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 .
Status of Claims
Currently pending Claim(s):
1-20
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 03/07/2024 and 06/21/2024 were filed in compliance with the provisions of 37 CFR 1.97 and 1.98. Accordingly, the information disclosure statement is being considered by the examiner as indicated below.
Applicant has cited a [large, extreme, excessive] number references on the IDS without indicating any significance or providing any explanation of relevance of any of the cited references.
It is desirable to avoid the submission of long lists of documents if it can be avoided. Eliminate clearly irrelevant and marginally pertinent cumulative information. If a long list is submitted, highlight those documents which have been specifically brought to applicant’s attention and/or are known to be of most significance. See Penn Yan Boats, Inc. v. Sea Lark Boats, Inc., 359 F. Supp. 948, 175 USPQ 260 (S.D. Fla. 1972), aff’d, 479 F.2d 1338, 178 USPQ 577 (5th Cir. 1973), cert. denied, 414 U.S. 874 (1974). But cf. Molins PLC v. Textron Inc., 48 F.3d 1172, 33 USPQ2d 1823 (Fed. Cir. 1995). Please see MPEP 2004.13.
Therefore, based on the current IDS submission, the examiner has considered the cited references searchable in USPTO databases, other patent office databases, and/or commercial patent and non-patent literature databases in the same manner the examiner has searched all prior art as indicated in the search history of record. Cited references not searchable in these databases will be considered independently.
The information disclosure statement (IDS) submitted on 02/12/2024 was not considered by the examiner because of the applicant’s request to review the IDS submitted on 03/07/2024, which includes the correct references cited.
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:
“microscope system” in claims 1 and 20.
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.
Claims 1 and 20: “microscope system” corresponds to Figure 1 element 11: “In certain embodiments, pathogen detection system 100 can optionally include or be operatively coupled to a microscope system 11. Microscope system 11 is typically a digital microscope that includes an imaging module 14, a focus variation module 16, a sample carrier 18 and an autofocus system 20.” (Applicant Pub paragraph [0152])
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
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, 11, and 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.
Claim 1, for example, at line 16 recites “indicating that presence of an infection within the bodily sample could not be determined with a sufficient degree of reliability”. The term “sufficient” in claims 1, 11, and 20 is a relative term which renders the claim indefinite. The term “sufficient” is not defined by the claims, 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. Therefore, the limitation “indicating that presence of an infection within the bodily sample could not be determined with a sufficient degree of reliability” is indefinite because it is unclear how “sufficient degree of reliability” will be used for determining the presence of an infection within the bodily sample.
Dependent claims 2-10, and 12-19 are rejected for the same reasons.
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 a judicial exception (i.e., abstract idea - mental process) without significantly more.
Step (1) Are the claims directed to a process, machine, manufacture, or composition of matter;
Step (2A) Prong One: Are the claims directed to a judicially recognized exception, i.e., a law of nature, a natural phenomenon, or an abstract idea;
Prong Two: If the claims are directed to a judicial exception under Prong One, then is the judicial exception integrated into a practical application;
Step (2B) If the claims are directed to a judicial exception and do not integrate the judicial exception, do the claims provide an inventive concept.
Step 1:
Claim 1 recites an apparatus. Therefore, the claim is directed to the statutory categories of machine.
Step (2A):
Prong One:
Claim 1 recites:
“in the one or more images, identify at least one element as being a candidate of a given entity, extract, from the one or more images, at least one candidate-informative feature associated with the candidate, extract, from the one or more images, at least one sample-informative feature that is indicative of contextual information related to the bodily sample.” Under its broadest reasonable interpretation in light of the specification, the limitation encompasses the mental process of identifying the candidate and extracting the features associated with the candidate which is practically capable of being performed in the human mind with the assistance of pen and paper.
Prong Two:
This judicial exception is not integrated into a practical application. The additional elements of “a microscope system configured to acquire one or more microscope images of a bodily sample; an output device; and at least one computer processor” and “process the candidate-informative feature in combination with the sample-informative feature, and in response thereto, perform an action selected from the group consisting of: generating an output on the output device indicating that presence of an infection within the bodily sample could not be determined with a sufficient degree of reliability, generating an output on the output device indicating that a portion of the sample should be re-imaged, generating an output on the output device indicating that a portion of the sample should be re-imaged using different settings, driving the microscope system to re-image a portion of the sample, driving the microscope system to re-image a portion of the sample using different settings, and modulating a frame rate at which microscope images are acquired by the microscope system.” amount to no more than mere necessary data gathering and applying because, under its broadest reasonable interpretation, it is simply using generic hardware to perform the abstract idea. Thus, they are insignificant extra-solution activity. Even when viewed in combination, these additional elements do not integrate the abstract idea into a practical application and the claims are thus directed to the abstract idea.
