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 .
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.
The USPTO “Interim Guidelines for Examination of Patent Applications for Patent Subject Matter Eligibility” (Official Gazette notice of 22 November 2005), Annex IV, reads as follows:
In contrast, a claimed computer-readable medium encoded with a computer program is a computer element which defines structural and functional interrelationships between the computer program and the rest of the computer which permit the computer program’s functionality to be realized, and is thus statutory See Lowry, 32 F.3d at 1583-84, 32 USPQ2d at 1035.
Claims that recite nothing but the physical characteristics of a form of energy, such as frequency, voltage, or strength of a magnetic field, define energy or magnetism, per se, and as such are nonstatutory natural phenomena. O’Reilly, 56 I.S. (15 How.) at 112-14. Moreover, it does not appear that a claim reciting a signal encoded with functional descriptive material falls within any of the categories of patentable subject matter set forth in Sec. 101.
…a signal does not fall within one of the four statutory classes of Sec 101.
…signal claims are ineligible for patent protection because they do not fall within any of the four statutory classes of Sec. 101.
Claim 20 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter as follows. Claim 20 is drawn to functional descriptive material recorded on one or more computer readable storage media. A computer readable medium can be defined as encompassing statutory medium, but it also encompasses non-statutory subject matter such as a signal or carrier wave.
A “signal” embodying functional descriptive material is neither a process nor a product (i.e., a tangible “thing”) and therefore does not fall within one of the four statutory classes of §101. Rather, “signal” is a form of energy, in the absence of any physical structure of tangible material.
Because the full scope of the claim encompasses non-statutory subject matter, the claim as a whole is non-statutory. The examiner suggests amending the claim to "a non-transitory computer readable medium encoded with a computer program.” Any amendment to the claim should be commensurate with its corresponding disclosure.
It is noted that claims 1-19 are considered eligible subject matter. Even if the claims were considered an abstract idea, the claims contain limitations that provide a practical application, i.e. medical image registration.
Claim Objections
Claim 8 is objected to because of the following informalities: Claim 8 refers to “The image segmentation” in line 3, where the applicant previously claims “image segmentation” multiple times, once in claim 8, line 1 and once in claim 7, line 3. The examiner believes the applicant is referring to the same image segmentation in claim 8, line 1 in which the claims should then state “the image segmentation”. Appropriate correction is required.
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 2-5, 12-18 and 20 are rejected under 35 U.S.C. 102(a)(1) as being unpatentable by U.S. Patent Application Publication No. 20100046821 (Manjeshwar et al).
Regarding claim 1, Manjeshwar et al discloses an image registration method (fig. 4) based on a Histoimage, i.e. PET images that are back projected images (page 3, paragraph 33), comprising: acquiring a to-be-registered image and a reference image of an object, i.e. the images that are registered in fig. 4, step 512, wherein either or both of the to-be-registered image and the reference image is a Histoimage with a Positron Emission Computed Tomography (PET) mode (fig. 4, “PET images”); and performing registration on the to-be-registered image and the reference image (fig. 4, item 512).
Claims 14 and 20 are rejected for the same reasons as claim 1. Thus, the arguments analogous to that presented above for claim 1 are equally applicable to claims 14 and 20. Claims 14 and 20 distinguish from claim 1 only in that claim 14 is an electronic device, comprising a memory, a processor, and a computer program stored in the memory and configured to be executed on the processor, wherein the processor implements the image registration method based on the Histoimage of claim 1, claim 20 is a computer readable storage medium on which a computer program is stored, wherein the computer program is executed by a processor to implement the image registration method based on the Histoimage of claim 1, instead of a method claim Manjeshwar et al teaches further this feature, i.e. an electronic device (fig. 1, 2) comprising a memory (fig. 2, item 244, 234) processor (fig. 2, item 240, 150) and computer program (fig. 2, item 246) that carries out the method of claim 1 (fig. 4) and a computer readable storage medium on which computer program is stored (fig. 2, item 244, 246), the program implementing fig. 4.
