DETAILED ACTION
[1] Remarks
I. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
II. Claims 1-17 are pending and have been examined, where claims 1-6 and 8-17 is/are rejected and claim 7 is/are objected. Explanations will be provided below.
III. Inventor and/or assignee search were performed and determined no double patenting rejection(s) is/are necessary.
IV. Patent eligibility (updated in 2019) shown by the following: Claims 1-17 pass patent eligibility test because there is/are no limitation or a combination of limitations amounting to an abstract idea. Also, the following limitation or the combinations of the limitations: “a segmentation module configured to implement a segmentation artificial intelligence model, the segmentation artificial intelligence model configured to generate a segmentation for the obtained non-contrast computed tomography imaging data, the segmentation artificial intelligence model being trained at least with imaging data based on first segmented contrast computed tomography imaging data” effects a transformation or a reduction of a particular article to a different state or thing / adds a specific limitation(s) other than what is well-understood, routine and conventional in the field, or adding unconventional steps that confine the claim to a particular useful application and providing improvements to the technical field of
image segmentation in Deep learning, which recite additional elements that integrate the judicial exception into a practical application and amounting significant more.
V. There are no PCT associated with the current application.
[2] 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.
Claim(s) 1-11 and 16 are interpreted under 35 U.S.C. 112(f) or pre-AIA U.S.C. 112 6th paragraph because of the following reason(s): the claim limitations uses the term “means” or a term used as a substitute for “means” that is a generic placeholder; the term “means” or the generic placeholder is modified by functional language, typically linked by the transition word “for” or another linking word or phrase, such as “configured to” or “so that”; the term “means” or the generic placeholder is not modified by sufficient structure or material for performing the claimed function;
Claim(s) 12-15 and 17 do not require 35 U.S.C. 112(f) or pre-AIA U.S.C. 112 6th paragraph interpretation because they are method claims and / or they are CRM claims.
Upon examination of the specification and claims, the examiner has determined, under the best understanding of the scope of the claim(s), rejection(s) under 35 U.S.C. 112(a)/(b) is not necessitated because of the following reasons: sufficient support are provided in the written description / drawings of the invention.
[3] Grounds of Rejection
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.
35 U.S.C. 101 requires that a claimed invention must fall within one of the four eligible categories of invention (i.e. process, machine, manufacture, or composition of matter) and must not be directed to subject matter encompassing a judicially recognized exception as interpreted by the courts. MPEP 2106. The four eligible categories of invention include: (1) process which is an act, or a series of acts or steps, (2) machine which is an concrete thing, consisting of parts, or of certain devices and combination of devices, (3) manufacture which is an article produced from raw or prepared materials by giving to these materials new forms, qualities, properties, or combinations, whether by hand labor or by machinery, and (4) composition of matter which is all compositions of two or more substances and all composite articles, whether they be the results of chemical union, or of mechanical mixture, or whether they be gases, fluids, powders or solids. MPEP 2106(I).
Claims 14 are rejected under 35 U.S.C. 101 as not falling within one of the four statutory categories of invention because the claimed invention is directed to computer program per se. See MPEP 2106(I). A claim directed toward a non-transitory computer-readable medium having the program encoded thereon establishes a sufficient functional relationship between the program and a computer so as to remove it from the realm of “program per se”. MPEP 2111.05(III). Hence, adding the limitation of “stored on a non-transitory computer-readable medium” would resolve this issue.
Claim Rejections - 35 USC § 102
U.S.C. 102 Conditions for patentability; novelty.
[Editor Note: Applicable to any patent application subject to the first inventor to file provisions of the AIA (see 35 U.S.C. 100 (note) ). See 35 U.S.C. 102 (pre-AIA ) for the law otherwise applicable.]
(a) NOVELTY; PRIOR ART.—A person shall be entitled to a patent unless—
(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; or
(2) the claimed invention was described in a patent issued under section 151 , or in an application for patent published or deemed published under section 122(b) , in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
(b) EXCEPTIONS.—
(1) DISCLOSURES MADE 1 YEAR OR LESS BEFORE THE EFFECTIVE FILING DATE OF THE CLAIMED INVENTION.—A disclosure made 1 year or less before the effective filing date of a claimed invention shall not be prior art to the claimed invention under subsection (a)(1) if—
(A) the disclosure was made by the inventor or joint inventor or by another who obtained the subject matter disclosed directly or indirectly from the inventor or a joint inventor; or
(B) the subject matter disclosed had, before such disclosure, been publicly disclosed by the inventor or a joint inventor or another who obtained the subject matter disclosed directly or indirectly from the inventor or a joint inventor.
(2) DISCLOSURES APPEARING IN APPLICATIONS AND PATENTS.—A disclosure shall not be prior art to a claimed invention under subsection (a)(2) if—
(A) the subject matter disclosed was obtained directly or indirectly from the inventor or a joint inventor;
(B) the subject matter disclosed had, before such subject matter was effectively filed under subsection (a)(2), been publicly disclosed by the inventor or a joint inventor or another who obtained the subject matter disclosed directly or indirectly from the inventor or a joint inventor; or
(C) the subject matter disclosed and the claimed invention, not later than the effective filing date of the claimed invention, were owned by the same person or subject to an obligation of assignment to the same person.