Step (2B):
Claim 1 does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The limitations “a microscope system configured to acquire one or more microscope images of a bodily sample; an output device; and at least one computer processor” and “process the candidate-informative feature in combination with the sample-informative feature, and in response thereto, perform an action selected from the group consisting of: generating an output on the output device indicating that presence of an infection within the bodily sample could not be determined with a sufficient degree of reliability, generating an output on the output device indicating that a portion of the sample should be re-imaged, generating an output on the output device indicating that a portion of the sample should be re-imaged using different settings, driving the microscope system to re-image a portion of the sample, driving the microscope system to re-image a portion of the sample using different settings, and modulating a frame rate at which microscope images are acquired by the microscope system.” amount to no more than mere data gathering and outputting with general purpose hardware and provide no inventive concept. These elements, individually and in combination, are well-understood, routine, conventional activity. As such, the claim is ineligible.
Step 1:
Prong One:
Claims 2-10 recite an apparatus. Claims 12-19 recite a method. Therefore, the claims are directed to the statutory categories of machine and process, respectively.
Step (2A):
Claims 2-10, and 12-19 merely narrow the previously recited abstract idea limitations. For
the reasons described above, this judicial exception is not meaningfully integrated into a practical application, or significantly more than the abstract idea. The claims disclose similar limitations described for the independent claim above.
Step 1:
Claim 11 recites a method. Therefore, the claim is directed to the statutory categories of process.
Step (2A):
Prong One:
Claim 11 recites:
“in the one or more images, identifying at least one element as being a candidate of a given entity; extracting, from the one or more images, at least one candidate-informative feature associated with the candidate; extracting, from the one or more images, at least one sample-informative feature that is indicative of contextual information related to the bodily sample;” Under its broadest reasonable interpretation in light of the specification, the limitation encompasses the mental process of identifying the candidate and extracting the features associated with the candidate which is practically capable of being performed in the human mind with the assistance of pen and paper.
Prong Two:
This judicial exception is not integrated into a practical application. The additional elements of “acquiring one or more microscope images of a bodily sample, using a microscope; using at least one computer processor:” and “processing the candidate-informative feature in combination with the sample-informative feature; and in response thereto, performing an action selected from the group consisting of: generating an output indicating that presence of an infection within the bodily sample could not be determined with a sufficient degree of reliability, generating an output indicating that a portion of the sample should be re-imaged, generating an output indicating that a portion of the sample should be re-imaged using different settings, driving the microscope to re-image a portion of the sample, driving the microscope to re-image a portion of the sample using different settings, and modulating a frame rate at which microscope images are acquired by the microscope.” amount to no more than mere necessary data gathering and applying because, under its broadest reasonable interpretation, it is simply using generic hardware to perform the abstract idea. Thus, they are insignificant extra-solution activity. Even when viewed in combination, these additional elements do not integrate the abstract idea into a practical application and the claims are thus directed to the abstract idea.
Step (2B):
Claim 11 does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The limitations “acquiring one or more microscope images of a bodily sample, using a microscope; using at least one computer processor:” and “processing the candidate-informative feature in combination with the sample-informative feature; and in response thereto, performing an action selected from the group consisting of: generating an output indicating that presence of an infection within the bodily sample could not be determined with a sufficient degree of reliability, generating an output indicating that a portion of the sample should be re-imaged, generating an output indicating that a portion of the sample should be re-imaged using different settings, driving the microscope to re-image a portion of the sample, driving the microscope to re-image a portion of the sample using different settings, and modulating a frame rate at which microscope images are acquired by the microscope.” amount to no more than mere data gathering and outputting with general purpose hardware and provide no inventive concept. These elements, individually and in combination, are well-understood, routine, conventional activity. As such, the claim is ineligible.
Step 1:
Claim 20 recites a non-transitory computer-readable medium. Therefore, the claim is directed to the statutory categories of manufacture.
Step (2A):
Prong One:
Claim 20 recites:
“in the one or more images, identifying at least one element as being a candidate of a given entity; extracting, from the one or more images, at least one candidate-informative feature associated with the candidate; extracting, from the one or more images, at least one sample-informative feature that is indicative of contextual information related to the bodily sample;” Under its broadest reasonable interpretation in light of the specification, the limitation encompasses the mental process of identifying the candidate and extracting the features associated with the candidate which is practically capable of being performed in the human mind with the assistance of pen and paper.
Prong Two:
This judicial exception is not integrated into a practical application. The additional elements of “A computer software product, for use with a bodily sample, an output device and a microscope system configured to acquire one or more microscope images of a bodily sample, the computer software product comprising a non-transitory computer-readable medium in which program instructions are stored, which instructions, when read by a computer cause the computer to perform the steps of:” and “processing the candidate-informative feature in combination with the sample-informative feature; and in response thereto, performing an action selected from the group consisting of: generating an output on the output device indicating that presence of an infection within the bodily sample could not be determined with a sufficient degree of reliability, generating an output on the output device indicating that a portion of the sample should be re-imaged, generating an output on the output device indicating that a portion of the sample should be re-imaged using different settings, driving the microscope system to re-image a portion of the sample, driving the microscope system to re-image a portion of the sample using different settings, and modulating a frame rate at which microscope images are acquired by the microscope system.” amount to no more than mere necessary data gathering and applying because, under its broadest reasonable interpretation, it is simply using generic hardware to perform the abstract idea. Thus, they are insignificant extra-solution activity. Even when viewed in combination, these additional elements do not integrate the abstract idea into a practical application and the claims are thus directed to the abstract idea.