Regarding claim 2, Manjeshwar et al discloses acquiring the to-be-registered image and the reference image of the object further comprises: acquiring raw data corresponding to the object in a PET scanning process, i.e. raw data described in page 3, paragraphs 31-33; generating, based on the raw data, a target Histoimage corresponding to the object, i.e. the PET data (fig. 4, item 504, 506, 510); and taking the target Histoimage as the to-be-registered image or the reference image (fig. 4, item 512).
Regarding claim 3, Manjeshwar et al discloses generating, based on the raw data, the target Histoimage corresponding to the object further comprises: generating, based on the raw data, an initial Histoimage corresponding to the object (Fig. 4, item 504); and preprocessing the initial Histoimage to generate the target Histoimage (fig. 4, item 506-510), wherein the preprocessing comprises either or both of correction, i.e. attenuation correction (fig. 4, item 510) and denoising.
Regarding claim 4, Manjeshwar et al discloses preprocessing the initial Histoimage to generate the target Histoimage further comprises: performing the correction on the initial Histoimage to generate the target Histoimage (fig. 4, item 504-510), wherein the correction comprises at least one of a scattering correction, an attenuation correction (fig. 4, item 510), a sensitivity correction, or a random correction.
Regarding claim 5, Manjeshwar et al discloses generating, based on the raw data, the initial Histoimage corresponding to the object further comprises: acquiring annihilation events corresponding to the raw data (Page 1, paragraph 4, page 3, paragraph 33); and performing a back-projection operation on the annihilation events to generate the initial Histoimage (page 3, paragraph 33, TOF data used for imaging).
Claims 15-18 are rejected for the same reasons as claims 2-5, respectively. Thus, the arguments analogous to that presented above for claims 2-5 are equally applicable to claims 15-18. Claims 15-18 distinguish from claims 2-5 only in that they have different dependencies, both of which have been previously rejected. Therefore, prior art applies.
Regarding claim 12, Manjeshwar et al discloses when one of the to-be-registered image or the reference image is the Histoimage with the PET mode, i.e. the PET image of fig. 4, item 504), the other one has a mode different from the PET mode, i.e. a CT mode (fig. 4, item 506), and the registration being the matching of the images in fig. 4, item 508 and as described in page 4, paragraph 40.
Regarding claim 13, Manjeshwar et al discloses when the to-be-registered image is the Histoimage of the PET mode (fig. 4, item 504), the reference image comprises an image with a Computed Tomography (CT) mode (fig. 4, item 506), an image with a Magnetic Resonance Imaging (MRI) mode, or an image with a Single-Photon Emission Computed Tomography (SPECT) mode; or when the reference image is the Histoimage of the PET mode, the to-be-registered image comprises an image with a CT mode, an image with a MRI mode, or an image with a SPECT mode.
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 6 and 19 are rejected under 35 U.S.C. 103(a) as being unpatentable over Manjeshwar et al in view of U.S. Patent Application Publication No. 20190150877 (SUN et al).
Regarding claim 6, Manjeshwar et al discloses all of the claimed elements as set forth above and incorporated herein by reference. Manjeshwar et al further discloses interest in reducing noise (page 1, paragraph 8)
Manjeshwar et al does not disclose expressly preprocessing includes denoising the initial Histoimage by a deep learning network or an image filter, wherein the deep learning network comprises a denoising network or a generation network from a Histoimage to a reconstructed image with Ordered Subsets Expectation Maximization.
SUN et al discloses preprocessing includes denoising the initial Histoimage by a an image filter (Page 16, paragraphs 142-143)
Manjeshwar et al and Sun et al are combinable because they are from the same field of endeavor, i.e. medical imaging.
Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to remove noise in a preprocessing step.
The suggestion/motivation for doing so would have been to provide a more robust method by removing bad data.
Therefore, it would have been obvious to combine the method of Manjeshwar et al with the noise removal of SUN et al to obtain the invention as specified in claim 6.
Claim 19 is rejected for the same reasons as claim 6. Thus, the arguments analogous to that presented above for claim 6 are equally applicable to claim 19. Claim 19 distinguishes from claim 6 only in that they have different dependencies, both of which have been previously rejected. Therefore, prior art applies.
Claims 7 and 8 are rejected under 35 U.S.C. 103(a) as being unpatentable over Manjeshwar et al in view of U.S. Patent Application Publication No. 20170301080 (Yan et al).
