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 .
DETAILED ACTION
The United States Patent & Trademark Office appreciates the application that is submitted by the inventor/assignee. The United States Patent & Trademark Office reviewed the following application and has made the following comments below.
Priority
This application claims benefit of foreign priority under 35 U.S.C. 119(a)-(d) of JP 2024-006305 , filed in Japan on 01/18/2024.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 11/14/2024 and 05/09/2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Specification
Applicant is reminded of the proper content of an abstract of the disclosure.
A patent abstract is a concise statement of the technical disclosure of the patent and should include that which is new in the art to which the invention pertains. The abstract should not refer to purported merits or speculative applications of the invention and should not compare the invention with the prior art.
If the patent is of a basic nature, the entire technical disclosure may be new in the art, and the abstract should be directed to the entire disclosure. If the patent is in the nature of an improvement in an old apparatus, process, product, or composition, the abstract should include the technical disclosure of the improvement. The abstract should also mention by way of example any preferred modifications or alternatives.
Where applicable, the abstract should include the following: (1) if a machine or apparatus, its organization and operation; (2) if an article, its method of making; (3) if a chemical compound, its identity and use; (4) if a mixture, its ingredients; (5) if a process, the steps.
Extensive mechanical and design details of an apparatus should not be included in the abstract. The abstract should be in narrative form and generally limited to a single paragraph within the range of 50 to 150 words in length.
See MPEP § 608.01(b) for guidelines for the preparation of patent abstracts.
The abstract of the disclosure is objected to because the abstract is two paragraphs and 174 words in length. A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
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 1-13 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. The Examiner strongly suggested that appropriate corrections be made to clarify the claim scope.
With respect to Claim 1, the claim recites the following, which renders the claim indefinite:
“an image” on line 15. It is unclear as to whether “an image” in line 15 refers to a tomographic image (line 7) or a partial reconstruction image (line 9).
With respect to Claim 12, the claim recites the following, which renders the claim indefinite:
“an image” on lines 6-7. It is unclear as to whether “an image” in lines 6-7 refers to an image of the pair of partial reconstruction images (line 3).
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(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102 of this title, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negatived by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103(a) 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.
Claims 1-3, 5-6, 10, and 12-13 are rejected under 35 U.S.C. 103(a) as being unpatentable over Lee et al. (U.S. Patent No. 10,565,744, hereafter referred to as Lee) in view of Fessler et al. (U.S. Patent Pub No. 2008/0304726 A1, hereafter referred to as Fessler).
Regarding Claim 1, Lee teaches an X-ray CT apparatus (Col. 4, lines 56-60, Fig. 1, Lee teaches a CT system (100). The CT system (100) may be implemented as a single-source CT system including one x-ray generator (112) and one x-ray detector (113) or as a dual-source CT system including two X-ray generators 112 and two X-ray detectors 113.)
