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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statement (IDS) received on January 15, 2025 has been considered by examiner.
Claim Objections
Claims 1, 2, 12, and 13 are objected to because of the following informalities: “an outputter/outputting or a communicator that outputs the explanation data to outside” should be “an outputter/outputting or a communicator that outputs the explanation data.” The phrase “to outside” is considered redundant. Appropriate correction is required.
Double Patenting
A rejection based on double patenting of the “same invention” type finds its support in the language of 35 U.S.C. 101 which states that “whoever invents or discovers any new and useful process... may obtain a patent therefor...” (Emphasis added). Thus, the term “same invention,” in this context, means an invention drawn to identical subject matter. See Miller v. Eagle Mfg. Co., 151 U.S. 186 (1894); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Ockert, 245 F.2d 467, 114 USPQ 330 (CCPA 1957).
A statutory type (35 U.S.C. 101) double patenting rejection can be overcome by canceling or amending the claims that are directed to the same invention so they are no longer coextensive in scope. The filing of a terminal disclaimer cannot overcome a double patenting rejection based upon 35 U.S.C. 101.
Claims 1-13 are provisionally rejected under 35 U.S.C. 101 as claiming the same invention as that of claims 1-11 of copending Application No. 19/020,310 (reference application). This is a provisional statutory double patenting rejection since the claims directed to the same invention have not in fact been patented.
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 1-13 are rejected under 35 U.S.C. 101 because the claims are not directed to patent eligible subject matter.
Regarding claim 13, the claim is rejected for being drawn to a transitory propagating signal per se. The United States Patent and Trademark Office (USPTO) is obliged to give claims their broadest reasonable interpretation consistent with the specification during proceedings before the USPTO. See In re Zletz, 893 F.2d 319(Fed. Cir. 1989)(during patent examination the pending claims must be interpreted as broadly as their terms reasonably allow). The broadest reasonable interpretation of a claim drawn to a computer readable medium (also called machine readable medium and other such variations) typically covers forms of non-transitory tangible media and transitory propagating signals per se in view of the ordinary and customary meaning of computer readable media, particularly when the specification is silent. See MPEP 2111.01. When the broadest reasonable interpretation of a claim covers a signal per se, the claim must be rejected under 35 U.S.C. 101 as covering non-statutory subject matter. See In re Nuijten, 500 F.3d 1346, 1356-57 (Fed. Cir. 2007) (transitory embodiments are not directed to statutory subject matter) and Interim Examination Instructions for Evaluating Subject Matter Eligibility Under 35 U.S.C.101, Aug. 24,2009; p. 2.
The USPTO recognizes that applicants may have claims directed to computer readable media that cover signals per se, which the USPTO must reject under 35 U.S.C.101 as covering both non-statutory subject matter and statutory subject matter. In an effort to assist the patent community in overcoming a rejection or potential rejection under 35 U.S.C. 101 in this situation, the USPTO suggests the following approach. A claim drawn to such a computer readable medium that covers both transitory and non-transitory embodiments may be amended to narrow the claim to cover only statutory embodiments to avoid a rejection under 35 U.S.C. 101 by adding the limitation "non-transitory" to the claim. Cf: Animals -Patentability, 1077 Off Gaz. Pat. Office 24 (April 21, 1987) (suggesting that applicants add the limitation "non-human" to a claim covering a multi-cellular organism to avoid a rejection under 35 U.S.C.101). Such an amendment would typically not raise the issue of new matter, even when the specification is silent because the broadest reasonable interpretation relies on the ordinary and customary meaning that includes signals per se. The limited situations in which such an amendment could raise issues of new matter occur, for example, when the specification does not support a non-transitory embodiment because a signal per se is the only viable embodiment such that the amended claim is impermissibly broadened beyond the supporting disclosure. See, e.g.,Gentry Gallery, Inc. v. Berkline Corp., 134 F.3d 1473 (Fed. Cir. 1998).
Although claim 13 fails to fall under one of the four statutory categories, the claim could potentially be amended. When a claim fails to fall under at least one of the four statutory categories and it appears from Applicant’s disclosure that the claim could be amended to be directed to a statutory category, it should be determined whether the claim wholly embraces a judicially recognized exception, which includes laws of nature, physical phenomena, and abstract ideas, or is it a particular practical application of a judicial exception (See MPEP 2106 I and II).