Step (2B):
Claim 20 does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The limitations “A computer software product, for use with a bodily sample, an output device and a microscope system configured to acquire one or more microscope images of a bodily sample, the computer software product comprising a non-transitory computer-readable medium in which program instructions are stored, which instructions, when read by a computer cause the computer to perform the steps of:” and “processing the candidate-informative feature in combination with the sample-informative feature; and in response thereto, performing an action selected from the group consisting of: generating an output on the output device indicating that presence of an infection within the bodily sample could not be determined with a sufficient degree of reliability, generating an output on the output device indicating that a portion of the sample should be re-imaged, generating an output on the output device indicating that a portion of the sample should be re-imaged using different settings, driving the microscope system to re-image a portion of the sample, driving the microscope system to re-image a portion of the sample using different settings, and modulating a frame rate at which microscope images are acquired by the microscope system.” amount to no more than mere data gathering and outputting with general purpose hardware and provide no inventive concept. These elements, individually and in combination, are well-understood, routine, conventional activity. As such, the claim is ineligible.
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 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Bachelet et al. (US 2012/0169863 A1) (hereinafter, Bachelet) in view of Beecher et al. (US 2009/0040325 A1) (hereinafter, Beecher).
Regarding claim 1, Bachelet discloses apparatus comprising: a microscope system configured to acquire one or more microscope images of a bodily sample (paragraph [0015] “for an automated apparatus capable of inspecting blood donations or blood samples for the presence of parasitic infection…where the apparatus includes components for automated microscopy, and machine-vision processing for performing automatic identification of pathogens.);
an output device (paragraph [0031] “The apparatus wherein at least one of the at least one processor outputs a result that includes at least one of the following:”); and
at least one computer processor (paragraph [0031] “The apparatus wherein at least one of the at least one processor outputs a result that includes at least one of the following:”); configured to:
in the one or more images, identify at least one element as being a candidate of a given entity (paragraph [0017] “provides an apparatus for automatic detection of pathogens within a sample… wherein the processor is adapted to perform image processing using classification algorithms on visual classification features to detect one or more suspected pathogens, when present, in the sample.”; paragraph [0078] “wherein the classification features include one or more of the following: motion, size, shape, coloring, contrast, location in respect to additional biological structures, presence of internal structures, presence of extracellular structures, the aspect ratio, the optical density, florescence at predetermined wavelengths, optical birefringence, clustering behavior, and pattern matching.”),
extract, from the one or more images, at least one candidate-informative feature associated with the candidate (paragraph [0107] “images of known pathogens are saved in a database, and image processing software of the invention is activated on the images to extract visual characteristics which are typically associated with each known pathogen. Classification features are constructed manually, automatically extracted or refined from a database of known pathogens, or a combination thereof.”),
extract, from the one or more images, at least one sample-informative feature that is indicative of contextual information related to the bodily sample (paragraph [0125] “the term "candidate" refers to a patch which, during the algorithmic processing stages, is suspected to contain a pathogen.”; paragraph [0126] “Given a novel candidate, the algorithm uses the separation model computed in the previous phase and extracts classification features to determine whether the candidate is a target or not.”),
process the candidate-informative feature in combination with the sample-informative feature (paragraph [0108] “The apparatus then utilizes image analysis software to locate putative appearances of the pathogen in the image. The apparatus compares the characteristics of a suspected pathogen present in the image, to a succinct set of characteristics extracted from images of known pathogens. The characteristics, termed "classification features" herein, may include, but are not limited to, typical motion of live parasites, their typical shape, size, their coloring, their contrast, and their location with respect to other elements of the biological sample (for example, if the pathogen is located within a mammalian cell)”), and
in response thereto, perform an action selected from the group consisting of: [generating an output on the output device] indicating that presence of an infection within the bodily sample could not be determined with a sufficient degree of reliability (Examiner interprets algorithmic decision in Bachelet as degree of reliability. paragraph [0180] “Central to the invention is the use of classification features which are associated with specific pathogens, in order to reach an algorithmic decision whether a pathogen is identified in the sample or not.”),
[generating an output on the output device] indicating that a portion of the sample should be re-imaged (paragraph [0148] “with the timing of activation of light source and with image capture of the digital camera, to ensure proper sequence is maintained and to ensure images are initially captured from different areas of the cartridge. Subsequently, when images have been processed and certain areas of the sample have been tagged as requiring additional analysis, when images have been processed and certain areas of the sample have been tagged as requiring additional analysis, controller may move the cartridge support frame 310, may move the stage 320, or may instruct camera to zoom in on these areas, may replace or add optical filters, or may illuminate the area of interest with a different light source to gather additional information.”),
[generating an output on the output device] indicating that a portion of the sample should be re-imaged using different settings (paragraph [0148] “controller may move the cartridge support frame 310, may move the stage 320, or may instruct camera to zoom in on these areas, may replace or add optical filters, or may illuminate the area of interest with a different light source to gather additional information.”),
driving the microscope system to re-image a portion of the sample (paragraph [0148] “with the timing of activation of light source and with image capture of the digital camera, to ensure proper sequence is maintained and to ensure images are initially captured from different areas of the cartridge. Subsequently, when images have been processed and certain areas of the sample have been tagged as requiring additional analysis, when images have been processed and certain areas of the sample have been tagged as requiring additional analysis, controller may move the cartridge support frame 310, may move the stage 320, or may instruct camera to zoom in on these areas, may replace or add optical filters, or may illuminate the area of interest with a different light source to gather additional information.”),
driving the microscope system to re-image a portion of the sample using different settings (paragraph [0148] “controller may move the cartridge support frame 310, may move the stage 320, or may instruct camera to zoom in on these areas, may replace or add optical filters, or may illuminate the area of interest with a different light source to gather additional information.”).
