Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 09/20/2024 and 03/31/2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Claim Objections
Claim 20 is objected to because of the following informalities:
Claim 20, which appears to be a claim of a system claim set, is dependent on claim 14, which is a claim of a method claim set. The examiner believes claim 20 should be dependent on claim 15 instead. Appropriate correction is required.
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:
Anatomical region property quantifier introduced in claim 24; and
Medical condition detector/predictor introduced in claim 25;
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.
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 § 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.
Claim(s) 1-4, 6-9, 15-18, 20-23, and 27 is/are rejected under 35 U.S.C. 103 as being unpatentable over us patent application publication no. 2023/0067841 to Saharia et al. (hereinafter Saharia) in view of us patent application publication no. 2022/0327662 to Matsuura et al. (hereinafter Matsuura).
For claims 1 and 27, Saharia as applied teaches a method for super-resolution processing of medical images, the method comprising:
(a) receiving, as input, a medical image of a modality and a first resolution (see, e.g., pars. 45-47 and 163 and FIGS. 1 and 19, which teach receiving an input image of a first resolution);
(b) concatenating the medical image with a noise vector of a desired resolution higher than the first resolution (see, e.g., pars. 48-59 and 77-78 and FIG. 3A, which teach concatenating the input image with a noisy high resolution image including a noise vector);
(c) passing the noise vector concatenated with the medical image though a neural network trained to remove noise and treating an output of the neural network as a new noise vector for use as the noise vector in step (b) (see, e.g., pars. 45-49, 54-57, 60-67, 85-87, 155, and 163-164 and FIGS. 1 and 19, which teach iteratively denoising using a trained neural network, such as Super-Resolution via Repeated Refinement (SR3) model, wherein the neural network predicts the noise vector based on a variance of the added noise from the output of the previous stage of the model); and
(d) repeating steps (b) and (c) a plurality of times to produce an image output from the neural network which comprises a super-resolution version of the medical image having the desired resolution (see, e.g., pars. 46, 60-67, 85-87, 157-158, and 163-171 and FIGS. 1, 18 and 19, which teach iteratively denoising/refining the input image to produce the enhanced version of the input image having a second resolution greater than the first resolution).
While Saharia does not explicitly teaches that the input image is a medical image of a modality, Matsuura in the analogous art teaches using, as an input of a noise-reduction super-resolution model, a medical image of a modality, such as a scanned image of a subject (see, e.g., pars. 79-83 and FIG. 2 of Matsuura).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Saharia to use a medical image of a modality as taught by Matsuura because Saharia suggests using image super-resolution on medical images (see, e.g., par. 34 of Saharia).
For claims 2 and 16, while Saharia does not explicitly teach, Matsuura in the analogous art teaches that the modality is computed tomography (CT) (see, e.g., pars. 45 and 91-95 and FIG. 2 of Matsuura).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Saharia to use a CT apparatus as taught by Matsuura because Saharia suggests using image super-resolution on medical images (see, e.g., par. 34 of Saharia).
For claims 3 and 17, while Saharia does not explicitly teach, Matsuura in the analogous art teaches that the modality is magnetic resonance (MR) (see, e.g., pars. 45 and 115 of Matsuura).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Saharia to use an MRI apparatus as taught by Matsuura because Saharia suggests using image super-resolution on medical images (see, e.g., par. 34 of Saharia).
For claims 4 and 18, while Saharia as applied does not explicitly teach, Matsuura in the analogous art teaches that the modality is positron emission tomography (PET) (see, e.g., pars. 45 and 115 of Matsuura).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Saharia to use a PET apparatus as taught by Matsuura because Saharia suggests using image super-resolution on medical images (see, e.g., par. 34 of Saharia).
For claims 6 and 20, while Saharia does not explicitly teach, Matsuura in the analogous art teaches that the modality is x-ray (see, e.g., pars. 45 and 115 of Matsuura).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Saharia to use an X-ray apparatus as taught by Matsuura because Saharia suggests using image super-resolution on medical images (see, e.g., par. 34 of Saharia).
For claims 7 and 21, Saharia in view of Matsuura teaches that the trained neural network comprises a U-Net encoder decoder with skip connections (see, e.g., pars. 32 and 77 and FIGS. 3A-B of Saharia).
For claims 8 and 22, Saharia in view of Matsuura teaches that the neural network implements a denoising diffusion probabilistic model (DDPM) (see, e.g., pars. 45-46, 78, 156, and 166 of Saharia, which teach that the neural network is based on a DDPM).
