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 .
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
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Claims 2-21 are rejected on the ground of non-statutory obviousness-type double patenting as being un-patentable over claims 1-18 of the U.S Patent No. 12186114. Although the conflicting claims are not identical, they are not patentably distinct from each other because they claiming the same subject matter. Furthermore claims 1-18 of the US Patent 12186114 include all the limitation recited in the claims of 2-21 of the instant application.
Regarding independent claim 2, claim 1 of the US Patent 12186114 recite the following limitations:
An image harmonization method for a brain (US Patent 12186114, claim 1, lines 1-2), the method comprising:
providing an original PET image of the brain using an original PET tracer (US Patent 12186114, claim 1, lines 3-4);
providing a target PET tracer (US Patent 12186114, claim 1, line 5); and
converting, using a deep learning neural network, the original PET image into a target PET image simulating an image that would be obtained had the target PET tracer been used (US Patent 12186114, claim 1, lines 6-9),
wherein the deep learning neural network comprises at least one residual block (US Patent 12186114, claim 1, lines 12-13)
wherein the at least one residual block comprises one or more encoding blocks, and wherein each encoding block receives a first input matrix, and each encoding block (US Patent 12186114, claim 1, lines 12-16) comprises:
a first convolutional path, wherein the first convolutional path receives the first input matrix and generates a second output matrix (US Patent 12186114, claim 1, lines 18-23), and
a second convolutional path comprising a first kernel, wherein the second convolutional path comprises a first filter bank and generates a third output matrix (US Patent 12186114, claim 1, lines 26-28)
wherein each encoding block (i) sums together the second output matrix and the third output matrix resulting in a first summed matrix, (ii) down-samples the first summed matrix, and (iii) generates a fourth output matrix (US Patent 12186114, claim 1, lines 30-35).
Therefore independent claim 2 of the instant application obvious in view of claim 1 of the US Patent no. 12186114.
Regarding independent claim 7, similarly the limitations recited in independent claim 14 of the US Patent 12186114 includes limitation recited in independent claim 7 of the instant application, therefore independent claim 7 of the instant is obvious in view of claim 14 of the US Patent 12186114.
Regarding independent claim 12, claim 1 of the US Patent 12186114 recite the following limitations:
An image harmonization method for a brain (US Patent 12186114, claim 1, lines 1-2), the method comprising:
providing an original PET image of the brain using an original PET tracer (US Patent 12186114, claim 1, lines 3-4);
providing a target PET tracer (US Patent 12186114, claim 1, line 5); and
converting, using a deep learning neural network, the original PET image into a target PET image simulating an image that would be obtained had the target PET tracer been used (US Patent 12186114, claim 1, lines 6-9),
wherein the original PET tracer and the target PET tracer are different PET tracers (US Patent 1216114, claim 1, lines 6-9 recites converting, using a deep learning neural network, the original PET image into a target PET image simulating an image that would be obtained had the target PET tracer been used. It is obvious that original PET tracer is converted in different form to obtain PET target tracer. Therefore it is obvious that limitation of claim 1 of the US Patent 12186114 includes the original PET tracer and the target PET tracer are different PET tracer).
Regarding dependent claims 3-6, 8-11 and 13-21 of the instant application are similarly also obvious in view of claims of 1-18 of the US Patent 12186114. Dependent claims 3-6, 8-11 and 13-21 recite similar limitations as dependent claims 2-13 and 15-18 of the US Patent 12186114.
The above rejection can be overcome by filing terminal disclaimer.
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 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.
Claims 12-20 are rejected under 35 U.S.C. 103 as being unpatentable over Zaharchuk et al. (US 20200311914).
Regarding claim 12 Zaharchuk disclose An image harmonization for a brain image, the method comprising (Zaharchuk, ABSTRACT, Fig. 15 paragraph 0020, Fig. 15 shows input low dose image block 13 is converted into simulated normal dose image block 118 based on reference normal image blocks 108, 112 and 114 ):
providing an original PET image of the brain using an original PET tracer (Zaharchuk, ABSTRACT, Fig. 15 blocks 101 and 103 obtain input image of low dose Radioactive tracer in a patient and Fig, 1 paragraph 0044 disclose low dose PET brain image and paragraph 0042, standard dose PET image is generated from low dose PET image. This obviously corresponds to providing an original PET image of the brain using an original PET tracer );
providing a target PET tracer (Zaharchuk, ABSTRACT, Fig. 15 blocks 101 and 103 obtain input image of low dose Radioactive tracer in a patient and blocks 102 and 108, disclose normal dose image as reference image and paragraph 0053 disclose/ standard/full dose. This corresponds to providing a target PET tracer ), and
converting, using a deep learning neural network, the original PET image into a target PET image simulating an image that would be obtained had the target PET tracer been used (Zaharchuk, ABSTRACT, Fig. 2B and Fig. 15, Claim 1 and paragraph 0042, states “FIG. 2B shows a deep network that is trained to generate standard-dose PET image, from low-dose PET image and corresponding multi-contrast MR images as multi-modality inputs. As shown, there are N CNN stages and each stage is a block that includes an M convolution layer with KxK kernels. The results are shown for settings with N=7, M=2, K=3. By down-sampling and then up-sampling the image, the network can extract the multi-scale and high-level features from the image. This obviously corresponds to converting, using a deep learning neural network, the original PET image into a target PET image simulating an image that would be obtained had the target PET tracer been used).