However, Bachelet fails to teach generating an output on the output device and modulating a frame rate at which microscope images are acquired by the microscope system.
Beecher teaches generating an output on the output device (paragraph [0022] “The display system in each of the user computing systems 114(1-n) is used to show data and information to the user… other types of data and information could be displayed and other manners of providing the information can be used. The display system comprises a computer display screen, such as a CRT or LCD screen by way of example only, although other types and numbers of displays could be used…”) and
modulating a frame rate at which microscope images are acquired by the microscope system (paragraph [0043] “The imaging management system 112 adjusts a video fame rate based on the bandwidth to control the rate at which images are provided between the requested one of the remotely operable microscope systems 110(1-n) and the one or more of the authorized user computing systems”).
Therefore, it would have been obvious to one of ordinary skill of the art before the effective filing date to modify Bachelet’s reference to include generating an output on an output device and modulating a frame rate at which microscope images are acquired by the microscope system taught by Beecher’s reference. The motivation for doing so would have been to show the data to the user and to provide multiple views of the specimen as suggested by Beecher (see Beecher paragraph [0019] and paragraph [0043]).
Further, one skilled in the art could have combined the elements described above by known methods with no change to the respective functions, and the combination would have yielded nothing more that predictable results. Therefore, it would have been obvious to combine Beecher with Bachelet to obtain the invention specified in claim 1.
Regarding claim 2, which claim 1 is incorporated, Bachelet discloses wherein the at least one computer processor is configured to extract the sample-informative feature from the one or more images (paragraph [0107] “image processing software of the invention is activated on the images to extract visual characteristics which are typically associated with each known pathogen. Classification features are constructed manually, automatically extracted or refined from a database of known pathogens, or a combination thereof.”), by extracting, from the one or more images, a number of candidates of the given entity within the sample (paragraph [0031] “at least one processor outputs a result that includes at least one of the following: the presence or absence of a pathogen; the species of pathogen; the number or concentration of pathogens detected;”; paragraph [0082] “processing the candidates for finding if more than one candidate belongs to the same target, and where found, candidates of the same target are clustered together;”).
Regarding claim 3, which claim 1 is incorporated, Bachelet discloses wherein the at least one computer processor is configured to extract the sample-informative feature from the one or more images (paragraph [0107] “image processing software of the invention is activated on the images to extract visual characteristics which are typically associated with each known pathogen. Classification features are constructed manually, automatically extracted or refined from a database of known pathogens, or a combination thereof.”), by extracting, from the one or more images, a brightness of the candidates relative to a background brightness (paragraph [0215] “The fluorescence image, which roughly overlays the intensity image, is segmented and clustered in a manner analogous to the motion detection above. Instead of looking for patches which move differently from the background, patches whose fluorescence is higher than the background, e.g. patches having high SNR, are sought. High fluorescence can refer to high fluorescence intensity values, or high sum fluorescence, e.g. as integrated over an area.”).
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Regarding claim 4, which claim 1 is incorporated, Bachelet discloses wherein the at least one computer processor is configured to extract the sample-informative feature from the one or more images (paragraph [0107] “image processing software of the invention is activated on the images to extract visual characteristics which are typically associated with each known pathogen. Classification features are constructed manually, automatically extracted or refined from a database of known pathogens, or a combination thereof.”), by extracting, from the one or more images, an indication of a number of candidates that are determined to be the given entity (paragraph [0031] “at least one processor outputs a result that includes at least one of the following: the presence or absence of a pathogen; the species of pathogen; the number or concentration of pathogens detected;”; paragraph [0082] “processing the candidates for finding if more than one candidate belongs to the same target, and where found, candidates of the same target are clustered together;”).
Regarding claim 5, which claim 1 is incorporated, Bachelet discloses wherein the at least one computer processor is configured to extract the sample-informative feature from the one or more images (paragraph [0107] “image processing software of the invention is activated on the images to extract visual characteristics which are typically associated with each known pathogen. Classification features are constructed manually, automatically extracted or refined from a database of known pathogens, or a combination thereof.”), by extracting, from the one or more images, an indication of probabilities of the candidates being the given entity (paragraph [0080] “calculating the likelihood that the at least one candidate contains a target;”; paragraph [0082] “processing the candidates for finding if more than one candidate belongs to the same target, and where found, candidates of the same target are clustered together;”; paragraph [0083] “tracking at least one candidate, in relation to the at least one cluster, that may belong to the cluster, and where the tracked candidate belongs, adding the tracked candidate to the cluster; determining and classifying the likelihood that the at least one cluster contains a target”).