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comprising: an imaging unit (Col. 4, lines 21-25, Fig. 1, Lee teaches a CT system/apparatus that emits x-rays. A CT image is constructed from raw data obtained by photographing an object by detecting x-rays that are emitted by the CT system.) that has a scanner equipped with an X-ray source and an X-ray detector (Col. 8, lines 40-54, Figs. 1 & 2, Lee teaches a scanner (220). The scanner (220) may include the x-ray generator (112) and the x-ray detector (113).) and rotating around a subject (Col. 4, lines 17-25, Lee teaches the CT system emits x-rays while rotating around at least one axis relative to an object and photograph the object by detecting the x-rays.) and a moving mechanism moving a position of the scanner in a body axis direction of the subject relative to the subject (Col. 4, lines 45-47, Fig. 1, Lee teaches a rotation driver (114) which sends a driving signal to the rotating frame (111) which rotates around the rotation axis.), and that acquires transmitted X-ray data having different angles with respect to the subject and different positions in the body axis direction (Col. 10, lines 20-26, Fig. 4, Lee teaches the x-ray generator (112) rotates while sequentially passing through angular sections (410) through (413) of Fig. 4 and projects x-rays to an object (420), and raw data is generated from x-rays detected by the x-ray detector (113).);
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and a processor that generates a tomographic image of the subject (Col. 5, lines 46-54, Lee teaches the image processor may generate the tomography data. The tomography data may be in the form of a tomography image.) using the transmitted X-ray data acquired by the imaging unit (Col. 9, lines 7-14, Col. 5, lines 55-62, Lee teaches obtaining raw data by scanning an object. The raw data may be obtained from a scanner of the medical image processing apparatus (CT).), wherein the processor is configured to generate a pair of partial reconstruction images at positions directly facing each other using the transmitted X-ray data
(Col. 10, lines 20-36, Fig. 4, Lee teaches the processor generates, from the raw data, PAR images (421-433) respectively corresponding to the angular sections (401-413). PAR images having a phase difference of 180-degrees therebetween, from among the PAR images (421-433), form a conjugate PAR image pair. For example, the PAR image (421) and the PAR image (427) may form a conjugate PAR image pair.),
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acquire motion information of the subject during scanning (Col. 2, lines 32-45, Col. 9, lines 18-19, Col. 12, lines 4-9, Lee teaches generating first motion information by using at least one partial angle reconstruction (PAR) image pair including two PAR images respectively obtained in two phase sections that face each other in the first phase section. The first motion information may be represented as, for example, a motion vector field (MVF).) by applying a motion estimation model to the pair of partial reconstruction images (Col. 12, lines 11-54, Lee teaches a B-spline-based 4D freeform deformation (FFD) model as a motion model in order to express the motion of the heart over time. The processor defines the parameter of the 4D motion model that a difference between the PAR Images from scan ranges 401 and 407 decreases, and defines the parameter of the 4D motion model such that a difference between the PAR images from scan ranges 402 and 408 decreases. See Fig. 4 (401 & 407 and 402 & 408 are conjugate pairs.), and reconstruct the tomographic image using the motion information (Col. 4, lines 31-35, Lee teaches reconstructing a motion-compensated image using an updated motion vector field (MVF).) and the transmitted X-ray data acquired in an angle range of 180 degrees or more (Col. 9, lines 32-41, Lee teaches generating a PAR sequence which may cover a phase section of 360 degrees, or a phase section of 360 degrees or greater.), the motion estimation model includes a first regularization term (Col. 13, lines 4-15, Equation 3, Lee teaches a regularization term R1 of penalizing a large difference between parameter values of spatio-temporally adjacent control points.)
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and a second regularization term (Col. 13, lines 22-35, Lee teaches another (second) regularization term R2.),
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at least one of the motion estimation model or a calculation method of motion estimation using the motion estimation model according to an image reconstruction condition (Col. 13, Lee teaches the processor defines a final cost function by using a previously defined data term (Eq. 2), and the two regularization terms (Eqs. 3 & 4) in Equation 5, and searches for a motion model parameter for minimizing the final cost function. The Examiner interprets searching for the motion model parameters (lambdas 1 & 2) to minimize the cost function “automatically” changes the motion estimation model. Under Broadest Reasonable Interpretation (BRI), the Examiner interprets “at least one of” and “or” to mean only one of the claim limitations listed before and after the word “or” is required.).
Lee does not explicitly disclose that maintains spatial continuity of an image and that maintains temporal continuity of the image, which are independently adjustable.
Fessler is in the same field of art of reconstructing a CT image to improve the resolution of the image. Further, Fessler teaches a first regularization term that maintains spatial continuity of an image (Paragraphs [0018], [0024], Fessler teaches a spatial regularization term S(f).)
