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 .
Election/Restrictions
Applicant's election with traverse of Species I in the reply filed on 12/01/2025 is acknowledged. The traversal is on the grounds that the species identified in the restriction requirement are related and can be used together, where one process corresponds to a more detailed description of one step in another process. This is not found persuasive because while the related processes can be used together, a finding of related and distinct processes apply in the instant case.
In any of the examples provided by the Applicant, each of the processes 300, 400, 500, and 600, while usable together, are capable of being performed independently of the other processes. That is, as emphasized in MPEP 802.01(II), as long as related inventions as claimed can be made by, or used in, materially different process, the inventions are distinct.
The requirement is still deemed proper and is therefore made FINAL.
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 1-3 and 24 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Salomon, et al., US 20200008770 A1.
Regarding claim 1, Salomon teaches a system for positron emission tomography (PET) imaging ([0026] discloses “With reference to FIG. 1, an illustrative emission imaging system comprises a combined positron emission tomography (PET)/transmission computed tomography (CT) imaging device 8, which includes both a PET imaging gantry or scanner 10 and a CT gantry or scanner 12 mounted with coaxial bores such that a patient may be loaded onto a common patient table 14 and loaded into either the CT gantry 12 for CT imaging or the PET gantry 10 for PET imaging”), comprising:
at least one storage device including a set of instructions; and at least one processor in communication with the at least one storage device, wherein when executing the set of instructions, the at least one processor is configured to direct the system to perform operations ([0008] discloses “an emission imaging data processing device comprises an electronic processor and a non-transitory storage medium storing instructions readable and executable by the electronic processor to perform a respiratory motion signal generation method”) including:
obtaining PET data of a subject collected by a PET scan of the subject and a physiological signal relating to a physiological motion of the subject during the PET scan ([0028] states that “an electronic processor 20 processes emission data 22 acquired by the PET imaging gantry or scanner 10 (comprising LORs in the illustrative PET imaging embodiment, or comprising projections acquired by a gamma camera in an alternative SPECT imaging embodiment) to generate a respiratory motion signal and to generate a reconstructed image”, the physiological signal comprising the respiratory motion signal);
generating, based on the PET data and the physiological signal, a plurality of gated PET images corresponding to a plurality of physiological phases of the subject ([0030] states that “The electronic processor 20 is further programmed by instructions stored on (the same or a different) non-transitory storage medium to perform a respiration-gated image reconstruction process 40 that operates on the emission data 22, the respiratory motion as estimated by the respiratory motion signal generation process 30, and optionally further based on the attenuation map 18, to perform attenuation correction of the reconstructed PET image”. Of note, [0029] states that “The emission imaging data 22 is acquired over a relatively extended period, that is, over a time interval encompassing many breaths performed by the imaging subject, in order to provide enough emission imaging data to achieve an acceptable signal to noise ratio (SNR)” and [0034] stating that “it is expected that the operation 60 will select a relatively small number of the regions of the array of regions 32, e.g. perhaps 10-20 regions or fewer may be selected. These selected regions are expected to be regions that contain at least a portion of a hot spot over at least a portion of the breathing cycle, with the hot spot being positioned in a lung, thoracic diaphragm, or other anatomical feature that moves strongly with respiration”, meaning the respiratory motion signal comprises a plurality of phases of the monitored breathing cycle);
for each of the plurality of physiological phases, generating a first attenuation map of the subject corresponding to the physiological phase based on the gated PET image corresponding to the physiological phase ([0026] states that “The CT gantry 12, if provided, acquires transmission CT images 16 which may, for example, be used to generate an attenuation map 18 by appropriate conversion of the Hounsfield numbers of the CT image 16 to corresponding absorption values at 511 keV (the energy of gamma rays emitted during positron-electron annihilation events”);
for each of the plurality of physiological phases, generating an attenuation corrected gated PET image corresponding to the physiological phase based on the first attenuation map and a portion of the PET data corresponding to the physiological phase ([0030] states “The electronic processor 20 is further programmed by instructions stored on (the same or a different) non-transitory storage medium to perform a respiration-gated image reconstruction process 40 that operates on the emission data 22, the respiratory motion as estimated by the respiratory motion signal generation process 30, and optionally further based on the attenuation map 18, to perform attenuation correction of the reconstructed PET image”) ; and
generating, based on the attenuation corrected gated PET images corresponding to the plurality of physiological phases, a target PET image corresponding to a reference physiological phase among the plurality of physiological phases ([0030] states that “The illustrative respiration-gated image reconstruction process 40 operates to reconstruct a sub-set of the emission data 22 corresponding to a selected respiratory phase (typically end-exhalation, as this phase is quiescent and of long duration) to generate a reconstructed image with reduced blurring due to respiratory motion”, the reconstructed image being the attenuation corrected PET image).
