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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on February 29, 2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Drawings
The drawings are objected to because Figure 1C contains elements 120X and 121X, each which are labeled with the words “PE. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Specification
The disclosure is objected to because of the following informalities:
The abstract line 1 capitalizes “Positron Emission Tomography” and this is not a proper noun, thus should not be capitalized.
Similar issue in specification paragraph 0002, paragraph 0005, paragraph 0030, paragraph 0046, paragraph 0047, paragraph 0156, paragraph 0157, paragraph 0158 and paragraph 0160,
Appropriate correction is required.
Claim Objections
Claims 1, 13 and 18 are objected to because of the following informalities:
Claim 1, line 1, “Positron Emission Tomography” is not a proper noun and should not be capitalized
Similar issue in claim 13, line 1 and claim 18, line 1
Claim 18, the limitation beginning with “extracting” connects each piece with semicolons, which instead should be commas so that the “extracting” applies to each of the plurality of 2-D images (i.e. the second and third)
Claim 19, line 2 “in a memory the PET system” should read “in a memory of the PET system”
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-2, 4, 6, 10-13 and 17 (and claims 3, 5, 7-9, 14-16 for inheriting and failing to cure the deficiency of the base claim) are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
General Indefiniteness
Regarding claim 2, the last limitation states, “wherein the PET system is one of a Cherenkov luminescence-based TOF PET system and a Cherenkov luminescence-based PET-CT system.” It is unclear what applicant is trying to claim here. The claim reads as “wherein the PET system is one of” A and B, where it is not possible to be one of both A and B (in that the system cannot be the two different types of claimed imaging systems), but rather should be A or B. Said differently, if applicant is intending to claim that the PET system only contains one of the options, the claim should read “wherein the PET system is one of a Cherenkov luminescence-based TOF PET system or a Cherenkov luminescence-based PET-CT system.”
Relative Terminology:
The term “higher-quality 2-D image” in claims 1, 6 and 12 is a relative term which renders the claim indefinite. The term “higher-quality” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. Specifically, it appears the higher-quality 2-D image is only defined in the claim as “based on Cherenkov radiation detected at bismuth germinate (BGO) crystals of the PET system.” Being that this is the only definition provided, it is unclear if all data detected from the Cherenkov radiation detected at bismuth germinate (BGO) crystals of the PET system are determined to be “higher-quality” or if there is a subset within that data which is regarded as “higher-quality” based on some threshold. For the sake of examination, the examiner will interpret “higher-quality 2-D image” as any image generated using Cherenkov radiation detected at bismuth germinate (BGO) crystals of the PET system.
The term “higher-quality TOF” in claims 1-2, 10-11, 13 and 17 is a relative term which renders the claim indefinite. The term “higher-quality TOF” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. Specifically, it appears the higher-quality TOF data is only defined in the claim as “based on Cherenkov radiation detected at bismuth germinate (BGO) crystals of the PET system.” Being that this is the only definition provided, it is unclear if all data detected from the Cherenkov radiation detected at bismuth germinate (BGO) crystals of the PET system are determined to be “higher-quality” or if there is a subset within that data which is regarded as “higher-quality” based on some threshold. For the sake of examination, the examiner will interpret “higher-quality TOF” data as data in the upper half of a quality analysis.
The term “lower-quality 2-D image” in claims 1, 4, 6 and 12 is a relative term which renders the claim indefinite. The term “lower-quality 2-D image” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. It is unclear what the delineation is between a higher-quality 2-D image and a lower-quality 2-D image; specifically, it is unclear if there is a threshold separating the higher-quality and lower-quality images. The claim notes, “extracting at least one lower-quality 2-D image from a second patient image volume reconstructed using lower-quality TOF patient data acquired from the subject during the scan” however, this definition is further unclear in that the “lower-quality 2-D image” is defined based on another term of degree of “lower-quality TOF.” For the sake of examination, the examiner will interpret “lower-quality 2-D image” as any image not generated using Cherenkov radiation detected at bismuth germinate (BGO) crystals of the PET system.
The term “lower-quality TOF” in claims 1-2, 6, 10-11, 13-14 and 17 is a relative term which renders the claim indefinite. The term “lower-quality TOF” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. It is unclear what the delineation is between a lower-quality TOF and a higher-quality TOF; specifically, it is unclear if there is a threshold separating the higher-quality and lower-quality TOF data. For the sake of examination, the examiner will interpret “lower-quality TOF” data as data in the lower half of a quality analysis.
The term “true” in claims 16-17 is a relative term which renders the claim indefinite. The term “true” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. It is unclear what the difference between a “True TOF capability camera” and a “TOF capability camera” would be. For the sake of examination, the examiner will interpret “True TOF capability camera” as a camera capable of capturing TOF data.
Allowable Subject Matter
Claims 1-17 would be allowable if rewritten or amended to overcome the objections and rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action.
Claims 18-19 would be allowable if rewritten or amended to overcome the objections set forth in this Office action.
