DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This action is in response to the application filed 12/07/2024.
Claims 1-20 are currently pending and have been examined.
Claim Objections
Claim 1 is objected to because of the following informalities: “comprising the adjusted at least a device parameter” is not grammatically correct. Appropriate correction is required.
Claim 11 is objected to because of the following informalities: “comprising the adjusted at least a device parameter” is not grammatically correct. Appropriate correction is required.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Where applicant acts as his or her own lexicographer to specifically define a term of a claim contrary to its ordinary meaning, the written description must clearly redefine the claim term and set forth the uncommon definition so as to put one reasonably skilled in the art on notice that the applicant intended to so redefine that claim term. Process Control Corp. v. HydReclaim Corp., 190 F.3d 1350, 1357, 52 USPQ2d 1029, 1033 (Fed. Cir. 1999). The term “function” in claims 1-20 is used by the claim to mean “input/output,” while the accepted meaning is “a relationship of variables.” The term is indefinite because the specification does not clearly redefine the term.
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., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claims 1-20 are drawn to a method and an apparatus which are statutory categories of invention (Step 1: YES).
Independent claims 1 and 11 recite: identifying regions of interest during slide digitization, configured to scan pathology slides; generate, an initial scan of at least a pathology slide receive a user dataset associated with the at least a pathology slide; identify one or more regions of interest within the at least a pathology slide as a function of the user dataset, wherein identifying the one or more regions of interest within the at least a pathology slide comprises: generating the one or more regions of interest as a function of the user dataset; determine at least a scan parameter, wherein determining the at least a scan parameter comprises identifying a first scan parameter as a function of the one or more regions of interest; adjust at least a device parameter as a function of the at least a scan parameter and the one or more regions of interest; and generate a digitized slide by scanning the at least a pathology slide comprising the adjusted at least a device parameter.
The recited limitations, as drafted, under their broadest reasonable interpretation, cover certain methods of organizing human activity between a user and a patient, as reflected in the specification, which states that “This comprehensive data provides a complete overview of a patient's health and facilitates informed decision-making. EHRs 116 may include a patient's past and current medical conditions, surgeries, allergies, immunization records, medications, and any significant health events. EHRs 116 may additionally include a large amount of information regarding the patient's health background. This may include previous diagnosis, medical tests, medical imaging, and the like. EHRs 116 may include documentation, observations, assessments, and treatment plans from medical professionals…For example, and without limitation, the user or a third party may manually input EHRs 116 using a graphical user interface of processor 104 or a remote device, such as for example, a smartphone or laptop. EHRs 116 may additionally be generated via the answer to a series of questions. In a non-limiting embodiment, a user may be prompted to input specific information or may fill out a questionnaire. In an embodiment, a graphical user interface may display a series of questions to prompt a user for information pertaining to the EHRs 116.” (see: specification paragraphs 16-17). If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or relationships or interactions between people, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. The present claims cover certain methods of organizing human activity because they address “Slide digitization offers opportunities for healthcare providers to provide enhanced patient care in a faster and more efficient manner” and “a "pathology slide" is a glass slide containing a portion of biopsied biological material from a patient. A pathology slide 112 may include biopsied tissue from a patient” (see: specification paragraphs 3 and 13). Accordingly, the claims recite an abstract idea(s) (Step 2A Prong One: YES).”
The judicial exception is not integrated into a practical application. The claims are abstract but for the inclusion of the additional elements including “apparatus”, “image capture device”, “image sensor”, “at least a processor”, “a memory”, “training an identification machine-learning model using identification training data, wherein the identification training data comprises exemplary user datasets correlated to exemplary regions of interest”, “ are recited at a high level of generality (e.g., that the generating, adjusting, and displaying is performed using generic computer components and a generic machine learning model with instructions are executed to perform the claimed limitations). Such that they amount to no more than mere instructions to apply the exception using generic computer components. See: MPEP 2106.05(f).
Hence, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Accordingly, the claims are directed to an abstract idea (Step 2A Prong Two: NO).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, using the additional elements to perform the abstract idea amounts to no more than mere instructions to apply the exception using generic components. Mere instructions to apply an exception using a generic component cannot provide an inventive concept. See MPEP 2106.05(f).
Further, the claimed additional elements, identified above, are not sufficient to amount to significantly more than the judicial exception because they are generic components that are configured to perform well-understood, routine, and conventional activities previously known to the industry. See MPEP 2106.05(d). Said additional elements are recited at a high level of generality and provide conventional functions that do not add meaningful limits to practicing the abstract idea. The originally filed specification supports this conclusion at Figure 1, Figure 2, Figure 11 and
Paragraph 9, where “Apparatus 100 includes a processor 104. Processor 104 may include any computing device as described in this disclosure, including without limitation a microcontroller, microprocessor, digital signal processor (DSP) and/or system on a chip (SoC) as described in this disclosure. Computing device may include, be included in, and/or communicate with a mobile device such as a mobile telephone or smartphone. Processor 104 may include a single computing device operating independently, or may include two or more computing device operating in concert, in parallel, sequentially or the like; two or more computing devices may be included together in a single computing device or in two or more computing devices.”