Regarding claim 2, Salomon further teaches wherein the obtaining a physiological signal relating to a physiological motion of the subject during the PET scan includes:
determining a target region of the subject that is affected by the physiological motion of the subject ([0039] states that “Advantageously, the disclosed respiratory motion signal generation method can be performed in real-time after an initial acquisition phase where the most motion-affected regions have been identified”);
determining, based on the PET data, a time activity curve (TAC) corresponding to the target region ([0033] states that “In an operation 52, for each region of the array of regions 32 and for each time interval, a value of a position descriptor is computed. For example, a position descriptor may comprise the centroid of the activity in the region along the z-direction (transaxial position). Additionally or alternatively, a position descriptor may comprise the radial distance of the centroid of the activity in the region from a center of the region in the x-y plane (transverse position). The result of the operation 52 is an activity position versus time curve 54 for each region of the array of regions 32”); and
generating, based on the TAC, the physiological signal of the subject ([0035] states that “In an operation 64 the activity position versus time curves of the regions selected in the operation 60 are combined to generate a respiratory motion signal 66”).
Regarding claim 3, Salomon further teaches wherein the obtaining a physiological signal relating to a physiological motion of the subject during the PET scan includes:
determining a target region that is affected by the physiological motion of the subject ([0039] states that “Advantageously, the disclosed respiratory motion signal generation method can be performed in real-time after an initial acquisition phase where the most motion-affected regions have been identified”);
for each of time points during the PET scan, determining a centroid of distribution (COD) of coincidence events in the target region at the time point based on the PET data ([0010] states “operating the PET or SPECT imaging device to acquire emission data of an imaging subject in an imaging FOV; computing activity maps from the emission data for successive time intervals in a region defined in the imaging FOV; computing a transaxial activity position versus time curve from the activity maps, the transaxial activity position comprising a minimum distance of the centroid of the activity map from an axial anatomical axis (z) of the imaging subject”);
generating, based on the COD corresponding to each of the time points, the physiological signal of the subject ([0010] further states “generating a respiratory motion signal based on at least the transaxial activity position versus time curve”).
Regarding claim 24, Salomon teaches a non-transitory computer readable medium, comprising at least one set of instructions for positron emission tomography (PET) imaging, wherein when executed by one or more processors of a computing device, the at least one set of instructions causes the computing device to perform a method ([0008] discloses “an emission imaging data processing device comprises an electronic processor and a non-transitory storage medium storing instructions readable and executable by the electronic processor to perform a respiratory motion signal generation method…A positron emission tomography (PET) or single photon emission computed tomography (SPECT) imaging device is operated to acquire emission data of an imaging subject in an imaging field of view (FOV)”), the method comprising:
obtaining PET data of a subject collected by a PET scan of the subject and a physiological signal relating to a physiological motion of the subject during the PET scan ([0028] states that “an electronic processor 20 processes emission data 22 acquired by the PET imaging gantry or scanner 10 (comprising LORs in the illustrative PET imaging embodiment, or comprising projections acquired by a gamma camera in an alternative SPECT imaging embodiment) to generate a respiratory motion signal and to generate a reconstructed image”, the physiological signal comprising the respiratory motion signal);
generating, based on the PET data and the physiological signal, a plurality of gated PET images corresponding to a plurality of physiological phases of the subject ([0030] states that “The electronic processor 20 is further programmed by instructions stored on (the same or a different) non-transitory storage medium to perform a respiration-gated image reconstruction process 40 that operates on the emission data 22, the respiratory motion as estimated by the respiratory motion signal generation process 30, and optionally further based on the attenuation map 18, to perform attenuation correction of the reconstructed PET image”. Of note, [0029] states that “The emission imaging data 22 is acquired over a relatively extended period, that is, over a time interval encompassing many breaths performed by the imaging subject, in order to provide enough emission imaging data to achieve an acceptable signal to noise ratio (SNR)” and [0034] stating that “it is expected that the operation 60 will select a relatively small number of the regions of the array of regions 32, e.g. perhaps 10-20 regions or fewer may be selected. These selected regions are expected to be regions that contain at least a portion of a hot spot over at least a portion of the breathing cycle, with the hot spot being positioned in a lung, thoracic diaphragm, or other anatomical feature that moves strongly with respiration”, meaning the respiratory motion signal comprises a plurality of phases of the monitored breathing cycle);