Claims 1, 3-4, 9, and 11-15 are rejected under 35 U.S.C. 102(b)(1) as being anticipated by Huo (Y. Huo et al., "SynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truth," in IEEE Transactions on Medical Imaging, vol. 38, no. 4, pp. 1016-1025, April 2019).
Regarding claim 1, Huo discloses a system for providing an automatic segmentation for non-contrast computed tomography imaging data, the system comprising:
an input data interface configured to obtain imaging data comprising at least non-contrast computed tomography imaging data (see figure 4, training path B, “real CT” is read as the input data, where the dark regions in the CT image are the “non-contrast” region);
a segmentation module configured to implement a segmentation artificial intelligence model, the segmentation artificial intelligence model configured to generate a segmentation for the obtained non-contrast computed tomography imaging data, the segmentation artificial intelligence model being trained at least with imaging data based on first segmented contrast computed tomography imaging data (see figure 4, training path A “CT Seg.” Is read as the segmented image, being trained using the network shown in figure 3 and 4 illustration below):
PNG
media_image1.png
371
1097
media_image1.png
Greyscale
an output data interface configured to output the generated segmentation (see figure 4, segmented CT image).
Regarding claim 3, Huo discloses the system of claim 1, wherein the segmentation artificial intelligence model is configured to implement a segmentation algorithm (see figure 4, segmented CT image, where the AL model segmentation algorithm).
Regarding claim 4, Huo discloses the system of claim 1, further comprising: an image-domain transfer module configured to implement an image-domain transfer artificial intelligence model, the image-domain transfer artificial intelligence model being trained and configured to produce synthetic (see figure 4, the “Generated CT” is read as the synthetic image), segmented non-contrast computed tomography imaging data based on second segmented contrast computed tomography imaging data, the produced segmented non-contrast computed tomography imaging data is used as a training dataset for the training of the segmentation artificial intelligence model (the “Generated CT” is segmented and results is shown as “CT Seg”).
Regarding claim 9, Huo discloses the system of claim 4, further comprising: a database module configured to store the synthetic, segmented non-contrast computed tomography imaging data produced with the image-domain transfer artificial intelligence model (see Training and Testing section, a computer is employed and is stored in a storage device for storing the segmented image):
PNG
media_image2.png
92
512
media_image2.png
Greyscale
.
Regarding claim 11, Huo discloses a computed tomography system, the computed tomography system comprising: a computed tomography device configured to perform a computed tomography and acquire imaging data; and the system of claim 1, wherein the system is configured to obtain the imaging data acquired by the computed tomography device (see A. MRI-to-CT Splenomegaly Synthetic Segmentation for Abdomen, illustration below):
PNG
media_image3.png
207
521
media_image3.png
Greyscale
Regarding claim 12, Huo discloses a computer-implemented method for providing an automatic segmentation for non-contrast computed tomography imaging data, using the system of claim 1, the method comprising: obtaining the imaging data; generating the segmentation; and outputting the generated segmentation (the images are obtained from a CT scanner, see figure 4 illustration below, the segmented image is read as the generated segmentation and output):
PNG
media_image4.png
196
496
media_image4.png
Greyscale
.
Regarding claims 13, see the rationale and rejection for claim 4.
Regarding claim 14, Huo discloses a computer program product comprising executable program code which, when executed by the system, causes the system to perform the computer-implemented method of claim 12 (see Training and Testing section, code instructions are required for running on the NVIDIA GPU):
PNG
media_image2.png
92
512
media_image2.png
Greyscale
Regarding claim 15, Huo discloses a non-transitory computer-readable data storage medium comprising executable program code which, when executed by the system, causes the system to perform the computer-implemented method of claim 12 (see Training and Testing section, code instructions are required for running on the NVIDIA GPU):
PNG
media_image2.png
92
512
media_image2.png
Greyscale
.
Claim Rejections - 35 USC § 103
1. 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.
2. Claims 2 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Huo (Y. Huo et al., "SynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truth," in IEEE Transactions on Medical Imaging, vol. 38, no. 4, pp. 1016-1025, April 2019) in view of KAISER (US 20200066007).
Regarding claim 2, Huo discloses all the limitations of claim 1, but is silent in disclosing the system of claim 1, wherein the segmentation artificial intelligence model is further trained with photon counting based virtual non-contrast computed tomography imaging data.
KAISER discloses the system of claim 1, wherein the segmentation artificial intelligence model is further trained with photon counting based virtual non-contrast computed tomography imaging data (see paragraph 147, the method can provide optimal segmentation data of an anatomical structure based on photon-counting spectral computed tomography data, where the optimal segmentation can be obtained by applying the segmentation algorithm onto the medical image data that was calculated based on the photon-counting spectral computed tomography and the optimal energy bin parameter set).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include photon counting in order to provides superior spectral separation and limits electronic noise, which offers improved spatial and contrast resolution. Also, this allows radiologists can subsequently reconstruct the CT image on-demand, reducing scan time.