Regarding claim 7, Manjeshwar et al discloses all of the claimed elements as set forth above and incorporated herein by reference. Manjeshwar et al further discloses performing registration on the to-be-registered image and the reference image (fig. 4) further comprises: performing image segmentation on the to-be-registered image and the reference image (fig. 4, item 506), performing image registration on a to-be-registered image obtained after the image segmentation and a reference image obtained after the image segmentation (page 4, paragraph 40), and generating deformation vectors in which the two-be-registered image is registered with the reference image (page 5, paragraph 49, fig. 7).
Manjeshwar et al does not disclose expressly a deformation field for the registration.
Yan et al discloses a deformation field for the registration (page 8, paragraph 82).
Manjeshwar et al and Yan et al are combinable because they are from the same field of endeavor, i.e. medical imaging.
Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to use a deformation field.
The suggestion/motivation for doing so would have been to provide a more robust system by taking into account multiple points in the images.
Therefore, it would have been obvious to combine the method of Manjeshwar et al with deformation fields of Yan et al to obtain the invention as specified in claim 7.
Regarding claim 8, Manjeshwar et al discloses the performing image segmentation on the to-be-registered image and the reference image (fig. 4, item 506), performing image registration on the to-be-registered image obtained after the image segmentation and the reference image obtained after the image segmentation (Fig. 4, item 508-514), and generating the deformation vectors in which the to-be-registered image is registered with the reference image (page 5, paragraph 49, fig. 7) further comprises: performing image segmentation on the to-be-registered image and the reference image based on a preset segmentation algorithm, i.e. the algorithm of fig. 4, item 506, and obtaining a first image corresponding to the to-be-registered image and a second image corresponding to the reference image, i.e. the obtained images that are processed in fig. 4 and acquired from fig. 2, item 210; and performing registration between the first image and the second image based on a preset registration algorithm, the registration algorithm of fig. 4, item 508-514, and generating the deformation vectors in which the to-be-registered image is registered with the reference image (page 5, paragraph 49, fig. 7). Yan et al discloses a deformation field for the registration (page 8, paragraph 82).
Claim 9 is rejected under 35 U.S.C. 103(a) as being unpatentable over Manjeshwar et al in view of Yan et al, as applied to claim 8 above, and further in view of U.S. Patent Application Publication NO. 20070280556 (Mullick et al).
Regarding claim 9, Manjeshwar et al (as modified by Yan et al) discloses all of the claimed elements as set forth above and incorporated herein by reference. Manjeshwar et al further discloses performing image segmentation on the to-be-registered image and the reference image based on the preset segmentation algorithm (fig. 4, item 506), and obtaining the first image corresponding to the to-be-registered image and the second image corresponding to the reference image further comprises: segmenting the same regions-of interest within the to-be-registered image and the reference image, wherein the first image and the second image comprise the corresponding regions of interest (page 4, paragraph 38).
Manjeshwar et al (as modified by Yan et al) does not disclose expressly the region of interest is at least one of a head, an upper arm, a lower arm, a thigh, or a lower leg.
Mullick et al discloses region of interest is at least one of a head (fig. 3, item 58, 66), an upper arm, a lower arm, a thigh (fig. 3, item 62, 70), or a lower leg (fig. 3, item 62, 70).
Manjeshwar et al (as modified by Yan et al) & Mullick et al are combinable because they are from the same field of endeavor, i.e. medical imaging.
Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to have a head or leg be a region of interest.
The suggestion/motivation for doing so would have been to provide a more robust method by considering various areas of the body.
Therefore, it would have been obvious to combine Manjeshwar et al (as modified by Yan et al) with the regions of interest of Mullick et al to obtain the invention as specified in claim 9.
Claim 10 is rejected under 35 U.S.C. 103(a) as being unpatentable over Manjeshwar et al in view of Yan et al, as applied to claim 8 above, and further in view of Mullick et al and U.S. Patent Application Publication No. 20190054315 (Isola et al).
Regarding claim 10, Manjeshwar et al (as modified by Yan et al) discloses all of the claimed elements as set forth above and incorporated herein by reference.