Regarding claim 6, which claim 1 is incorporated, Bachelet discloses wherein the at least one computer processor is configured to extract the sample-informative feature from the one or more images (paragraph [0107] “image processing software of the invention is activated on the images to extract visual characteristics which are typically associated with each known pathogen. Classification features are constructed manually, automatically extracted or refined from a database of known pathogens, or a combination thereof.”), by extracting, from the one or more images, an indication of a number of the candidates that have a probability of being the given entity that exceeds a threshold (paragraph [0080] “calculating the likelihood that the at least one candidate contains a target;”; paragraph [0082] “processing the candidates for finding if more than one candidate belongs to the same target, and where found, candidates of the same target are clustered together;”; paragraph [0083] “tracking at least one candidate, in relation to the at least one cluster, that may belong to the cluster, and where the tracked candidate belongs, adding the tracked candidate to the cluster; determining and classifying the likelihood that the at least one cluster contains a target” paragraph [0211-212] “which it is likely that a pathogen of interest, referred to hereinafter as the "target", appears. One or more of the following methods may be used to detect these candidate patches: a. Pattern matching--if the general form of the target is well defined, a pattern describing this form is constructed in a pre-processing stage: numerous examples of its form are manually collected, and the general pattern is extracted. When processing an image, this pattern is then matched at every location, and those locations which exhibit high similarity to the pattern are taken as candidates”).
Regarding claim 7, which claim 1 is incorporated, Bachelet discloses wherein the at least one computer processor is configured to extract the sample-informative feature from the one or more images (paragraph [0107] “image processing software of the invention is activated on the images to extract visual characteristics which are typically associated with each known pathogen. Classification features are constructed manually, automatically extracted or refined from a database of known pathogens, or a combination thereof.”), by extracting, from the one or more images, an indication of a number of the candidates that have a probability of being a given type of the given entity that exceeds a threshold (paragraph [0080] “calculating the likelihood that the at least one candidate contains a target;”; paragraph [0082] “processing the candidates for finding if more than one candidate belongs to the same target, and where found, candidates of the same target are clustered together;”; paragraph [0083] “tracking at least one candidate, in relation to the at least one cluster, that may belong to the cluster, and where the tracked candidate belongs, adding the tracked candidate to the cluster; determining and classifying the likelihood that the at least one cluster contains a target” paragraph [0211-212] “which it is likely that a pathogen of interest, referred to hereinafter as the "target", appears. One or more of the following methods may be used to detect these candidate patches: a. Pattern matching--if the general form of the target is well defined, a pattern describing this form is constructed in a pre-processing stage: numerous examples of its form are manually collected, and the general pattern is extracted. When processing an image, this pattern is then matched at every location, and those locations which exhibit high similarity to the pattern are taken as candidates”).
Regarding claim 8, which claim 1 is incorporated, Bachelet discloses wherein the bodily sample includes a sample that contains blood, and wherein the computer processor is configured to identify elements as being candidates of the given entity by identifying elements as being candidates of the given entity within the blood (paragraph [0046] “the sample is a slide selected from one or more of the following: a blood smear (thin or thick)”; paragraph [0119] “The terms "bodily material", "bodily fluid", "bodily waste product", "tissue" and "sample" are used interchangeably to refer to a material originating in the human or mammalian body, and from which a portion may be readily removed for analysis for the presence of pathogens or for visually apparent changes related to disease progression. Non-limiting examples include: blood…”; paragraph [0247] “module may be used to identify sample elements that are not the pathogens themselves but are useful in determining pathogen presence. For example, red blood cells may be identified in malaria diagnosis in order to determine whether a suspected target is located within a red blood cell.”).
Regarding claim 9, which claim 8 is incorporated, Bachelet discloses wherein the computer processor is configured to identify elements as being candidates of the given entity by identifying elements as being candidates of an entity selected from the group consisting of: a white blood cell (paragraph [0198] “the resultant images can emphasize pathogen markers. For example, when blood is stained with acridine orange, fluorescence images reveal only white blood cells and parasites”), an anomalous white blood cell (paragraph [0031] “The apparatus wherein at least one of the at least one processor outputs a result that includes at least one of the following: the presence or absence of a pathogen; the species of pathogen; the number or concentration of pathogens detected; the life stage of the pathogen; a finding of anemia; a finding of an unusual white blood cell count; and information on the quality of the sample.”), a red blood cell (paragraph [0247] “module may be used to identify sample elements that are not the pathogens themselves but are useful in determining pathogen presence. For example, red blood cells may be identified in malaria diagnosis in order to determine whether a suspected target is located within a red blood cell”), and a pathogen (paragraph [0031] “The apparatus wherein at least one of the at least one processor outputs a result that includes at least one of the following: the presence or absence of a pathogen; the species of pathogen; the number or concentration of pathogens detected; the life stage of the pathogen).