Claims 1-12 do fall within at least one of the four categories of patent eligible subject matter because the claims recite a machine (i.e., apparatus) and process (i.e., a method).
Although claim 13 fails to fall under one of the four statutory categories, the claim could potentially be amended. Additionally, claims 1-12 fall under at least one of the four statutory categories. Subsequently, it should be determined whether the claim wholly embraces a judicially recognized exception, which includes laws of nature, physical phenomena, and abstract ideas, or is it a particular practical application of a judicial exception (See MPEP 2106 I and II).
Claims 1-13 are directed to a judicial exception (i.e., a law of nature, natural phenomenon, or abstract idea) without significantly more.
Part I: Step 2A, Prong One: Identify the Abstract Idea
Under step 2A, Prong One of the Alice framework, the claims are analyzed to determine if the claims are directed to a judicial exception. MPEP §2106.04(a). The determination consists of a) identifying the specific limitations in the claim that recite an abstract idea; and b) determining whether the identified limitations fall within at least one of the three subject matter groupings of abstract ideas (i.e., mathematical concepts, mental processes, and certain methods of organizing human activity).
The identified limitations of independent claim 1 (in bold and italics) (representative of independent claims 12 and 13) recite:
a hardware processor that acquires a dynamic image obtained by capturing a site including a diagnosis target region of a patient;
a hardware processor that extracts a feature amount through a first process based on the dynamic image;
a hardware processor that makes a determination related to diagnosis through a second process based on a result of machine learning based on the dynamic image; and
a hardware processor that generates explanation data based on the feature amount and the determination related to the diagnosis; and
an outputter or a communicator that outputs the explanation data to outside
The identified limitations, under their broadest reasonable interpretation, cover performance of the limitations in the mind (including observation, evaluation, judgement or opinion) but for the recitation of generic computer components. That is, other than reciting a hardware processor, nothing in the claim elements precludes the steps form practically being performed in the mind. For example, the identified limitations encompass a healthcare professional reviewing medical images to determine a diagnosis of the patient. The claim limitations fall within the Mental Processes groupings of abstract ideas. Thus, the claimed invention recites a judicial exception.
Part I: Step 2A, prong two: additional elements that integrate the judicial exception into a practical application
Under step 2A, Prong Two of the Alice framework, the claims are analyzed to determine whether the claims recite additional elements that integrate the judicial exception into a practical application. In particular, the claims are evaluated to determine if there are additional elements or a combination of elements that apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claims are more than a drafting effort designed to monopolize the judicial exception.
This judicial exception is not integrated into a practical application. As a whole, the processor in the steps is recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Dependent claims 2-11, when analyzed as a whole are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitations fail to establish that the claims are not directed to an abstract idea.
Since these claims are directed to an abstract idea, the Office must determine whether the remaining limitations “do significantly more” than describe the abstract idea.
Part II. Determine whether any Element, or Combination, Amounts to“Significantly More” than the Abstract Idea itself
Under Part II, the steps of the claims, when considered individually and as an ordered combination, do not improve another technology or technical field, do not improve the functioning of the computer itself, and are not enough to qualify as "significantly more". For example, the steps require no more than a conventional computer to perform generic computer functions. As stated above, the processor in the steps is recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component. Therefore, based on the two-part Mayo analysis, there are no meaningful limitations in the claim that transform the exception into a patent eligible application such that the claim amounts to significantly more than the exception itself. Claims 1-13, when considered individually and as an ordered combination, are rejected as ineligible subject matter under 35 U.S.C. 101.
Dependent claims 2-11 when analyzed as a whole are held to be patent ineligible under 35 U.S.C. 101 because the additional claims do no recite significantly more than an abstract idea.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-9, 12, and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Fujiwara et al. (US 2016/0104283 A1) in view of Watanabe et al. (US 2022/0245816 A1).