for each of the plurality of physiological phases, generating a first attenuation map of the subject corresponding to the physiological phase based on the gated PET image corresponding to the physiological phase ([0026] states that “The CT gantry 12, if provided, acquires transmission CT images 16 which may, for example, be used to generate an attenuation map 18 by appropriate conversion of the Hounsfield numbers of the CT image 16 to corresponding absorption values at 511 keV (the energy of gamma rays emitted during positron-electron annihilation events”);
for each of the plurality of physiological phases, generating an attenuation corrected gated PET image corresponding to the physiological phase based on the first attenuation map and a portion of the PET data corresponding to the physiological phase ([0030] states “The electronic processor 20 is further programmed by instructions stored on (the same or a different) non-transitory storage medium to perform a respiration-gated image reconstruction process 40 that operates on the emission data 22, the respiratory motion as estimated by the respiratory motion signal generation process 30, and optionally further based on the attenuation map 18, to perform attenuation correction of the reconstructed PET image”) ; and
generating, based on the attenuation corrected gated PET images corresponding to the plurality of physiological phases, a target PET image corresponding to a reference physiological phase among the plurality of physiological phases ([0030] states that “The illustrative respiration-gated image reconstruction process 40 operates to reconstruct a sub-set of the emission data 22 corresponding to a selected respiratory phase (typically end-exhalation, as this phase is quiescent and of long duration) to generate a reconstructed image with reduced blurring due to respiratory motion”, the reconstructed image being the attenuation corrected PET image).
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 4-5 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Salomon in view of Schaefferkoetter, J. US 20230009528 A1.
Regarding claim 4, Salomon teaches all the limitations of claim 1 above.
Salomon fails to teach wherein the for each of the plurality of physiological phases, generating a first attenuation map of the subject corresponding to the physiological phase based on the gated PET image corresponding to the physiological phase ([0026] states that “The CT gantry 12, if provided, acquires transmission CT images 16 which may, for example, be used to generate an attenuation map 18 by appropriate conversion of the Hounsfield numbers of the CT image 16 to corresponding absorption values at 511 keV (the energy of gamma rays emitted during positron-electron annihilation events”) includes: for each of the plurality of physiological phases, generating the first attenuation map of the subject corresponding to the physiological phase by processing the gated PET image corresponding to the physiological phase using an attenuation map generation model, the attenuation map generation model being a trained machine learning model.
However, within the same field of endeavor, Schaefferkoetter teaches a system for reconstructing medical images where gated positron emission tomography (PET) data ([0024]) and anatomical computed tomography (CT) data are acquired and a trained neural network is applied to the PET and CT data to generate and attenuation map to reconstruct a corrected PET image (see abstract), and then a neural network engine 116 receives CT image 137 and PET image 115, and applies a trained neural network, such as a trained deep learning neural network as described herein, to the CT image 137 and the PET image 115 to generate an attenuation map 105, hence teaching “for each of the plurality of physiological phases, generating the first attenuation map of the subject corresponding to the physiological phase by processing the gated PET image corresponding to the physiological phase using an attenuation map generation model, the attenuation map generation model being a trained machine learning model”.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Salomon, wherein for each of the plurality of physiological phases, generating the first attenuation map of the subject corresponding to the physiological phase by processing the gated PET image corresponding to the physiological phase using an attenuation map generation model, the attenuation map generation model being a trained machine learning model, as taught by, Schaefferkoetter, to improve the accuracy and quality of the medical image data ([0003]), with a reasonable expectation of success, as Salomon also strives to improve image accuracy ([0002]) and quality ([0004]).