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and a second regularization term that maintains temporal continuity of the image (Paragraphs [0018], [0023], Fessler teaches a temporal regularization term T(f).),
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which are independently adjustable (Paragraphs [0023-24], [0034-35], Fessler teaches the temporal regularization term T(f) and the spatial regularization term S(f) are weighted by different equations. See equations (3) and (4) above. The temporal regularization parameters in equation (3) are selected to improve temporal resolution. The spatial regularization parameters are selected to improve the spatial resolution.).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Lee by including separate spatial and temporal regularization terms in the cost function that is taught by Fessler, to make the invention that improves both temporal and spatial resolution of a reconstructed CT image; thus, one of ordinary skilled in the art would be motivated to combine the references to provide a reconstructed image of a moving object (cardiac CT- heart motion) having both improved spatial resolution and temporal resolution by regularizing both spatial and temporal parameters after every iteration. Therefore, providing better image quality (Fessler, Paragraph [0038]).
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
In regards to Claim 2, Lee in view of Fessler teaches the X-ray CT apparatus according to claim 1, wherein the processor adjusts the motion estimation model according to the image reconstruction condition (Col. 12, lines 42-67, Lee teaches that the processor determines a parameter of a 4D motion model such that the difference between conjugate PAR images in each conjugate PAR stack decreases. For example, the processor defines the parameter of the 4D motion model such that a difference between the PAR images from scan ranges 401 and 407 decreases, and defines the parameter of the 4D motion model such that the difference between the PAR images from scan ranges 402 and 408 decreases.).
In regards to Claim 3, Lee in view of Fessler teaches the X-ray CT apparatus according to claim 2, wherein the processor adjusts at least one of a weight of the first regularization term or a weight of the second regularization term according to the image reconstruction condition (Paragraphs [0023-26], Fessler teaches weighting the temporal T(f) and spatial S(f) regularization terms. Temporal (tij) and spatial (sjk) parameters are selected to improve temporal and spatial resolution respectively. By minimizing the cost function an updated image is produced. The spatio-temporal data-weighting factor is adjusted based on where a projection data m falls in the cardiac cycle relative to phase 1, resulting in phase-weighted iterative reconstruction. Under BRI, the Examiner interprets “or” to mean adjusting either the first or second regularization terms is required to meet the claim limitation. However, Fessler teaches adjusting the weight of the first and second regularization terms.).
In regards to Claim 5, Lee in view of Fessler discloses the X-ray CT apparatus according to claim 3, wherein the processor (Paragraph [0005], Fessler teaches the processor modifies at least one of the data fit term and the regularization term to accommodate spatio-temporal information to form a reconstructed image.) adjusts the weight of the second regularization term (Paragraph [0023], Fessler teaches weighting the temporal regularization term T(f). Temporal regularization parameters in the term are selected to improve temporal resolution.) according to an image reconstruction interval set as the image reconstruction condition (Paragraph [0026], Fessler teaches the spatio-temporal data-weighting factor is adjusted based on where a projection data falls in the cardiac cycle relative to the cardiac phase I, resulting in phase-weighted iterative construction.).
In regards to Claim 6, Lee in view of Fessler discloses the X-ray CT apparatus according to claim 3, wherein the processor adjusts a control point of the motion estimation model (Col. 2, lines 7-10, Lee teaches the processor may update the first motion information such that a difference between pieces of motion information of spatially adjacent control points decreases.) in addition to adjustment of a weight of a regularization term according to the image reconstruction condition (Col. 13, lines 36-48, Lee teaches searching for motion model parameters (regularization parameters λ1 and λ2) for minimizing the final cost function. A Gauss-Newton method is used to search for a motion model parameter for minimizing the pre-defined cost function.).
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In regards to Claim 10, Lee in view of Fessler discloses the X-ray CT apparatus according to claim 1, wherein the processor dynamically adjusts a calculation method (Col. 13, lines 36-40, Lee teaches the processor defines a cost function and searches for a motion model parameter for minimizing the final cost function.) according to an image reconstruction interval set as the image reconstruction condition (Col. 14, lines 8-11, Lee teaches a repetition of β (1D cubic spline) at intervals of 180 degrees and enables a motion field vector to be created by re-using a control point at intervals of 180 degrees.) in calculation of a control point parameter using the motion estimation model (Col. 14, lines 31-36, Lee teaches an equation defining a regularization term such as a difference between spatially adjacent control points does not increase. The Examiner interprets a regularization term which influences the difference between control points to be a “control point parameter.”).