Claims 1-12:
The following is a statement of reasons for the indication of allowable subject matter: the closest prior arts of record teach methods of reconstructing PET images while increasing overall image quality. However, none of them alone or in any combination teaches extracting both high quality and low quality images from respective volumes reconstructed from high and low quality TOF data, enhancing an image from the low quality 2D image using a trained model, and merging the enhanced image with the high quality image. The closest prior art being U.S. Publication No. 2022/0343496 to Zhang et al. discloses “A computer-implemented method is provided for improving image quality with shortened acquisition time. The method comprises: determining an accelerated image acquisition parameter for imaging a subject using a medical imaging apparatus; acquiring, using the medical imaging apparatus, a medical image of the subject according to the accelerated image acquisition parameter; applying a deep network model to the medical image to generate a corresponding transformed medical image with improved quality; and combining the medical image and the corresponding transformed medial image using an adaptive mixing algorithm to generate output image (abstract; see also Figure 1).” However, Zhang fails to disclose extracting both high quality and low quality images from respective volumes reconstructed from high and low quality TOF data, enhancing an image from the low quality 2D image using a trained model, and merging the enhanced image with the high quality image.
Claims 13-17:
The following is a statement of reasons for the indication of allowable subject matter: the closest prior arts of record teach methods of reconstructing PET images while increasing overall image quality. However, none of them alone or in any combination teaches classifying TOF data from a Cherenkov radiation detected using BGO crystals into higher and lower quality TOF data, reconstructing an image using the higher-quality TOF, and another image using the lower-quality TOF, inputting the image from the second volume into an image quality enhancement model to output an enhanced 2D image, merging the enhanced 2D image with an unenhanced image form the first volume, and each image volume is reconstructed using kernels optimized for their respective quality TOF data.
The closest prior art Zhang discloses “A computer-implemented method is provided for improving image quality with shortened acquisition time. The method comprises: determining an accelerated image acquisition parameter for imaging a subject using a medical imaging apparatus; acquiring, using the medical imaging apparatus, a medical image of the subject according to the accelerated image acquisition parameter; applying a deep network model to the medical image to generate a corresponding transformed medical image with improved quality; and combining the medical image and the corresponding transformed medial image using an adaptive mixing algorithm to generate output image (abstract; see also Figure 1).”
However, Zhang fails to disclose classifying TOF data from a Cherenkov radiation detected using BGO crystals into higher and lower quality TOF data, reconstructing an image using the higher-quality TOF, and another image using the lower-quality TOF, inputting the image from the second volume into an image quality enhancement model to output an enhanced 2D image, merging the enhanced 2D image with an unenhanced image form the first volume, and each image volume is reconstructed using kernels optimized for their respective quality TOF data.
Claims 18-19:
The following is a statement of reasons for the indication of allowable subject matter: the closest prior arts of record teach methods of reconstructing PET images while increasing overall image quality. However, none of them alone or in any combination teaches reconstructing three separate volumes using 3 kernels, extracting images from each volume, inputting 2D images from the second and third volumes into respective image enhancement models, merging a non-enhanced image with the two enhanced images and generating an enhanced 3D volume. The closest prior art being Li, Siqi, and Guobao Wang. "Deep kernel representation for image reconstruction in PET." IEEE transactions on medical imaging 41.11 (2022): 3029-3038. (hereinafter Li) discloses “Image reconstruction for positron emission tomography (PET) is challenging because of the ill-conditioned tomographic problem and low counting statistics. Kernel methods address this challenge by using kernel representation to incorporate image prior information in the forward model of iterative PET image reconstruction. Existing kernel methods construct the kernels commonly using an empirical process, which may lead to unsatisfactory performance. In this paper, we describe the equivalence between the kernel representation and a trainable neural network model. A deep kernel method is then proposed by exploiting a deep neural network to enable automated learning of an improved kernel model and is directly applicable to single subjects in dynamic PET. (abstract).” However, Li fails to disclose reconstructing three separate volumes using 3 kernels, extracting images from each volume, inputting 2D images from the second and third volumes into respective image enhancement models, merging a non-enhanced image with the two enhanced images and generating an enhanced 3D volume.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
U.S. Patent No. 10,977,841 to Zhu et al. discloses, “ At least one processor (30) is programmed to reconstruct a dataset comprising detected electron-positron annihilation events acquired for a region of interest by the PET scanner to form a reconstructed PET image wherein the reconstruction includes TOF localization of the events along respective LORs using a TOF kernel having a location parameter dependent on At and a TOF kernel width or shape that varies over the region of interest (abstract)”
U.S. Publication No. 2022/0343566 to Peng discloses, “An apparatus for reconstructing a positron emission tomography (PET) image, comprising processing circuitry configured to extract, from raw data obtained from a PET scanner, energy data and timing data associated with a plurality of annihilation events, the extracted energy data and the extracted timing data for each annihilation event corresponding to interactions between each of a pair of gamma rays generated by each annihilation event and one or more gamma ray detectors of the PET scanner, classify each annihilation event based on respective extracted energy data and respective extracted timing data, determine, for each annihilation event and based on a calculated timing resolution of the annihilation event, a width of a time-of-flight kernel, and reconstruct, by processing circuitry, the PET image based on the obtained raw data from the PET scanner and the determined width of the time-of-flight kernel associated with each annihilation event (abstract).”
Contact
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Courtney J. Nelson whose telephone number is (571)272-3956. The examiner can normally be reached Monday - Friday 8:00 - 4:00.
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/COURTNEY JOAN NELSON/Primary Examiner, Art Unit 2661