Regarding claim 5, Salomon in view of Schaefferkoetter teaches all the limitations of claim 4 above.
Salomon fails to teach wherein the attenuation map generation model is generated according to a model training process including: obtaining a plurality of training samples each of which includes a sample gated PET image and a ground truth attenuation map of a sample subject, the sample gated PET image and the ground truth attenuation map corresponding to the same physiological phase of the sample subject; and generating the attenuation map generation model by training a preliminary model using the plurality of training samples.
However, Schaefferkoetter further teaches wherein the attenuation map generation model is generated according to a model training process including: obtaining a plurality of training samples each of which includes a sample gated PET image ([0058] states that “computing device 200 receives CT image data 362 and PET image data 324 from image scanning system 102, and aggregates and stores CT image data 362 and PET image data 324 within data repository 320 to generate PET/CT training data 395. Computing device 200 may then obtain PET/CT training data 395, which comprises CT image data 362 and PET image data 324, and provides the PET/CT training data 395 to neural network engine 116 to train the neural network”) and a ground truth attenuation map of a sample subject, the sample gated PET image and the ground truth attenuation map corresponding to the same physiological phase of the sample subject ([0056] states that “the neural network can be trained based on previously generated CT images and PET images (e.g., ground truth data) during a training period, and further validated during a validation period, such as by comparing attenuation maps 105 to expected attenuation maps”); and generating the attenuation map generation model by training a preliminary model using the plurality of training samples ([0056] states “the neural network can be trained based on previously generated CT images and PET images (e.g., ground truth data) during a training period, and further validated during a validation period, such as by comparing attenuation maps 105 to expected attenuation maps”, meaning that untrained neural network is preliminary model that is then trained to generate the attenuation map).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Salomon, wherein the attenuation map generation model is generated according to a model training process including: obtaining a plurality of training samples each of which includes a sample gated PET image and a ground truth attenuation map of a sample subject, the sample gated PET image and the ground truth attenuation map corresponding to the same physiological phase of the sample subject; and generating the attenuation map generation model by training a preliminary model using the plurality of training samples, as taught by, Schaefferkoetter, to improve the accuracy and quality of the medical image data ([0003]), with a reasonable expectation of success, as Salomon also strives to improve image accuracy ([0002]) and quality ([0004]).
Regarding claim 11, Salomon teaches all the limitations of claim 1 above.
Salomon fails to teach wherein the plurality of gated PET images are non-attenuation corrected (NAC) PET images.
However, Schaefferkoetter further teaches wherein the plurality of gated PET images are non-attenuation corrected (NAC) PET images ([0062] states that “registration engine 406 can include a neural network which takes as input a “moving” anatomy image, e.g. initial attenuation map 403, and the “fixed” uncorrected PET image, e.g., PET image 115. Application of the neural network to the anatomy image and the uncorrected PET image causes a regression of transformation parameters necessary to match the anatomy image (e.g., moving image) to the uncorrected PET image (e.g., fixed image)”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Salomon, wherein the plurality of gated PET images are non-attenuation corrected (NAC) PET images, as taught by, Schaefferkoetter, to improve the accuracy and quality of the medical image data ([0003]), with a reasonable expectation of success, as Salomon also strives to improve image accuracy ([0002]) and quality ([0004]).
Claims 6, 8-9 and 26 are rejected under 35 U.S.C. 103 as being unpatentable over Salomon in view of Feng, et al., US 20210065412 A1.
Regarding claim 6, Salomon teaches all the limitations of claim 1 above.
Salomon does not teach wherein the generating, based on the attenuation corrected gated PET images corresponding to the plurality of physiological phases, a target PET image corresponding to a reference physiological phase among the plurality of physiological phases ([0030] states that “The illustrative respiration-gated image reconstruction process 40 operates to reconstruct a sub-set of the emission data 22 corresponding to a selected respiratory phase (typically end-exhalation, as this phase is quiescent and of long duration) to generate a reconstructed image with reduced blurring due to respiratory motion”, the reconstructed image being the attenuation corrected PET image) includes: determining, from the attenuation corrected gated PET images, a first attenuation corrected gated PET image corresponding to the reference physiological phase and one or more second attenuation corrected gated PET images corresponding to physiological phases other than the reference physiological phase; for each of the one or more second attenuation corrected gated PET images, transforming the second attenuation corrected gated PET image to generate a transformed gated PET image corresponding to the reference physiological phase; and generating, based on the first attenuation corrected gated PET image and the one or more transformed gated PET images, the target PET image.