In regards to Claim 12, Lee discloses a processor for image processing that processes transmitted X-ray data acquired by an X-ray CT apparatus (Col. 5, lines 17-30, Fig. 1, Lee teaches an image processor (150) that receives a detection signal generated by the x-ray detector (113) of the CT system (100).), the processor being configured to: generate a pair of partial reconstruction images at positions directly facing each other using the transmitted X-ray data (Col. 10, lines 28-36, Fig. 4, Lee teaches the processor generates from the raw data, PAR images 421-433 respectively corresponding to the angular sections 401-413. PAR images having a phase difference of 180 degrees therebetween, from among the PAR images 421-433, form a conjugate PAR image. For example, the PAR image 421 and the PAR image 427 may form a conjugate pair.); acquire motion information of a subject during scanning (Col. 10, lines 52-65, Lee teaches the processor obtains motion information, namely, a motion vector field, by using at least one PAR image pair.) by applying a motion estimation model (Col. 12, lines 11-18, Lee teaches the processor uses a B-spline-based 4D freeform deformation model as a motion model in order to express a motion of a heart over time. The 4D FFD model represents correspondence between a reference image at a reference time point r and an image at each time point.) including a first regularization term (Col. 13, lines 4-9, Equation 3, Lee teaches a regularization term R1 that penalizes a large difference between parameter values of spatio-temporally adjacent control points.) and a second regularization term(Col. 13, lines 22-29, Equation 4, Lee teaches another regularization term for correcting that an MVF does not become 0 at the reference phase.), (Col. 12, lines 42-54, Lee teaches the 4D motion model is applied such that the difference between conjugate PAR images in each conjugate PAR stack decreases.); and reconstruct a tomographic image using the motion information (Col. 4, lines 31-35, Lee teaches reconstructing a motion-compensated image using an updated motion vector field (MVF).) and the transmitted X-ray data acquired in an angle range of 180 degrees or more (Col. 9, lines 32-41, Lee teaches generating a PAR sequence which may cover a phase section of 360 degrees, or a phase section of 360 degrees or greater.).
Fessler is in the same field of art of reconstructing a CT image to improve the resolution of the image. Further, Fessler teaches a first regularization term that maintains spatial continuity of an image (Paragraphs [0021], [0024], Fessler teaches a spatial regularization term S(f).) and a second regularization term that maintains temporal continuity of the image (Paragraphs [0021], [0023], Fessler teaches a temporal regularization term T(f).), which are independently adjustable (Paragraphs [0023-24], Fessler teaches separate spatial and temporal regularization terms S(f) and T(f). The spatial regularization parameters and temporal regularization parameters are selected to improve temporal resolution and spatial resolution, respectively.).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Lee by including separate spatial and temporal regularization terms in the cost function that is taught by Fessler, to make the invention that improves both temporal and spatial resolution of a reconstructed CT image; thus, one of ordinary skilled in the art would be motivated to combine the references to provide a reconstructed image of a moving object (cardiac CT- heart motion) having both improved spatial resolution and temporal resolution by regularizing both spatial and temporal parameters after every iteration. Therefore, providing better image quality (Fessler, Paragraph [0038]) .
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
In regards to Claim 13, Lee in view of Fessler teaches the processor according to claim 12, wherein in a case of acquiring the motion information, at least one of the motion estimation model used for acquisition of the motion information or a calculation method using the motion estimation model is dynamically changed according to an image reconstruction condition which is set upon motion correction reconstruction (Col. 13, Lee teaches the processor defines a final cost function by using a previously defined data term (Eq. 2), and the two regularization terms (Eqs. 3 & 4) in Equation 5, and searches for a motion model parameter for minimizing the final cost function. The Examiner interprets searching for the motion model parameters (lambdas 1 & 2) to minimize the cost function “automatically” changes the motion estimation model. Under Broadest Reasonable Interpretation (BRI), the Examiner interprets only one of the claim limitations listed before and after “or” is required.).
