DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Specification
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
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.
Use of the word “means” (or “step for”) in a claim with functional language creates a rebuttable presumption that the claim element is to be treated in accordance with 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph). The presumption that 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph) is invoked is rebutted when the function is recited with sufficient structure, material, or acts within the claim itself to entirely perform the recited function.
Absence of the word “means” (or “step for”) in a claim creates a rebuttable presumption that the claim element is not to be treated in accordance with 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph). The presumption that 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph) is not invoked is rebutted when the claim element recites function but fails to recite sufficiently definite structure, material or acts to perform that function.
Claim elements in this application that use the word “means” (or “step for”) are presumed to invoke 35 U.S.C. 112(f) except as otherwise indicated in an Office action. Similarly, claim elements that do not use the word “means” (or “step for”) are presumed not to invoke 35 U.S.C. 112(f) except as otherwise indicated in an Office action.
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 limitations use a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are:
a feature amount extraction section,
an importance calculation section,
an image accumulation section of claim 1.
Because these claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have these limitations interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitations to avoid 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 limitations recite sufficient structure to perform the claimed function so as to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
The corresponding structure described in the specification as performing the claimed function, and equivalents thereof of the claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, are a computer controlling the operations of the feature amount extraction section, the importance calculation section, and the image accumulation section of claim 1 (See Applicant’s Specification at paragraph 29).
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.
Claim 20 is directed to data structures embodied on a computer-readable medium. The broadest reasonable interpretation of a claim drawn to a computer-readable medium includes forms of non-transitory tangible media and transitory propagating signals per se in view of the ordinary and customary meaning of computer-readable media. See In re Nuijten, 500 F.3d 1346 (Fed. Cir. 2007). The Applicant’s specification does not limit computer-readable medium to non-transitory embodiments, and therefore claim 20 is non-statutory. The Examiner suggests amending the claims to include "non-transitory computer-readable medium” or similar language.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 5-9, 19 and 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Takehara US Publication 2020/0387756 (hereafter “Takehara”).
Referring to claims 1, 19 and 20, Takehara discloses an image processing device comprising:
a feature amount extraction section that extracts an intermediate feature amount related to machine learning from an input image that is an image inside a body (paragraph 34, The classification evaluation unit 36 reads the learned model from the storage 22, and classifies the object image P by using the learned model);
an importance calculation section that calculates image importance of the input image on a basis of the intermediate feature amount (paragraph 62, The controller 26 causes the classification evaluation unit 36 to calculate the reliability for each of the candidate labels of the object image P based on the learned model (Step S16)); and
an image accumulation section that stores the input image on a basis of the image importance (paragraph 63, if the number of the object images P to which the temporary label is assigned is equal to or larger than the predetermined number (Step S26; Yes), the label assigning unit 40 determines the temporary label as the label (Step S28), and the learning data generation unit 42 adopts the temporary label and the object images P as the learning data (Step S30)).
Referring to claim 5, Takehara discloses wherein the image accumulation section stores the input image in a case where the image importance exceeds a predetermined threshold (paragraph 62, If the maximum reliability is equal to or larger than the first threshold K1 (Step S18; Yes), the classification determination unit 38 determines that the object image P is classified as the candidate label with the maximum reliability, and the label assigning unit 40 determines the candidate label with the maximum reliability as the label of the object image P (Step S20)).
Referring to claim 6, Takehara discloses wherein the image accumulation section changes the predetermined threshold at update timing of a learned model (paragraph 40, it is preferable to reduce the first threshold K1 with an increase in the number of classifications, and increase the first threshold K1 with an increase in the number of learned images in the learned model).
Referring to claim 7, Takehara discloses wherein the image accumulation section changes the predetermined threshold according to a number of times of update of a learned model (paragraph 40, it is preferable to reduce the first threshold K1 with an increase in the number of classifications, and increase the first threshold K1 with an increase in the number of learned images in the learned model).
Referring to claim 8, Takehara discloses wherein the image accumulation section decreases the predetermined threshold at timing at which the number of times of update becomes a predetermined number of times (paragraph 40, it is preferable to reduce the first threshold K1 with an increase in the number of classifications, and increase the first threshold K1 with an increase in the number of learned images in the learned model)
Referring to claim 9, Takehara discloses wherein the image accumulation section stores the input image and the image importance in association with each other (paragraph 38, The classification evaluation unit 36 stores the reliability calculated as above in the storage 22 in association with the object image P).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 2-4 and 10-18 are rejected under 35 U.S.C. 103 as being unpatentable over Takehara US Publication 2020/0387756 as applied to claim 1 above, and further in view of Kobayashi et al. US Publication 2024/0257509 (hereafter “Kobayashi”).
Referring to claim 2, Takehara discloses wherein the importance calculation section calculates the image importance, but does not disclose expressly calculating the importance calculation section calculation on a basis of a difference between the intermediate feature amount of the image inside the body in a first environment and the intermediate feature amount of the input image in a second environment different from the first environment.
Kobayashi discloses wherein the importance calculation section calculates the image importance on a basis of a difference between the intermediate feature amount of the image inside the body in a first environment (paragraph 246, the first learning model 310 may be a learning model trained by using training data including an operative field image imaged in a certain health institute and annotation data (ground truth data) with respect to the operative field image) and the intermediate feature amount of the input image in a second environment different from the first environment (paragraph 246, the second learning model 320 may be a learning model trained by using training data including an operative field image imaged in another health institute and annotation data (ground truth data) with respect to the operative field image).