However, within the same field of endeavor, Feng teaches a system for reconstruct an attenuation corrected PET image corresponding to the target physiological phase based on the target motion vector field, the CT image, and PET data used for the plurality of gated PET images reconstruction (see abstract), including:
determining, from the attenuation corrected gated PET images, a first attenuation corrected gated PET image corresponding to the reference physiological phase and one or more second attenuation corrected gated PET images corresponding to physiological phases other than the reference physiological phase ([0171] states “the data processing system 130 may reconstruct a first gated PET image corresponding to the end-inspiration phase based on a group of gated PET data corresponding to the end-inspiration phase, and reconstruct a second gated PET image corresponding to the end-expiration phase based on a group of gated PET data corresponding the end-expiration phase”);
for each of the one or more second attenuation corrected gated PET images, transforming the second attenuation corrected gated PET image to generate a transformed gated PET image corresponding to the reference physiological phase ([0187] states “In 1308, the data processing system 130 (e.g., the reconstruction unit 520) may reconstruct an attenuation corrected PET image corresponding to the target physiological phase based on the target motion vector field, the CT image, and PET data used for the plurality of gated PET images reconstruction”); and generating, based on the first attenuation corrected gated PET image and the one or more transformed gated PET images, the target PET image ([0188] states “he data processing system 130 may further reconstruct the attenuation corrected PET image corresponding to the target physiological phase based on the physiological phase-matched CT image and the gated PET image (or gated PET data) corresponding to the target physiological phase”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Salomon, determining, from the attenuation corrected gated PET images, a first attenuation corrected gated PET image corresponding to the reference physiological phase and one or more second attenuation corrected gated PET images corresponding to physiological phases other than the reference physiological phase; for each of the one or more second attenuation corrected gated PET images, transforming the second attenuation corrected gated PET image to generate a transformed gated PET image corresponding to the reference physiological phase; and generating, based on the first attenuation corrected gated PET image and the one or more transformed gated PET images, the target PET image, as taught by Feng, to reduce the effect of respiratory and/or cardiac motion of the subject and improve the quality of a PET image reconstructed accordingly [0005], with a reasonable expectation of success, as Salomon also strives to improve image accuracy ([0002]) and quality ([0004]).
Regarding claim 8, Salomon in view of Feng teaches all the limitations of claim 6 above.
Modified Salomon further teaches wherein the for each of the one or more second attenuation corrected gated PET images, transforming the second attenuation corrected gated PET image to generate a transformed gated PET image corresponding to the reference physiological phase includes: determining a target region of the subject that is affected by the physiological motion of the subject ([0039] states that “Advantageously, the disclosed respiratory motion signal generation method can be performed in real-time after an initial acquisition phase where the most motion-affected regions have been identified”);
Salomon fails to teach for each of the one or more second attenuation corrected gated PET images, determining a motion field between a first region of the first attenuation corrected gated PET image corresponding to the target region and a second region of the second attenuation corrected gated PET image corresponding to the target region; and transforming the second region in the second attenuation corrected gated PET image based on the motion field to generate the transformed gated PET image corresponding to the reference physiological phase.