Claim 4 is rejected under 35 U.S.C. 103(a) as being unpatentable over Lee et al. (U.S. Patent No. 10,565,744, hereafter referred to as Lee) in view of Fessler et al. (U.S. Patent Pub No. 2008/0304726 A1, hereafter referred to as Fessler) in further view of Zhou et al. (U.S. Patent Pub. No. 2017/0294034 A1, hereafter referred to as Zhou).
Regarding Claim 4, Lee in view of Fessler discloses the X-ray CT apparatus according to claim 3.
Lee in view of Fessler does not explicitly disclose wherein the processor adjusts the weight of the first regularization term according to a field of view (FOV) set as the image reconstruction condition.
Zhou is in the same field of art of predicting a regularization parameter for construction of radiation detection data (CT) to generate a reconstructed image. Further, Zhou teaches wherein the processor (Paragraph [0086], Zhou teaches a processor.) adjusts the weight of the first regularization term according to a field of view (FOV) set as the image reconstruction condition (Paragraphs [0003], [0019], Zhou teaches predicting a regularization parameter (β) according to predefined specifications of the reconstructed image, such as the display field of view (dFOV) and iteratively reconstructing an image using the predicted regularization parameter (β). The regularization parameter (β) weights the relative contributions of the system-matrix term and the regularization term.).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Lee in view of Fessler by adjusting the weight of the regularization parameter based on predefined specifications of the reconstructed image, such as the display field of view (dFOV) that is taught by Zhou, to make the invention that enables selection of a regularization parameter to generate specific characteristics such as display field of view for CT systems; thus, one of ordinary skilled in the art would be motivated to combine the references to improve the characteristics of the reconstructed image based on the regularization term (Zhou, Paragraphs [0006-7]). In addition, many users for CT must guess the magnitude of regularization parameter required in order to obtain a desired noise level in a reconstructed image and different dFOVs result in different noise properties in the reconstructed image. The method of guessing and checking the regularization parameter corresponding to the desired properties of the reconstructed image is inefficient (Zhou, Paragraphs [0027-29]).
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
Claims 7 and 9 are rejected under 35 U.S.C. 103(a) as being unpatentable over Lee et al. (U.S. Patent No. 10,565,744, hereafter referred to as Lee) in view of Fessler et al. (U.S. Patent Pub No. 2008/0304726 A1, hereafter referred to as Fessler) in further view of Lu et al. (U.S. Patent Pub. No. 2014/0081129 A1, hereafter referred to as Lu).
In regards to Claim 7, Lee in view of Fessler discloses the X-ray CT apparatus according to claim 2 wherein the processor adjusts a control point of the motion estimation model (Col. 2, lines 7-10, Lee teaches the processor updates the first motion information such that a difference between pieces of motion information of spatially adjacent control points decreases.).
Lee in view of Fessler does not explicitly disclose according to a field of view (FOV) set as the image reconstruction condition.
Lu is in the same field of art of defining control points in CT images. Further, Lu teaches (adjusting a control point) according to a field of view (FOV) set as the image reconstruction condition (Paragraph [0046], Lu teaches centering the control point by translating the field of view.).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Lee in view of Fessler by adjusting a control point of the CT image based on a field of view of the image that is taught by Lu, to make the invention that keeps the control point within the field of view; thus, one of ordinary skilled in the art would be motivated to combine the references since the control point is an important point from which motion is to be estimated (Lee, Col. 12, lines 35-38) .
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
Regarding Claim 9, Lee in view of Fessler in further view of Lu discloses the X-ray CT apparatus according to claim 7, wherein the processor adjusts coordinates of the control point (Col. 2, lines 7-10, Lee teaches the processor updates the first motion information such that a difference between pieces of motion information of spatially adjacent control points decreases.) such that a position of the control point with respect to an image center in an image space is constant according to the FOV (Paragraphs [0046-47], Figs. 6A-6D, Lu teaches translating the field of view to center the control point (610). The control point is fixed in the center of the image. The Examiner interprets “center(ing) the control point” means the coordinates of the control points are adjusted to accommodate the field of view.).