Manjeshwar et al further discloses performing image segmentation on the to-be-registered image and the reference image based on the preset segmentation algorithm (fig. 4, item 506), and obtaining the first image corresponding to the to-be-registered image and the second image corresponding to the reference image further comprises: performing region of interest segmentation on the to-be-registered image and the reference image (fig. 4, item 506), obtaining a first region of interest image corresponding to the first image and a second region of interest image corresponding to the second image, i.e. the output of fig. 4, item 506, and performing registration between the first image and the second image based on the preset registration algorithm (fig. 4, items 508-514), and generating the deformation vectors in which the to-be-registered image is registered with the reference image(page 5, paragraph 49, fig. 7) further comprises: performing registration based on the first region of interest image and the second region of interest image (fig. 4, items 508-514 depend on item 506) and obtaining the deformation vectors in which the to-be-registered image is registered with the reference image (page 5, paragraph 49, fig. 7) . Yan et al discloses a deformation field for the registration (page 8, paragraph 82).
Manjeshwar et al (as modified by Yan et al) does not disclose expressly the region of interest is a torso, and further, performing organ segmentation on the first region of interest image and the second region of interest image, and obtaining a first organ mask corresponding to the first image and a second organ mask corresponding to the second image wherein registering two images is performed based on both images regions of interest images, both images organ masks.
Mullick et al discloses the region of interest is a torso (fig. 3, items 68, 60).
Manjeshwar et al (as modified by Yan et al) & Mullick et al are combinable because they are from the same field of endeavor, i.e. medical imaging.
Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to have a head or leg be a region of interest.
The suggestion/motivation for doing so would have been to provide a more robust method by considering various areas of the body.
Manjeshwar et al (as modified by Yan et al and Mullick et al) does not disclose expressly performing organ segmentation on the first region of interest image and the second region of interest image, and obtaining a first organ mask corresponding to the first image and a second organ mask corresponding to the second image wherein registering two images is performed based on both images regions of interest images, both images organ masks
Isola et al discloses performing organ segmentation on the first region of interest image and the second region of interest image (fig. 3, item 104, page 8, paragraph 81), and obtaining a first organ mask corresponding to the first image and a second organ mask corresponding to the second image (page 8, paragraph 81) wherein registering two images is performed based on both images regions of interest images, because the region of interest images are used to find the ORI masks (page 8, paragraph 81), and both images’ organ masks (page 8, paragraph 82)..
Manjeshwar et al (as modified by Yan et al Mullick et al) & Isola et al are combinable because they are from the same field of endeavor, i.e. medical imaging.
Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to use organ masks for further alignment.
The suggestion/motivation for doing so would have been to provide a more accurate method by focusing on relevant data.
Therefore, it would have been obvious to combine Manjeshwar et al (as modified by Yan et al) with the torso segmentation of Mullick et al the organ masks of Isola et al to obtain the invention as specified in claim 10.
Allowable Subject Matter
Claim 11 is 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.
Claim 11 contains allowable subject matter regarding generating the claimed deformation field in which the to-be-registered image is registered with the reference image further comprises: performing registration on at least one of the corresponding claimed body parts between the claimed first image and the claimed second image, and obtaining a first deformation field; performing registration based on the claimed first torso image and the claimed first organ mask, and the claimed second torso image and the claimed second organ mask, and obtaining a second deformation field; and fusing the first deformation field with the second deformation field, and obtaining the deformation field in which the to-be-registered image is registered with of the reference image, wherein performing image segmentation on the to-be-registered image and the reference image based on the claimed preset segmentation algorithm, and obtaining the claimed first and second images comprises: segmenting a torso and claimed body part from the claimed images, obtaining the first and second torso images corresponding to the claimed images, performing organ segmentation on the torso images, and obtaining the first and second organ masks corresponding to the claimed images, wherein the first image and the second image comprise a corresponding torso and claimed corresponding body part; and performing registration between the first image and the second image based on the claimed preset registration algorithm.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Kathleen Yuan Dulaney whose telephone number is (571)272-2902. The examiner can normally be reached M-F: 9AM-5PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Emily Terrell can be reached at 5712703717. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/KATHLEEN Y DULANEY/Primary Examiner, Art Unit 2666 5/14/2026
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