Before the effective filing date of the claimed invention, it would have obvious to a person of ordinary skill in the art to use images of multiple environments in the calculation of image importance. The motivation for doing so would have been to improve inference by relying on knowledge from multiple sources. Therefore, it would have been obvious to combine Kobayashi with Takehara to obtain the invention as specified in claim 2.
Referring to claim 3, Kobayashi discloses wherein the importance calculation section converts the difference by a predetermined conversion formula and calculates the image importance (paragraph 255, The control unit 201 compares the first score with the second score, and determines whether the first score is greater than or equal to the second score (step S810)).
Referring to claim 4, Kobayashi discloses wherein the first environment is a first hospital (paragraph 246, the first learning model 310 may be a learning model trained by using training data including an operative field image imaged in a certain health institute and annotation data (ground truth data) with respect to the operative field image), and
the second environment is a second hospital different from the first hospital (paragraph 246, the second learning model 320 may be a learning model trained by using training data including an operative field image imaged in another health institute and annotation data (ground truth data) with respect to the operative field image).
Referring to claim 10, Takehara discloses further comprising a display device (paragraph 25, The output unit is, for example, a display and is able to display a captured image or the like), but does not disclose expressly displaying the image importance.
Kobayashi discloses a display device that displays the image importance (paragraph 119, In a case where the recognition result of the loose connective tissue by the first learning model 310 and the recognition result of the nerve tissue by the second learning model 320 overlap with each other, the control unit 201 of the information processing device 200 may derive the recognition result according to the confidence, and may display the recognition result in a display mode according to the confidence. FIG. 9 is a schematic view illustrating a display example of the recognition result according to the confidence).
Before the effective filing date of the claimed invention, it would have obvious to a person of ordinary skill in the art to display the image importance. The motivation for doing so would have been to allow an operator to view the machine learning results to improve the knowledge of the operator. Therefore, it would have been obvious to combine Kobayashi with Takehara to obtain the invention as specified in claim 10.
Referring to claim 11, Kobayashi discloses wherein the display device displays the input image and the image importance (paragraph 119, In a case where the recognition result of the loose connective tissue by the first learning model 310 and the recognition result of the nerve tissue by the second learning model 320 overlap with each other, the control unit 201 of the information processing device 200 may derive the recognition result according to the confidence, and may display the recognition result in a display mode according to the confidence. FIG. 9 is a schematic view illustrating a display example of the recognition result according to the confidence).
Referring to claim 12, Kobayashi discloses wherein the display device displays the input image with the image importance being superimposed thereon (paragraph 119, In a case where the recognition result of the loose connective tissue by the first learning model 310 and the recognition result of the nerve tissue by the second learning model 320 overlap with each other, the control unit 201 of the information processing device 200 may derive the recognition result according to the confidence, and may display the recognition result in a display mode according to the confidence. FIG. 9 is a schematic view illustrating a display example of the recognition result according to the confidence).
Referring to claim 13, Kobayashi discloses wherein the display device displays an image indicating that the image importance exceeds a predetermined threshold (paragraph 108, By extracting the pixel in which the probability of the label output from the softmax layer 313 of the first learning model 310 is the threshold value or more (for example, 60% or more), the control unit 201 is capable of recognizing the loose connective tissue included in the operative field image).
Referring to claim 14, Kobayashi discloses wherein the display device changes a display mode of the image according to the image importance (paragraph 119, the color changes in accordance with the confidence).
Referring to claim 15, Kobayashi discloses wherein the display device displays the input image with the image being superimposed thereon (paragraph 119, In a case where the recognition result of the loose connective tissue by the first learning model 310 and the recognition result of the nerve tissue by the second learning model 320 overlap with each other, the control unit 201 of the information processing device 200 may derive the recognition result according to the confidence, and may display the recognition result in a display mode according to the confidence. FIG. 9 is a schematic view illustrating a display example of the recognition result according to the confidence).
Referring to claim 16, Kobayashi discloses wherein the display device displays the input image, the image importance, and an image indicating that the image importance exceeds a predetermined threshold (paragraph 108, By extracting the pixel in which the probability of the label output from the softmax layer 313 of the first learning model 310 is the threshold value or more (for example, 60% or more), the control unit 201 is capable of recognizing the loose connective tissue included in the operative field image).
Referring to claim 17, Kobayashi discloses wherein the display device changes a display mode of the image according to the image importance (paragraph 119, the color changes in accordance with the confidence).
Referring to claim 18, Takehara discloses wherein the display device displays the input image with the image importance and the image being superimposed thereon (paragraph 119, In a case where the recognition result of the loose connective tissue by the first learning model 310 and the recognition result of the nerve tissue by the second learning model 320 overlap with each other, the control unit 201 of the information processing device 200 may derive the recognition result according to the confidence, and may display the recognition result in a display mode according to the confidence. FIG. 9 is a schematic view illustrating a display example of the recognition result according to the confidence).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PETER K HUNTSINGER whose telephone number is (571)272-7435. The examiner can normally be reached Monday - Friday 8:30 - 5:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Benny Q Tieu can be reached at 571-272-7490. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/PETER K HUNTSINGER/ Primary Examiner, Art Unit 2682