Claim 11 is rejected under 35 U.S.C. 103(a) as being unpatentable over Lee et al. (U.S. Patent No. 10,565,744, hereafter referred to as Lee) in view of Fessler et al. (U.S. Patent Pub No. 2008/0304726 A1, hereafter referred to as Fessler) in further view of Schreibmann et al (NPL “Image interpolation in 4D CT using a BSpline deformable registration model,” 2006, hereafter referred to as Schreibmann).
Regarding Claim 11, Lee in view of Fessler discloses the X-ray CT apparatus according to claim 10, wherein the processor(Col. 13, lines 4-9, Lee teaches using a regularization term for penalizing a large difference between parameter values of spatio-temporally adjacent control points. The regularization parameters are determined by minimizing a cost function.) using the partial reconstruction image (Col. 2, lines 52-56, Lee teaches generating the motion information by using at least one partial angle reconstruction image pair including two PAR images.)
Schreibmann is in the same field of art of performing deformable image registration on CT images using Bspline. Further, Schreibmann teaches wherein the processor (Software and hardware platform, Schreibmann teaches all calculations were done on a standard PC computer with a Windows XP operating system and a Pentium 4 Processor at 1.6 GHZ, 256 MB of RAM.) sets one or more virtual cross sections at a constant interval between a cross section of interest and an adjacent cross section adjacent to the cross section of interest in the body axis direction of the subject (Image acquisition, Schreibmann teaches selecting CT0 and CT40 as input images to an image interpolation algorithm to derive the images CT10, CT20, and CT30. The Examiner interprets CT10, CT20, and CT30 are at constant intervals between a cross section of interest CT0 “fixed image” and an adjacent cross section CT40 “floating image”.), (Coregistration of images at known phases, Schreibann teaches image registration by finding the transformation matrix T(x), that maps an arbitrary point (x), on the fixed image to the corresponding point, x’, on the floating image or vice versa so that the best possible match is achieved.), and sets the control point parameter calculated in the virtual cross section in a case where the position of the virtual cross section reaches the position of the adjacent cross section as the control point parameter of the adjacent cross section (Performance of image coregistration, Schreibann teaches image coregistration to relate the fixed and floating images. The mapped floating image and the fixed image should be identical after the registration.).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Lee in view of Fessler by adjusting the control point parameter (regularization parameter) based on matching the virtual cross sections via registration that is taught by Schreibann, to make the invention that determines a transformation that describes the 3D deformation field describing the anatomy change/motion from one image to the adjacent image; thus, one of ordinary skilled in the art would be motivated to combine the references to achieve the best possible match between an arbitrary point on a fixed image and a corresponding point on a floating image, as measured by the registration metric (Schreibann, Coregistration of images at known phases).
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
Allowable Subject Matter
Claim 8 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.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding Claim 8, no prior art teaches wherein the processor adjusts the number of pixels between adjacent control points of the motion estimation model according to the FOV. Specifically, Lee teaches updating a motion vector field such that a difference between pieces of motion information of spatially adjacent control points decreases. Lee does not disclose adjusting the number of pixels between adjacent control points according to the field of view.
Pertinent Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Pack et al. (U.S. Patent Pub. No. 2011/0142313 A1) teaches a method and system for motion estimation and compensation. A motion model is employed to estimate the motion path of a region of interest (ROI) on the images. The motion estimation of the ROI may be further augmented by using pair-wise cross-correlation to estimate relative translation of at least a portion of the object of interest included in the ROI during a 180-degree rotation.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SYDNEY L BLACKSTEN whose telephone number is (571)272-7651. The examiner can normally be reached 8:30am-4:30pm.
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/SYDNEY L BLACKSTEN/Examiner, Art Unit 2674
/ONEAL R MISTRY/Supervisory Patent Examiner, Art Unit 2674
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