Regarding claim 17 see the rationale and rejection for claim 2.
3. Claims 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Huo (Y. Huo et al., "SynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truth," in IEEE Transactions on Medical Imaging, vol. 38, no. 4, pp. 1016-1025, April 2019) in view of Xia et al. (Wenjun Xia, Wenxiang Cong, Ge Wang, Patch-Based Denoising Diffusion Probabilistic Model for Sparse-View CT Reconstruction, arXiv, 18 Nov 2022).
Regarding claim 5, Huo discloses all the limitations of claim 1, but is silent in disclosing the system of claim 4, wherein the image-domain transfer artificial intelligence model is based on a denoising diffusion probabilistic model. Xia discloses the system of claim 4, wherein the image-domain transfer artificial intelligence model is based on a denoising diffusion probabilistic model (see figure 1 illustration below):
PNG
media_image5.png
218
681
media_image5.png
Greyscale
.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include denoising diffusion probabilistic model because
they offer good anatomical detail and also allowing for the stable, high-fidelity translation of CT images, which can successfully generate tissues, tumors, and bone densities in said CT.
4. Claims 6, 8, 10 and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Huo (Y. Huo et al., "SynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truth," in IEEE Transactions on Medical Imaging, vol. 38, no. 4, pp. 1016-1025, April 2019) in view of SILVER (US 20160371862).
Regarding claim 6, Huo discloses all the limitations of claim 1, but is silent in disclosing the system of claim 4, wherein the image-domain transfer artificial intelligence model is trained with at least one of paired imaging data corresponding to a segmented computed tomography angiography and to a non-contrast computed tomography or with photon counting based virtual non-contrast imaging data.
SILVER discloses the system of claim 4, wherein the image-domain transfer artificial intelligence model is trained with at least one of paired imaging data corresponding to a segmented computed tomography angiography and to a non-contrast computed tomography or with photon counting based virtual non-contrast imaging data (see paragraph 66, recognize that different threshold ranges can be used to either segment out or segment in voxels of the contrast image according to predetermined absorption ranges, in a CT apparatus using dual-energy CT and/or photon-counting detectors, paragraph 53, digital subtraction angiography (DSA), with a fixed viewing angle, a contrast frame is subtracted from a non-contrast mask frame to obtain blood vessel data and eliminate the background of other soft tissues and bone information).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include a segmented computed tomography angiography and to a non-contrast computed tomography allowing medical professionals to use a segmented image to accurately map vascular structures to pinpoint blockages and detect aneurysms, improving diagnostic analysis.
Regarding claim 8, SILVER discloses the system of claim 4, wherein the image-domain transfer module comprises a VNC-generation unit configured to generate virtual non-contrast computed tomography imaging data based on contrast multi-energy computed tomography angiography (see paragraph 66, CT apparatus using dual-energy CT and/or photon-counting detectors, dual energy is read as multi energy CT).
See the motivation for claim 6. Also, including contrast multi-energy computed tomography angiography for reducing patient radiation exposure and can simultaneously provide diagnostic data and reduced scan times.
Regarding claim 10, SILVER discloses the system of claim 1, wherein the obtained non-contrast computed tomography imaging data and the segmented contrast computed tomography imaging data are derived from a computed tomography of blood vessels of a patient (see figure 7C illustration below):
PNG
media_image6.png
231
525
media_image6.png
Greyscale
.
See the motivation for claim 6. Also, imaging data are derived from a computed tomography of blood vessels of a patient in order to allow artificial intelligence models to learn how to generate synthetic contrast images or accurately segment vessels without contrast.
Regarding claim 16 see the rationale and rejection for claim 4.
[4] Claim Objections
Claim(s) 7 is/are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
With regards to claim 7, the examiner cannot find any applicable prior art providing teachings for the following limitation(s): the system of claim 6, wherein the image-domain transfer module comprises a registration unit configured to implement a registration algorithm, wherein the registration algorithm configured to pair the segmented computed tomography angiography imaging data and the non-contrast computed tomography imaging data
in combination with the rest of the limitations of claims 1 and 6.
Regarding claim 7, SILVER discloses the system of claim 6, wherein the image-domain transfer module comprises a registration unit configured to implement a registration algorithm (see figure 12A, 1228 and 1230, angiography and CT image are blended):
PNG
media_image7.png
125
408
media_image7.png
Greyscale
.
SILVER does not disclose the registration algorithm configured to pair the segmented computed tomography angiography imaging data and the non-contrast computed tomography imaging data.
CONTACT INFORMATION
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALEX LIEW (duty station is located in New York City) whose telephone number is (571)272-8623 (FAX 571-273-8623), cell (917)763-1192 or email alexa.liew@uspto.gov. Please note the examiner cannot reply through email unless an internet communication authorization is provided by the applicant. The examiner can be reached anytime.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, MISTRY ONEAL R, can be reached on (313)446-4912. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/ALEX KOK S LIEW/Primary Examiner, Art Unit 2674
Telephone: 571-272-8623
Date: 6/24/26
Prosecution Insights