Regarding claims 1, 12, and 13, Fujiwara discloses an image determination apparatus comprising:
a hardware processor that acquires a dynamic image obtained by capturing a site including a diagnosis target region of a patient (Paragraph [0098]: The base dynamic image acquiring unit 200 acquires a base dynamic image composed of a plurality of frame images…a state of a dynamic period in which a physical state of a target region in a body of the test subject M changes periodically);
a hardware processor that extracts a feature amount through a first process based on the dynamic image (Paragraph [0101]: The image analysis unit 300 performs image analysis processing on the plurality of frame images SI constituting the base dynamic image to obtain an overall analysis value AN in the lung field region as a whole);
a hardware processor that generates explanation data based on the feature amount and the determination related to the diagnosis (Paragraph [0165]: the statistical analysis unit 500 selectively performs the statistical analysis processing on the diagnostic region AR set in Step S5 to obtain the first analysis value ANs, and outputs the generation instruction information ); and
an outputter or a communicator that outputs the explanation data to outside (Paragraph [0165]: the statistical analysis unit 500 selectively performs the statistical analysis processing on the diagnostic region AR set in Step S5 to obtain the first analysis value ANs, and outputs the generation instruction information).
Fujiwara discloses the limitations above. Fujiwara does not explicitly disclose:
a hardware processor that makes a determination related to diagnosis through a second process based on a result of machine learning based on the dynamic image.
Watanabe teaches:
a hardware processor that makes a determination related to diagnosis through a second process based on a result of machine learning based on the dynamic image (Paragraph [0188]: the controller 11 performs machine learning for determining normality or abnormality of the dynamic information on the basis of the case data accumulated in the case database 152 (see FIG. 3) and determines normality or abnormality of the diagnosis target dynamic information on the basis of learning results.).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Fujiwara to disclose a hardware processor that makes a determination related to diagnosis through a second process based on a result of machine learning based on the dynamic image as taught by Watanabe. Fujiwara discloses An image processing apparatus of the present invention includes an image analysis unit that performs image analysis processing on a plurality of frame images constituting a base dynamic image to obtain an overall analysis value (Fujiwara Abstract). Using the machine learning process of Watanabe would provide a more accurate diagnosis when analyzing medical imaging.
Regarding claim 2, Fujiwara discloses the image determination apparatus according to claim 1, further comprising an outputter or a communicator from which the feature amount is output to the outside (Paragraph [0165]).
Regarding claim 3, Fujiwara discloses the image determination apparatus according to claim 1, wherein the hardware processor that makes the determination makes the determination related to diagnosis based on the feature amount and the dynamic image (Paragraph [0171]: information that is proper and significant in diagnosis can be obtained by narrowing down the diagnostic region AR).
Regarding claim 4, Fujiwara discloses the image determination apparatus according to claim 1, wherein the first process is a process based on machine learning or a process based on a rule (Paragraph [0101]:The image analysis processing herein refers to processing to calculate at least one of (i) a luminance change value in corresponding pixels of the plurality of frame images SI, (ii) the distance indicating a size of the lung field region in each of the plurality of frame images SI, ).
Regarding claim 5, Fujiwara discloses the image determination apparatus according to claim 1, wherein the dynamic image is a radiographic image acquired by a radiography apparatus (Paragraph [0056]: The radiographic dynamic image photographing system according to Embodiment 1 photographs a radiographic image of a human body).
Regarding claim 6, Fujiwara discloses the image determination apparatus according to claim 1, wherein the feature amount includes one or more still images making up the dynamic image (Paragraph [0151]: as the diagnostic region AR, the superior lobe of the right lung field with respect to the analysis still image IG1.).
Regarding claim 7, Fujiwara discloses the image determination apparatus according to claim 1, wherein the determination related to the diagnosis is determination of a disease level of a specific disease (Paragraph [0154]: if the first analysis value ANs falls within a range of the reference statistical value SV of the patients with COPD in which COPD is identified, the possibility that the target subject M is suffering from COPD is suggested).
Regarding claim 8, Fujiwara discloses the image determination apparatus according to claim 7,
wherein the specific disease is COPD (Paragraph [0154]);
wherein the disease level is a stage of COPD (Paragraph [0154]); and
wherein the feature amount is at least one of a lung field area, a change rate of the lung field area, a trachea diameter, a change rate of the trachea diameter, a displacement amount of a diaphragm, a change amount of alveoli, an image density, a variance of each change amount, one or more still images making up the dynamic image, and one or more processed still images (Paragraph [0151]: this is the results of setting, as the diagnostic region AR, the superior lobe of the right lung field with respect to the analysis still image IG1.).
Regarding claim 9, Fujiwara discloses the image determination apparatus according to claim 7,
wherein the specific disease is COPD (Paragraph [0154]);
wherein the disease level is a stage of COPD (Paragraph [0154]); and
wherein the feature amount is at least one of a ratio of a magnitude of a movement for each point of a lung field, an area of the entire lung field, an area of the lung field with reduced movement, a ratio of the area of the lung field with reduced movement to the area of the entire lung field, one or more still images making up the dynamic image, and one or more processed still images (Paragraph [0184]: movement of the lung field region is tracked and associated among the frame images SI (or difference images SI′) to automatically obtain the diagnostic region AR ).