For claims 9 and 23, Saharia in view of Matsuura teaches that repeating steps (b) and (c) a plurality of times includes repeating steps (b) and (c) a number of times based on a number of iterations required to achieve a desired value of a loss function during training of the neural network (see, e.g., pars. 38, 42 and 160 of Saharia, which teach that the series of iterative refinement steps are trained with a regression loss, and that the loss function may be optimized).
For claim 15, Saharia as applied teaches a system for super-resolution processing of medical images (see, e.g., FIGS. 16-17), the system comprising:
at least one processor (see, e.g., pars. 134-136 and FIGS. 16-17); and
a super-resolution image generator implemented by the at least one processor for
receiving, as input, a medical image of a modality and a first resolution (see, e.g., pars. 45-47 and 163 and FIGS. 1 and 19, which teach receiving an input image of a first resolution),
concatenating the medical image with a noise vector of a desired resolution higher than the first resolution (see, e.g., pars. 48-59 and 77-78 and FIG. 3A, which teach concatenating the input image with a noisy high resolution image including a noise vector),
passing the noise vector concatenated with the medical image though a neural network trained to remove noise and treating an output of the neural network as a new noise vector for use as the noise vector (see, e.g., pars. 45-49, 54-57, 60-67, 85-87, 155, and 163-164 and FIGS. 1 and 19, which teach iteratively denoising using a trained neural network, such as Super-Resolution via Repeated Refinement (SR3) model, wherein the neural network predicts the noise vector based on a variance of the added noise from the output of the previous stage of the model), and
repeating the concatenating and passing a plurality of times to produce an image output from the neural network which comprises a super- resolution version of the medical image having the desired resolution (see, e.g., pars. 46, 60-67, 85-87, 157-158, and 163- 171 and FIGS. 1, 18 and 19, which teach iteratively denoising/refining the input image to produce the enhanced version of the input image having a second resolution greater than the first resolution).
While Saharia does not explicitly teaches that the input image is a medical image of a modality, Matsuura in the analogous art teaches using, as an input of a noise-reduction super-resolution model, a medical image of a modality, such as a scanned image of a subject (see, e.g., pars. 79-83 and FIG. 2 of Matsuura).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Saharia to use a medical image of a modality as taught by Matsuura because Saharia suggests using image super-resolution on medical images (see, e.g., par. 34 of Saharia).
Claim(s) 5 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Saharia in view of Matsuura and further in view of us patent application publication no. 2022/0253977 to Lyu.
For claims 5 and 19, while Saharia in view of Matsuura does not explicitly teach, Lyu in the analogous art teaches that wherein the modality is ultrasound (see, e.g., pars. 3 and 104 of Lyu).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Saharia in view of Matsuura to use an ultrasound apparatus as taught by Lyu because Saharia suggests using image super-resolution on medical images (see, e.g., par. 34 of Saharia).
Claim(s) 10-13 and 24-25 is/are rejected under 35 U.S.C. 103 as being unpatentable over Saharia in view of Matsuura and further in view of us patent application publication no. 2018/0018766 to Jang et al. (hereinafter Jang).
For claims 10 and 24, while Saharia in view of Matsuura does not explicitly teach, Jang in the analogous art teaches generating a measurement of a physiological, structural, or mechanical property of an anatomical region depicted in the super-resolution image (see, e.g., pars. 14, 16, 45-46, 64-67, 102, 108, and 124 of Jang, which teach calculating bone stiffness using a high-resolution image and the finite element method).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Saharia in view of Matsuura to determine the bone microstructure because doing so would allow ascertaining osteoporosis expression portion and increasing the reliability of early diagnosis (see pars. 108 and 124 of Jang).
For claim 11, while Saharia in view of Matsuura does not explicitly teach, Jang in the analogous art teaches that the anatomical region comprises a bone and generating the measurement of the mechanical property is achieved using finite element analysis (see, e.g., pars. 14, 16, 45-46, 64-67, 102,108, and 124 of Jang, which teach calculating bone stiffness using a high-resolution image and the finite element method).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Saharia in view of Matsuura to determine the bone microstructure because doing so would allow ascertaining osteoporosis expression portion and increasing the reliability of early diagnosis (see pars. 108 and 124 of Jang).