the original PET tracer and the target PET tracer are different PET tracers (Zaharchuk, ABSTRACT, Fig. 2B and Fig. 15, Claim 1 and paragraphs 0020 and 0042-044, states “FIG. 2B shows a deep network that is trained to generate standard-dose PET image, from low-dose PET image and corresponding multi-contrast MR images as multi-modality inputs and Fig. 15 shows input low dose image (original) is converted in high dose image (target). In the system Zaharchuk it is obvious that low dose and high dose are different),
Therefore it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to harmonize a brain image, provide original PET image of the brain using an original PET tracer, provide a target PET tracer and convert using a deep learning neural network, the original PET image into a target PET image simulating an image that would be obtained had the target PET tracer been used as disclosed by Zaharchuk because such a system provide reduction of nuclear medicine dose for Positron emission tomography (PET) imaging and thereby by reducing or eliminating the risk of nuclear radiation for the patient.\
Regarding claims 13-14 Zaharchuk disclose the original PET tracer and target PET tracer comprises one of the [C11]- Pittsburgh compound (PIB), florbetapir (FBP), florbetaben (FBB), flutemetamol (FTE), or NAV4694 (NAV). [C1IE Pittsburgh compound (PIB), florbetapir (FBP), florbetaben (FBB), flutemetamol (FTE), or NAV 4694 (NAV) (Zaharchuk, ABSTRACT, paragraph 0012, and Fig. 15 blocks 101, 102, 108 and 118 disclose original PET tracer and target PET tracer. However Zaharchuk has npt explicitly disclose PET tracer comprises one of the [C11]- Pittsburgh compound (PIB), florbetapir (FBP), florbetaben (FBB), flutemetamol (FTE), or NAV4694 (NAV). [C1IE Pittsburgh compound (PIB), florbetapir (FBP), florbetaben (FBB), flutemetamol (FTE), or NAV 4694 (NAV). However these PET tracer are known and it would be obvious to use one of the above the tracers).
Regarding claim 15-16 Zaharchuk disclose the original PET image and target PET image comprises a two-dimensional image (Zaharchuk disclose in paragraph 0020 the original PET image and target PET image comprises a 2-dimensional image).
Regarding claim 17 Zaharchuk disclose the original PET image and target PET image have a size of 256 pixels by 256 pixels (Zaharchuk, Fig. 15 and Figs 9A-9F the original PET image and target PET image, However Zaharchuk has not explicitly disclose pixels size of 256x256, size of PET images having size of 256x256 is conventional therefore it would be obvious to obtain PET images of 256x256)..
Regarding claim 18 the original PET image comprises a three-dimensional image (Zaharchuk disclose in paragraph 0020 the original PET image and target PET image comprises a 3-dimensional image).
Regarding claim 19 Zaharchuk disclose the original PET image is converted into series of images two-dimensional images, each original two-image being converted into target two dimensional images and the target to-dimension mages are recombined to form the target PET images (Zaharchuk in ABSTRACT, claim 1, Fig, 2A-2B, paragraphs 0020 and 0042-044 disclose the original PET image is converted into series of images two-dimensional images, each original two-image being converted a target two dimensional images and the target to-dimension mages are recombined to form the target PET images).
Regarding claim 20 Zaharchuk disclose series of original and target images each comprise coronal, sagittal and axial views (Zaharchuk, paragraph 0042-0044, Fig. 1B and 2B disclose series of 2-D of original brain images and target image of Brain. Zaharchuck has not explicitly disclose each images comprise coronal, sagittal and axial views. However coronal, sagittal and axial views are natural occurring parts of brain image therefore it would be obvious to obtain series of original and target brain images to include coronal, sagittal and axial views).
Allowable Subject Matter
Claims 2-11 and 21 would be allowable over the prior art of record provided that claims 2-11 overcome the obviousness double patenting rejections over claims 1-18 of the US 12186114 by filing the terminal disclaimer.
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ISHRAT I. SHERALI
Examiner
Art Unit 2667
/ISHRAT I SHERALI/Primary Examiner, Art Unit 2667
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