Regarding claim 10, which claim 8 is incorporated, Bachelet discloses wherein the computer processor is configured to perform a blood count on the sample that contains blood, and the computer processor is configured to generate the output by outputting the blood count. (paragraph [0031] “apparatus wherein at least one of the at least one processor outputs a result that includes at least one of the following:… a finding of an unusual white blood cell count; and information on the quality of the sample.”; paragraph [0267] “software may report medically pertinent information obtained from the biological sample yet unrelated to parasites, (such as detection of anemia, or detection of an unusual white blood-cell count).”).
Regarding claim 11, Bachelet discloses a method comprising: acquiring one or more microscope images of a bodily sample, using a microscope (paragraph [0015] “for an automated apparatus capable of inspecting blood donations or blood samples for the presence of parasitic infection…where the apparatus includes components for automated microscopy, and machine-vision processing for performing automatic identification of pathogens.);
using at least one computer processor (paragraph [0031] “The apparatus wherein at least one of the at least one processor outputs a result that includes at least one of the following:”):
in the one or more images, identifying at least one element as being a candidate of a given entity (paragraph [0017] “provides an apparatus for automatic detection of pathogens within a sample… wherein the processor is adapted to perform image processing using classification algorithms on visual classification features to detect one or more suspected pathogens, when present, in the sample.”; paragraph [0078] “wherein the classification features include one or more of the following: motion, size, shape, coloring, contrast, location in respect to additional biological structures, presence of internal structures, presence of extracellular structures, the aspect ratio, the optical density, florescence at predetermined wavelengths, optical birefringence, clustering behavior, and pattern matching.”);
extracting, from the one or more images, at least one candidate-informative feature associated with the candidate (paragraph [0107] “images of known pathogens are saved in a database, and image processing software of the invention is activated on the images to extract visual characteristics which are typically associated with each known pathogen. Classification features are constructed manually, automatically extracted or refined from a database of known pathogens, or a combination thereof.”);
extracting, from the one or more images, at least one sample-informative feature that is indicative of contextual information related to the bodily sample (paragraph [0125] “the term "candidate" refers to a patch which, during the algorithmic processing stages, is suspected to contain a pathogen.”; paragraph [0126] “Given a novel candidate, the algorithm uses the separation model computed in the previous phase and extracts classification features to determine whether the candidate is a target or not.”);
processing the candidate-informative feature in combination with the sample-informative feature (paragraph [0108] “The apparatus then utilizes image analysis software to locate putative appearances of the pathogen in the image. The apparatus compares the characteristics of a suspected pathogen present in the image, to a succinct set of characteristics extracted from images of known pathogens. The characteristics, termed "classification features" herein, may include, but are not limited to, typical motion of live parasites, their typical shape, size, their coloring, their contrast, and their location with respect to other elements of the biological sample (for example, if the pathogen is located within a mammalian cell)”); and
in response thereto, performing an action selected from the group consisting of: [generating an output] indicating that presence of an infection within the bodily sample could not be determined with a sufficient degree of reliability (Examiner interprets algorithmic decision in Bachelet as degree of reliability. paragraph [0180] “Central to the invention is the use of classification features which are associated with specific pathogens, in order to reach an algorithmic decision whether a pathogen is identified in the sample or not.”),
[generating an output] indicating that a portion of the sample should be re-imaged (paragraph [0148] “with the timing of activation of light source and with image capture of the digital camera, to ensure proper sequence is maintained and to ensure images are initially captured from different areas of the cartridge. Subsequently, when images have been processed and certain areas of the sample have been tagged as requiring additional analysis, when images have been processed and certain areas of the sample have been tagged as requiring additional analysis, controller may move the cartridge support frame 310, may move the stage 320, or may instruct camera to zoom in on these areas, may replace or add optical filters, or may illuminate the area of interest with a different light source to gather additional information.”),
[generating an output] indicating that a portion of the sample should be re-imaged using different settings (paragraph [0148] “controller may move the cartridge support frame 310, may move the stage 320, or may instruct camera to zoom in on these areas, may replace or add optical filters, or may illuminate the area of interest with a different light source to gather additional information.”),
driving the microscope to re-image a portion of the sample (paragraph [0148] “with the timing of activation of light source and with image capture of the digital camera, to ensure proper sequence is maintained and to ensure images are initially captured from different areas of the cartridge. Subsequently, when images have been processed and certain areas of the sample have been tagged as requiring additional analysis, when images have been processed and certain areas of the sample have been tagged as requiring additional analysis, controller may move the cartridge support frame 310, may move the stage 320, or may instruct camera to zoom in on these areas, may replace or add optical filters, or may illuminate the area of interest with a different light source to gather additional information.”),
driving the microscope to re-image a portion of the sample using different settings (paragraph [0148] “controller may move the cartridge support frame 310, may move the stage 320, or may instruct camera to zoom in on these areas, may replace or add optical filters, or may illuminate the area of interest with a different light source to gather additional information.”).