However, Feng further teaches for each of the one or more second attenuation corrected gated PET images, determining a motion field between a first region of the first attenuation corrected gated PET image corresponding to the target region and a second region of the second attenuation corrected gated PET image corresponding to the target region ([0171] further states that “a motion vector field (denoted as M1 and also referred to as a first motion vector field) between the end-inspiration phase and the end-expiration phase may be determined based on the first gated PET image and the second gated PET image (e.g., by registering the first gated PET image with the second gated PET image)”); and
transforming the second region in the second attenuation corrected gated PET image based on the motion field to generate the transformed gated PET image corresponding to the reference physiological phase ([0171] states that “For a respiratory phase other than the end-inspiration phase and the end-expiration phase, a motion vector field (denoted as M2 and also referred to as a second motion vector field) between the end-inspiration phase (or the end-inspiration phase) and the respiratory phase may be determined based on the motion vector field M1”, where the transformation refers to the application of the motion vector field).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Salomon, for each of the one or more second attenuation corrected gated PET images, determining a motion field between a first region of the first attenuation corrected gated PET image corresponding to the target region and a second region of the second attenuation corrected gated PET image corresponding to the target region; and transforming the second region in the second attenuation corrected gated PET image based on the motion field to generate the transformed gated PET image corresponding to the reference physiological phase, as taught by Feng, to reduce the effect of respiratory and/or cardiac motion of the subject and improve the quality of a PET image reconstructed accordingly [0005], with a reasonable expectation of success, as Salomon also strives to improve image accuracy ([0002]) and quality ([0004]).
Regarding claim 9, Salomon teaches all the limitations of claim 1 above.
Salomon fails to teach wherein the operations further include: obtaining a second attenuation map of the subject generated based on a computed tomography (CT) scan of the subject; determining a motion field between the second attenuation map and the first attenuation map corresponding to the reference physiological phase; and generating, based on the motion field and the target PET image, a physiological phase-matched PET image corresponding to the CT scan.
However, Feng further teaches wherein the operations further include: obtaining a second attenuation map of the subject generated based on a computed tomography (CT) scan of the subject ([0101] states “The reconstruction unit 520 may generate an attenuation map including a plurality of attenuation coefficients based on the CT image (or the respiratory phase-matched CT image). The attenuation map may be used to correct the gated PET data”);
determining a motion field between the second attenuation map and the first attenuation map corresponding to the reference physiological phase ([0106] states “The motion vector field determination unit 550 may determine a motion vector field between two images by registering the two images. For example, the motion vector field determination unit 550 may register two gated PET images corresponding to different respiratory phases”); and
generating, based on the motion field and the target PET image, a physiological phase-matched PET image corresponding to the CT scan ([0106] states “the motion vector field determination unit 550 may register one or more gated PET images with a reference gated PET image. The reference gated PET image may be one of the gated PET images corresponding to a reference respiratory phase of a CT image”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Salomon, wherein the operations further include: obtaining a second attenuation map of the subject generated based on a computed tomography (CT) scan of the subject; determining a motion field between the second attenuation map and the first attenuation map corresponding to the reference physiological phase; and generating, based on the motion field and the target PET image, a physiological phase-matched PET image corresponding to the CT scan, as taught by Feng, to reduce the effect of respiratory and/or cardiac motion of the subject and improve the quality of a PET image reconstructed accordingly [0005], with a reasonable expectation of success, as Salomon also strives to improve image accuracy ([0002]) and quality ([0004]).
Regarding claim 26, Salomon teaches all the limitations of claim 1 above.
Salomon fails to teach wherein the operations further comprises: obtaining a second attenuation map of the subject generated based on a computed tomography (CT) scan of the subject; and generating a physiological phase-matched PET image corresponding to the CT scan based on the second attenuation map, the first attenuation map corresponding to the reference physiological phase, and the target PET image.
However, Feng further teaches wherein the operations further comprises: obtaining a second attenuation map of the subject generated based on a computed tomography (CT) scan of the subject ([0101] states “The reconstruction unit 520 may generate an attenuation map including a plurality of attenuation coefficients based on the CT image (or the respiratory phase-matched CT image). The attenuation map may be used to correct the gated PET data”); and
generating a physiological phase-matched PET image corresponding to the CT scan based on the second attenuation map, the first attenuation map corresponding to the reference physiological phase, and the target PET image scan ([0135] states “The reconstruction unit 520 may generate an attenuation map corresponding to the 511 KeV photon rays (e.g., γ rays) based on the tissue attenuation coefficients. The reconstruction unit 520 may then perform an attenuation correction on the gated PET image based on the attenuation map. The attenuation correction of the gated PET image based on the respiratory phase-matched CT image may also be referred to as a phase-matched attenuation correction of the gated PET image (or gated PET data).”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Salomon, wherein the operations further comprises: obtaining a second attenuation map of the subject generated based on a computed tomography (CT) scan of the subject; and generating a physiological phase-matched PET image corresponding to the CT scan based on the second attenuation map, the first attenuation map corresponding to the reference physiological phase, and the target PET image, as taught by Feng, to reduce the effect of respiratory and/or cardiac motion of the subject and improve the quality of a PET image reconstructed accordingly [0005], with a reasonable expectation of success, as Salomon also strives to improve image accuracy ([0002]) and quality ([0004]).
