificity above 92%.”
The following is an examiner’s statement of reasons for allowance:
Regarding Claim 15, although the cited prior art Ma teaches machine learning used in sterilization process management (Ma, column 10, lines 5-16 discloses “In the second instance above, the vision system 100 would be used to detect and log the actual result (pass/fail) from that chemical indicator 134 automatically providing updates to the record 132 for the instrument 112”), Ma does not explicitly teach quantifying cavitation energy using an artificial intelligence model comprising a convolutional neural network. Additionally, color changing cavitation indicators are also known in the art (Sharavara (US 2021/0325239 A1) teaches a method of testing operation of ultrasonic cleaning machines by evaluating indicator ink: [0058] discloses “In this embodiment the color of the ink is visually different compared to the color of the substrate to clearly visualize the test results.”) However, there is no teaching in the cited prior art to quantify cavitation energy using an artificial intelligence model, and there is no motivation in Ma nor Sharavara to combine the teachings of Decker, Rowe, Ma, and Sharavara to teach the method of Claim 15.
Thus, none of the previously cited prior art, alone or in combination, provides a motivation to teach the ordered combination of “A method for quantifying cavitation energy in a cavitation indicator subjected to an ultrasonic wash cycle, comprising the following steps: a) capturing an image of the cavitation indicator using reading means, said image having the cavitation indicator correctly positioned and aligned in a field of view of the reading means, with framing, focus and illumination being verified using processing means; b) preprocessing the image using the processing means, applying image processing techniques to improve the quality of the image; c) cropping regions of interest in the image obtained from the previous step by isolating specific areas needed for analysis; and d) analyzing the regions of interest using the processing means to quantify the cavitation energy in the cavitation indicator, wherein the processing means uses an artificial intelligence model comprising a convolutional neural network to analyze the regions of interest and quantify the cavitation energy to which the cavitation indicator was subjected based on colorimetric changes detected.”
Dependent Claims 16 and 17 contain all allowable subject matter of Claim 15 and thus are also allowable.
Claim 18 recites a method with steps corresponding to the elements of Claim 15, and thus contains all allowable subject matter of Claim 15 and is also allowable.
Dependent Claims 19 and 20 contain all allowable subject matter of Claim 18 and thus are also allowable.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: Corsini (US 2020/0030476 A1) discloses a sterilization method including identifying failed sterilization cycles using QR codes and a scanner to scan chemical indicators to identify and evaluate sterilized items.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CAROLINE TABANCAY DUFFY whose telephone number is (703)756-1859. The examiner can normally be reached Monday - Friday 8:00 am - 5:30 pm.
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, Amandeep Saini can be reached at 5712723382. 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.
/CAROLINE TABANCAY DUFFY/Examiner, Art Unit 2662
/AMANDEEP SAINI/Supervisory Patent Examiner, Art Unit 2662
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