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Fujiwara et al. (US 2016/0104283 A1) in view of Watanabe et al. (US 2022/0245816 A1) in view of Zhou et al. (US 2023/0329646 A1).
Regarding claim 10, Fujiwara, in view of Watanabe, does not explicitly disclose image determination apparatus according to claim 7,
wherein the specific disease is tetralogy of Fallot;
wherein the disease level is a backflow rate; and
wherein the feature amount is at least one of a waveform of a pulmonary artery, a heartbeat waveform, one or more still images making up the dynamic image, and one or more processed still images.
Zhou teaches:
wherein the specific disease is tetralogy of Fallot (Paragraph [0275]: More particularly, this figure shows…(d) pulmonary stenosis and regurgitation due to Tetralogy of Fallot (pathologic));
wherein the disease level is a backflow rate ((Paragraph [0275]: More particularly, this figure shows…(d) pulmonary stenosis and regurgitation due to Tetralogy of Fallot (pathologic))); and
wherein the feature amount is at least one of a waveform of a pulmonary artery, a heartbeat waveform, one or more still images making up the dynamic image, and one or more processed still images (Fig. 14; Paragraph [0275]: FIG. 14 shows example image representations comprising spectrograms, MTFs and GAFs for each of a plurality of different types of pediatric heart sounds.).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Fujiwara, in view of Watanabe, to disclose wherein the specific disease is tetralogy of Fallot; wherein the disease level is a backflow rate; and wherein the feature amount is at least one of a waveform of a pulmonary artery, a heartbeat waveform, one or more still images making up the dynamic image, and one or more processed still images as taught by Zhou. Fujiwara, in view of Watanabe, discloses an image processing apparatus of the present invention includes an image analysis unit that performs image analysis processing on a plurality of frame images constituting a base dynamic image to obtain an overall analysis value (Fujiwara Abstract). Using the image representations of Zhou would provide accurate and efficient point-of-care diagnosis.
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Fujiwara et al. (US 2016/0104283 A1) in view of Watanabe et al. (US 2022/0245816 A1) in view of El Sayed et al. (US 2022/0148166 A1).
Regarding claim 11, Fujiwara, in view of Watanabe, does not explicitly disclose image determination apparatus according to claim 7,
wherein the specific disease is CTEPH;
wherein the disease level is a certainty factor; and
wherein the feature amount is at least one of a phase change amount and an amplitude change amount of a blood flow image at each measurement position, one or more still images making up the dynamic image, and one or more processed still images.
El Sayed teaches:
wherein the specific disease is CTEPH (Paragraph [0082]: can be used to perform an operation for use in the diagnosis of CTEPH and the identification of one or more candidate signs or characteristics indicative thereof within an imaging study of a subject patient);
wherein the disease level is a certainty factor (Paragraph [0113]: For example, a classifier, such as a 3-class-cube-level classifier, can be employed to predict whether or not a cube exhibits a risk of chronic pathology ); and
wherein the feature amount is at least one of a phase change amount and an amplitude change amount of a blood flow image at each measurement position, one or more still images making up the dynamic image, and one or more processed still images (Paragraph [0082]: pertains to software trained via machine learning for use in applying pattern recognition techniques to an imaging study performed via computed tomography (CT) or other scanning modalities to identify whether one or more characteristics exist in the cardiac region ).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Fujiwara, in view of Watanabe, to disclose wherein the specific disease is CTEPH; wherein the disease level is a certainty factor; and wherein the feature amount is at least one of a phase change amount and an amplitude change amount of a blood flow image at each measurement position, one or more still images making up the dynamic image, and one or more processed still images as taught by El Sayed. Fujiwara, in view of Watanabe, discloses an image processing apparatus of the present invention includes an image analysis unit that performs image analysis processing on a plurality of frame images constituting a base dynamic image to obtain an overall analysis value (Fujiwara Abstract). Using the systems and methods for assessing a likelihood of CTEPH of El Sayed would provide accurate and efficient point-of-care diagnosis.
Conclusion
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/CHINYERE MPAMUGO/Primary Examiner, Art Unit 3685