For claim 12, while Saharia in view of Matsuura does not explicitly teach, Jang in the analogous art teaches using the super-resolution image to predict a future medical condition of the subject (see, e.g., pars. 14-15, 49, 108, and 124 of Jang, which teach making an early diagnosis of a lesion, e.g., osteoporosis, using a high-resolution image and the finite element method).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Saharia in view of Matsuura to determine the bone microstructure because doing so would allow ascertaining osteoporosis expression portion and increasing the reliability of early diagnosis (see pars. 108 and 124 of Jang).
For claims 13 and 25, while Saharia in view of Matsuura does not explicitly teach, Jang in the analogous art teaches using the super-resolution image to detect a current medical condition of the subject (see, e.g., pars. 14-15, 49, 108, and 124 of Jang, which teach diagnosing osteoporosis, using a high-resolution image and the finite element method).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Saharia in view of Matsuura to determine the bone microstructure because doing so would allow ascertaining osteoporosis expression portion and increasing the reliability of early diagnosis (see pars. 108 and 124 of Jang).
Claim(s) 14 and 26 is/are rejected under 35 U.S.C. 103 as being unpatentable over Saharia in view of Matsuura and further in view of us patent application publication no. 2019/0365341 to Chan et al. (hereinafter Chan).
For claim 14, while Saharia in view of Matsuura teaches performing steps (a)-(d) to generate a plurality of 2D super-resolution image slices (see, e.g., pars. 46, 60-67, 85-87, 157-158, and 163- 171 and FIGS. 1, 18 and 19 of Saharia), it does not explicitly teach generating a plurality of the 2D images to generate a 3D super-resolution image. Chan in the analogous art teaches stacking denoised 2D images to generate a high quality 3D image (see, e.g., pars. 62-69 and FIG. 4 of Chan).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Saharia in view of Matsuura to generate a 3D image as taught by Chan because doing so would yield predictable results of providing an image that provides volume and spatial realism (see MPEP 2143(I)(D)).
For claim 26, while Saharia in view of Matsuura teaches that the super-resolution image generator is configured to generate a plurality of 2D super-resolution image slices of a 3D super-resolution image (see, e.g., pars. 46, 60-67, 85-87, 157-158, and 163- 171 and FIGS. 1, 18 and 19 of Saharia), it does not explicitly teach that the plurality of the 2D images are of a 3D super- resolution image. Chan in the analogous art teaches that denoised 2D images are part of a high quality 3D image (see, e.g., pars. 62-69 and FIG. 4 of Chan).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Saharia in view of Matsuura to generate a 3D image as taught by Chan because doing so would yield predictable results of providing an image that provides volume and spatial realism (see MPEP 2143(I)(D)).
Additional Citations
The following table lists several references that are relevant to the subject matter claimed and disclosed in this Application. The references are not relied on by the Examiner, but are provided to assist the Applicant in responding to this Office action.
Citation
Relevance
Dala-Krishna (us pat. pub. 2009/0005679)
Describes methods for processing two-dimensional ultrasound images from an intracardiac ultrasound imaging catheter that provide improved image quality and enable generating three-dimensional composite images of the heart. Two-dimensional ultrasound images are obtained and stored in conjunction with correlating information, such as time or an electrocardiogram. Images related to particular conditions or configurations of the heart can be processed in combination to reduce image noise and increase resolution. Images may be processed to recognize structure edges, and the location of structure edges used to generate cartoon rendered images of the structure. Structure locations may be averaged over several images to remove noise, distortions and blurring from movement.
Petrov et al. (us pat. pub. 2022/0351387)
Describes generally techniques relate to estimating a size of a biological anomaly depicted in a medical image by using a neural network (e.g., a Generator network) to generate a fake version of the image that lacks the anomaly and subtracting the fake image from the medical image. The Generator network can be trained by training a Generative Adversarial Network (GAN) (e.g., a Recycle-GAN or Cycle-GAN) that includes the Generator network.
Lee et al. (us pat. pub. 2022/0028154)
Describes a three-dimensional reconstructing method of a 2D medical image. A three-dimensional reconstructing device includes: a communicator for receiving sequential 2D images with an arbitrary slice gap; a sliced image generator for generating at least one sliced image positioned between the 2D images based on a feature point of the adjacent 2D images; and a controller for reconstructing the 2D image into a 3D image by use of the generated sliced image and providing the 3D image.
Table 1
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See Table 1 and form 892.
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/WOO C RHIM/Examiner, Art Unit 2676
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