Bachelet fails to teach generating an output and modulating a frame rate at which microscope images are acquired by the microscope.
Beecher teaches generating an output (paragraph [0022] “The display system in each of the user computing systems 114(1-n) is used to show data and information to the user… other types of data and information could be displayed and other manners of providing the information can be used. The display system comprises a computer display screen, such as a CRT or LCD screen by way of example only, although other types and numbers of displays could be used…”) and
modulating a frame rate at which microscope images are acquired by the microscope system (paragraph [0043] “The imaging management system 112 adjusts a video fame rate based on the bandwidth to control the rate at which images are provided between the requested one of the remotely operable microscope systems 110(1-n) and the one or more of the authorized user computing systems”).
Therefore, it would have been obvious to one of ordinary skill of the art before the effective filing date to modify Bachelet’s reference to include generating an output and modulating a frame rate at which microscope images are acquired by the microscope system taught by Beecher’s reference. The motivation for doing so would have been to show the data to the user and to provide multiple views of the specimen as suggested by Beecher (see Beecher paragraph [0019] and paragraph [0043]).
Further, one skilled in the art could have combined the elements described above by known methods with no change to the respective functions, and the combination would have yielded nothing more that predictable results. Therefore, it would have been obvious to combine Beecher with Bachelet to obtain the invention specified in claim 11.
Regarding claim 12 (drawn to a method), claim 12 is rejected the same as claim 2 and the arguments similar to that presented above for claim 2 are equally applicable to the claim 12, and all the other limitations similar to claim 2 are not repeated herein, but incorporated by reference.
Regarding claim 13 (drawn to a method), claim 13 is rejected the same as claim 3 and the arguments similar to that presented above for claim 3 are equally applicable to the claim 13, and all the other limitations similar to claim 3 are not repeated herein, but incorporated by reference.
Regarding claim 14 (drawn to a method), claim 14 is rejected the same as claim 4 and the arguments similar to that presented above for claim 4 are equally applicable to the claim 14, and all the other limitations similar to claim 4 are not repeated herein, but incorporated by reference.
Regarding claim 15 (drawn to a method), claim 15 is rejected the same as claim 5 and the arguments similar to that presented above for claim 5 are equally applicable to the claim 15, and all the other limitations similar to claim 5 are not repeated herein, but incorporated by reference.
Regarding claim 16 (drawn to a method), claim 16 is rejected the same as claim 6 and the arguments similar to that presented above for claim 6 are equally applicable to the claim 16, and all the other limitations similar to claim 6 are not repeated herein, but incorporated by reference.
Regarding claim 17 (drawn to a method), claim 17 is rejected the same as claim 7 and the arguments similar to that presented above for claim 7 are equally applicable to the claim 17, and all the other limitations similar to claim 7 are not repeated herein, but incorporated by reference.
Regarding claim 18 (drawn to a method), claim 18 is rejected the same as claim 8 and the arguments similar to that presented above for claim 8 are equally applicable to the claim 18, and all the other limitations similar to claim 8 are not repeated herein, but incorporated by reference.
Regarding claim 19 (drawn to a method), claim 19 is rejected the same as claim 10 and the arguments similar to that presented above for claim 10 are equally applicable to the claim 19, and all the other limitations similar to claim 10 are not repeated herein, but incorporated by reference.
Regarding claim 20, Bachelet discloses a computer software product, for use with a bodily sample, an output device (paragraph [0031] “The apparatus wherein at least one of the at least one processor outputs a result that includes at least one of the following:”) and a microscope system configured to acquire one or more microscope images of a bodily sample (paragraph [0015] “for an automated apparatus capable of inspecting blood donations or blood samples for the presence of parasitic infection…where the apparatus includes components for automated microscopy, and machine-vision processing for performing automatic identification of pathogens.),
the computer software product comprising a non-transitory computer-readable medium in which program instructions are stored (paragraph [0093] provides computer readable storage medium that includes software capable of performing the image processing method of the invention) ,
which instructions, when read by a computer cause the computer to perform the steps of: in the one or more images, identifying at least one element as being a candidate of a given entity (paragraph [0017] “provides an apparatus for automatic detection of pathogens within a sample… wherein the processor is adapted to perform image processing using classification algorithms on visual classification features to detect one or more suspected pathogens, when present, in the sample.”; paragraph [0078] “wherein the classification features include one or more of the following: motion, size, shape, coloring, contrast, location in respect to additional biological structures, presence of internal structures, presence of extracellular structures, the aspect ratio, the optical density, florescence at predetermined wavelengths, optical birefringence, clustering behavior, and pattern matching.”);
extracting, from the one or more images, at least one candidate-informative feature associated with the candidate (paragraph [0107] “images of known pathogens are saved in a database, and image processing software of the invention is activated on the images to extract visual characteristics which are typically associated with each known pathogen. Classification features are constructed manually, automatically extracted or refined from a database of known pathogens, or a combination thereof.”);
extracting, from the one or more images, at least one sample-informative feature that is indicative of contextual information related to the bodily sample (paragraph [0125] “the term "candidate" refers to a patch which, during the algorithmic processing stages, is suspected to contain a pathogen.”; paragraph [0126] “Given a novel candidate, the algorithm uses the separation model computed in the previous phase and extracts classification features to determine whether the candidate is a target or not.”);