Paragraph 9, where “Processor 104 may distribute one or more computing tasks as described below across a plurality of computing devices of computing device, which may operate in parallel, in series, redundantly, or in any other manner used for distribution of tasks or memory between computing devices. Processor 104 may be implemented using a "shared nothing" architecture in which data is cached at the worker, in an embodiment, this may enable scalability of apparatus 100 and/or computing device.”
Paragraph 10, where “With continued reference to FIG. 1, processor 104 may be designed and/or configured to perform any method, method step, or sequence of method steps in any embodiment described in this disclosure, in any order and with any degree of repetition.”
Paragraph 11, where “Memory is communicatively connected to processor 104. Memory may contain instructions configuring processor 104 to perform tasks disclosed in this disclosure. As used in this disclosure, "communicatively connected" means connected by way of a connection, attachment, or linkage between two or more relata which allows for reception and/or transmittance of information therebetween. For example, and without limitation, this connection may be wired or wireless, direct, or indirect, and between two or more components, circuits, devices, systems, apparatus, and the like, which allows for reception and/or transmittance of data and/or signal(s)”
Paragraph 53, where “In a non-limiting example, identification machine-learning model 128 may include a convolutional neural network (CNN.) Identifying one or more ROis 124 using an identification machine-learning model 128 may include training CNN using unique identifier training data and identifying one or more ROis 124 from the user dataset 108 using trained CNN. A "convolutional neural network," for the purpose of this disclosure, is a neural network in which at least one hidden layer is a convolutional layer that convolves inputs to that layer with a subset of inputs known as a "kernel," along with one or more additional layers such as pooling layers, fully connected layers, and the like. In some cases, CNN may include, without limitation, a deep neural network (DNN) extension.”
Paragraph 66, where “As used in the current disclosure, an "image capture device" is a tool engineered to detect electromagnetic radiation, including but not limited to visible light, and to create a visual representation of this radiation. Such a device may incorporate various optical components. Examples of these optics, which are not limited to, encompass spherical lenses, aspherical lenses, reflectors, polarizers, filters, windows, aperture stops, among others. Additionally, an image capture device 140 might feature an image sensor, with examples including, but not restricted to, digital image sensors like charge-coupled device (CCD) sensors and complementary metal-oxide-semiconductor (CMOS) sensors, as well as chemical and analog image sensors, including film. It's also possible for an image capture device 140 to be responsive to electromagnetic radiation beyond the visible spectrum, such as infrared radiation. In a non-limiting example, an image capture device 140 may include an automated microscope.”
Viewing the limitations as an ordered combination, the claims simply instruct the additional elements to implement the concept described above in the identification of abstract idea with route, conventional activity specified at a high level of generality in a particular technological environment.
Hence, the claims as a whole, considering the additional elements individually and as an ordered combination, do not amount to significantly more than the abstract idea (Step 2B: NO).
Dependent claims 2-10, 12-20 when analyzed as a whole, considering the additional elements individually and/or as an ordered combination, are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitations fail to establish that the claims are directed to an abstract idea without significantly more. Claim 2, 5-10, 12, 15-20 recite receiving, identifying, and displaying image data from scans on the generically recited computing device as shown in the parent claims above.
Claims 3 and 13 further recite “training a machine-learning model with a parameter training data, wherein the parameter training data correlates a plurality of regions of interest to a plurality of scan parameters; and identifying the scan parameter as a function of the one or more regions of interest using the trained machine-learning model” , which is recited at a high level of generality (e.g., that the training of the generic machine learning model is using generic computer components with instructions are executed to perform the claimed limitations) as shown in the specification paragraphs 52 and 53. Such that they amount to no more than mere instructions to apply the exception using generic computer components. See: MPEP 2106.05(f).
Claims 4 and 14 further recite “retraining the machine-learning model as a function of the accuracy score and identifying a second scan parameter using the retrained machine-learning model” which is recited at a high level of generality (e.g., that the retraining of the generic machine learning model is using generic computer components with instructions are executed to perform the claimed limitations) as shown in the specification paragraphs 52 and 53. Such that they amount to no more than mere instructions to apply the exception using generic computer components. See: MPEP 2106.05(f).
These claims fail to remedy the deficiencies of their parent claims above, and therefore rejected for at least the same rationale as applied to their parent claims above, and incorporated herein.
Allowable Subject Matter
Claims 1-20 are allowable over the prior art. Similar to its parent case, the independent claims contain the claim limitations of “training an identification machine-learning model using identification training data, wherein the identification training data comprises exemplary user datasets correlated to exemplary regions of interest”, “adjust at least a device parameter of the image capture device as a function of the at least a scan parameter and the one or more regions of interest” and “generate a digitized slide by scanning the at least a pathology slide using the image capture device comprising the adjusted at least a device parameter” which overcomes the previous prior art of Linhart (US 20230068571 A1), Stumpe (US 11594024 B2), and Stumpe (WO 2019/199392 A1). A new prior art search was conducted and found the prior art of Park (US 20210366594 A1) that teaches labeling patient scan data to determine regions of interest, however it does not explicitly teach adjusting scan parameters.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KIMBERLY A SASS whose telephone number is (571)272-4774. The examiner can normally be reached 7AM-5PM (EST).
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, JASON DUNHAM can be reached at 571-272-8109. 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.
/KIMBERLY A. SASS/Examiner, Art Unit 3686
Prosecution Insights