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Salomon in view of Feng, as applied to claim 6 above, and further in view of Schaefferkoetter.
Regarding claim 7, Salomon in view of Feng teaches all the limitations of claim 6 above.
Salomon in view of Feng fails to teach wherein the operations further include: obtaining a second attenuation map of the subject generated based on a computed tomography (CT) scan of the subject; selecting, from the first attenuation maps corresponding to the plurality of physiological phases, a reference attenuation map that has the highest similarity to the second attenuation map; determining the physiological phase corresponding to the reference attenuation map as the reference physiological phase.
However, within the same field of endeavor, Schaefferkoetter teaches a system for reconstructing medical images where gated positron emission tomography (PET) data ([0024]) and anatomical computed tomography (CT) data are acquired and a trained neural network is applied to the PET and CT data to generate and attenuation map to reconstruct a corrected PET image (see abstract), wherein the operations further include: obtaining a second attenuation map of the subject generated based on a computed tomography (CT) scan of the subject (a second attenuation map of the plurality of attenuation maps in [0056]); selecting, from the first attenuation maps corresponding to the plurality of physiological phases, a reference attenuation map that has the highest similarity to the second attenuation map ([0056] discloses comparing attenuation maps to an expected attenuation map);
determining the physiological phase corresponding to the reference attenuation map as the reference physiological phase ([0062] states that “registration engine 406 may perform operations to correspond the values of the initial attenuation map 403 to the PET image 115 in a same coordinate system, and adjust the values of the initial attenuation map 403 based on corresponding values of the PET image 115”, meaning that the gated PET [0024] matches the respective respiratory phases).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Salomon, wherein the operations further include: obtaining a second attenuation map of the subject generated based on a computed tomography (CT) scan of the subject; selecting, from the first attenuation maps corresponding to the plurality of physiological phases, a reference attenuation map that has the highest similarity to the second attenuation map; determining the physiological phase corresponding to the reference attenuation map as the reference physiological phase, as taught by, Schaefferkoetter, to improve the accuracy and quality of the medical image data ([0003]), with a reasonable expectation of success, as modified Salomon also strives to improve image accuracy ([0002]) and quality ([0004]).
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Bharkhada, et al., US 20230401769 A1.
Regarding claim 10, Salomon teaches all the limitations of claim 1 above.
Salomon fails to teach wherein the plurality of gated PET images are histoimages.
However, within the same field of endeavor, Bharkhada teaches systems and methods of dynamic PET imaging are disclosed. A system includes a positron emission tomography (PET) imaging modality configured to execute a first scan to acquire a first PET dataset and a processor. The first PET dataset includes dynamic PET data (see abstract), the dynamically-generated PET images are configured to provide analysis of changing body states over the time period, such as, for example, being applicable for motion correction, assessing distribution of a tracer over different cardiac and/or respiratory cycles, studying tracer kinetics, and/or other suitable applications according to [0026] (gating), wherein the plurality of gated PET images are histoimages ([0026] states that “The dynamically-generated PET images are generated in real-time, to allow simultaneous monitoring of dynamic changes in the time-referenced PET data. Prior methods utilizing histo-images to obtain simulated reconstructed PET images require histo-images incorporating all PET data obtained at axial positions into a single histo-image and are not able to account for dynamically changing PET data”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Salomon wherein the plurality of gated PET images are histoimages, as taught by Bharkhada, to allow acquisition of higher quality images, [0054], with a reasonable expectation of success, as modified Salomon also strives to improve image accuracy ([0002]) and quality ([0004]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Farouk A Bruce whose telephone number is (408)918-7603. The examiner can normally be reached Mon-Fri 8-5pm PST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Christopher Koharski can be reached at (571) 272-7230. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/FAROUK A BRUCE/ Examiner, Art Unit 3797