processing the candidate-informative feature in combination with the sample-informative feature (paragraph [0108] “The apparatus then utilizes image analysis software to locate putative appearances of the pathogen in the image. The apparatus compares the characteristics of a suspected pathogen present in the image, to a succinct set of characteristics extracted from images of known pathogens. The characteristics, termed "classification features" herein, may include, but are not limited to, typical motion of live parasites, their typical shape, size, their coloring, their contrast, and their location with respect to other elements of the biological sample (for example, if the pathogen is located within a mammalian cell)”); and
in response thereto, performing an action selected from the group consisting of: [generating an output on the output device] indicating that presence of an infection within the bodily sample could not be determined with a sufficient degree of reliability (Examiner interprets algorithmic decision in Bachelet as degree of reliability. paragraph [0180] “Central to the invention is the use of classification features which are associated with specific pathogens, in order to reach an algorithmic decision whether a pathogen is identified in the sample or not.”),
[generating an output on the output device] indicating that a portion of the sample should be re-imaged (paragraph [0148] “with the timing of activation of light source and with image capture of the digital camera, to ensure proper sequence is maintained and to ensure images are initially captured from different areas of the cartridge. Subsequently, when images have been processed and certain areas of the sample have been tagged as requiring additional analysis, when images have been processed and certain areas of the sample have been tagged as requiring additional analysis, controller may move the cartridge support frame 310, may move the stage 320, or may instruct camera to zoom in on these areas, may replace or add optical filters, or may illuminate the area of interest with a different light source to gather additional information.”),
[generating an output on the output device] indicating that a portion of the sample should be re-imaged using different settings (paragraph [0148] “controller may move the cartridge support frame 310, may move the stage 320, or may instruct camera to zoom in on these areas, may replace or add optical filters, or may illuminate the area of interest with a different light source to gather additional information.”),
driving the microscope system to re-image a portion of the sample (paragraph [0148] “with the timing of activation of light source and with image capture of the digital camera, to ensure proper sequence is maintained and to ensure images are initially captured from different areas of the cartridge. Subsequently, when images have been processed and certain areas of the sample have been tagged as requiring additional analysis, when images have been processed and certain areas of the sample have been tagged as requiring additional analysis, controller may move the cartridge support frame 310, may move the stage 320, or may instruct camera to zoom in on these areas, may replace or add optical filters, or may illuminate the area of interest with a different light source to gather additional information.”),
driving the microscope system to re-image a portion of the sample using different settings (paragraph [0148] “controller may move the cartridge support frame 310, may move the stage 320, or may instruct camera to zoom in on these areas, may replace or add optical filters, or may illuminate the area of interest with a different light source to gather additional information.”),
However, Bachelet fails to teach generating an output on the output device and modulating a frame rate at which microscope images are acquired by the microscope system.
Beecher teaches generating an output on the output device (paragraph [0022] “The display system in each of the user computing systems 114(1-n) is used to show data and information to the user… other types of data and information could be displayed and other manners of providing the information can be used. The display system comprises a computer display screen, such as a CRT or LCD screen by way of example only, although other types and numbers of displays could be used…”) and
modulating a frame rate at which microscope images are acquired by the microscope system (paragraph [0043] “The imaging management system 112 adjusts a video fame rate based on the bandwidth to control the rate at which images are provided between the requested one of the remotely operable microscope systems 110(1-n) and the one or more of the authorized user computing systems”).
Therefore, it would have been obvious to one of ordinary skill of the art before the effective filing date to modify Bachelet’s reference to include generating an output on an output device and modulating a frame rate at which microscope images are acquired by the microscope system taught by Beecher’s reference. The motivation for doing so would have been to show the data to the user and to provide multiple views of the specimen as suggested by Beecher (see Beecher paragraph [0019] and paragraph [0043]).
Further, one skilled in the art could have combined the elements described above by known methods with no change to the respective functions, and the combination would have yielded nothing more that predictable results. Therefore, it would have been obvious to combine Beecher with Bachelet to obtain the invention specified in claim 20.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Kenny et al. (US 2014/0270425 A1) discloses as image quality assessment of microscopic images. The images acquired by a digital microspore are registered and defects are automatically detected by calculating correlations in localized image regions for images acquired in different imaging rounds.
Pollak et al. (WO 2013/098821 A1) discloses detecting a pathogen infection by staining the sample. One dye is used to stain the DNA and at least one other cellular component being different from DNA, and use the stained areas to determine a value or combination of values being indicative of the presence of a suspected pathogen in the bodily sample.
Murugkar et al. (US 2008/0059135 A1) discloses a method and system for monitoring the presence of a pathogen in water using CARS microscopy. The system allows for automatic pathogen detection in moving water in real-time.
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/UROOJ FATIMA/Examiner, Art Unit 2676
/Henok Shiferaw/Supervisory Patent Examiner, Art Unit 2676
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