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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 04/01/2026 has been entered.
Status of Claims
Claims 1-20 are pending.
Response to Arguments
Applicant’s arguments, see p.8-16, filed 03/17/2026, with respect to the rejection of Claims 1-20 under 35 U.S.C. 101 have been fully considered and are persuasive. Therefore, the rejection of Claims 1-20 under this section of the Rules has been withdrawn.
Applicant’s arguments, see p.16-20, filed 03/17/2026, with respect to the rejections of Claims 1-20 under 35 U.S.C. 103 have been fully considered but are moot because Applicant’s amendments of the independent claims has altered the scope of the claims, and therefore, necessitated new grounds of rejection which are presented below.
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 1, 8, 10-13, and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Berlin et al. (US 20190154822 A1) in view of Sakaguchi et al. (JP 2017074194 A), Fartaria et al. (US 20200294237 A1), and Florent et al. (US 20140005538 A1).
Regarding Claim 1, Berlin teaches "A computer-implemented method of obtaining medical images of a subject corrected for a difference in contrast agent density of a contrast agent in a sequence of contrast-enhanced image frames from the medical images, the computer-implemented method comprising: selecting a reference image frame from the sequence of contrast-enhanced image frames"; (Berlin, Paras. 8-9, teaches a signal model process that defines, from the plurality of time-based images, time-based measurement windows having successive and overlapping groups of the time-based image frames wherein the background signal from at least one image frame is removed by comparing the time-based measurement windows to determine the presence of the background signal based upon changes in imaged contrast agent between time-based measurement windows, i.e., selecting a reference image frame from a sequence of a plurality of images with contrast-enhanced image frames for comparing a difference of contrast agent density);
"performing segmentation on the reference image frame"; (Berlin, Para. 8, teaches region of interest segmentation processes for automatic segmentation of an image, i.e., perform segmentation on the reference image frame);
"identifying a region of interest in the reference image frame based on the segmentation, wherein the region of interest is a region of the reference image frame that contains the contrast agent"; (Berlin, Para. 8, teaches region of interest segmentation processes for automatic segmentation of an image to identify regions of interest that share similar contrast agent accumulation characteristics, i.e., identification of regions of interest in the reference frame based on the segmentation wherein the region of interest contains the contrast agent).
However, Berlin does not explicitly teach "and correcting the difference in contrast agent density in a set of one or more image frames in the sequence of contrast-enhanced image frames to provide contrast agent density corrected medical images of the subject based on a change in image intensity within the region of interest between each of the one or more image frames and the reference image frame; wherein the set of one or more image frames includes at least one image frame that is different to the reference image frame, and wherein each contrast agent density corrected medical image appears to have the same contrast agent density as in the reference image frame, thereby reducing effects of degradation and/or dilution of the contrast agent over time”.
In an analogous field of endeavor, Sakaguchi teaches "and correcting the difference in contrast agent density in a set of one or more image frames in the sequence of contrast-enhanced image frames to provide contrast agent density corrected medical images of the subject based on a change in image intensity within the region of interest between each of the one or more image frames and the reference image frame"; (Sakaguchi, Pg. 8 Paras. 5-6, teaches a correction function which performs correction processing on a region in the difference image by partially correcting the image by replacing the luminance value of a pixel in a predetermined region in the difference image with a value of density times thickness wherein the region is where a contrast agent flows and wherein correcting the luminance value of the difference image it is possible to accurately perform perfusion measurement in interventional treatment, i.e., a difference of contrast agent density in a set of one or more image frames is corrected in the difference image based on the change in image intensity indicated by the luminance values of the pixels within the region of interest between a contrast-enhanced image frame and the difference or reference image frame. For further clarification, Sakaguchi, Pg.4 Para.3, Pg. 5 Para. 1, Pg. 8 Paras. 3-6, and Pg. 9 Para. 5, teaches generating a difference image by performing subtraction between the mask image and the contrast image previously stored in which a correction curve indicates the relationship between the signal intensity and the contrast agent concentration and thickness in the difference image wherein a correction function performs correction processing on a region in the difference image to correct the luminance value of the pixels using the correction curve and wherein the luminance value at the same position is measured based on different contrast agent concentrations in a plurality of difference images in which the correction curve is calculated based on the plurality of difference images with different concentrations, i.e., contrast agent density corrected medical images of a subject are provided by correcting a difference in contrast agent density of a contrast enhanced image being the contrast image based on a change in image intensity within the region of interest between the contrast enhanced image and the reference frame being the generated difference image via subtraction of a mask image and the contrast image and the measure of the change in luminance or intensity within an image region at the same position of a plurality of difference images in order to determine the correction curve that is applied to correct pixel luminance values in the contrast enhanced image region);
"wherein the set of one or more image frames includes at least one image frame that is different to the reference image frame"; (Sakaguchi, Pg. 9 Para. 5, teaches acquiring a plurality of difference images based on different contrast agent concentrations wherein a correction curve is acquired from the difference images and corrects the luminance value of the difference image, i.e., the set of image frames includes image frames that are different from the reference image frame).
It would have been obvious to one having ordinary skill in the art before the effective filing date to modify the invention of Berlin wherein reference image frame are contrast-enhanced image frames by including the correction of a difference in contrast density of the set of images based on the change of image intensity of the region between the images and the reference image taught by Sakaguchi. One of ordinary skill in the art would be motivated to combine the references since it corrects the image with higher accuracy (Sakaguchi, Pg. 12 Para. 5, teaches the motivation of combination to be to correct the contrast image with higher accuracy).
However, the combination of references of Berlin in view of Sakaguchi does not explicitly teach “and wherein each contrast agent density corrected medical image appears to have the same contrast agent density as in the reference image frame, thereby reducing effects of degradation and/or dilution of the contrast agent over time”.
In an analogous field of endeavor, Fartaria teaches "and wherein each contrast agent density corrected medical image appears to have the same contrast agent density as in the reference image frame"; (Fartaria, Abstract and Para. 26, teaches a method to monitor a biological process including obtaining an abnormal tissue mask from an abnormal tissue segmentation of an image of an object containing tissue to be analyzed, the image being acquired at a time t0 being a reference time point wherein other images of the object are registered onto the abnormal tissue mask and are acquired at other time points in which image contrasts of the other images are normalized with respect to the contrasts of the image acquired at the reference time point that way contrast intensity inhomogeneities in each one of the other images might be corrected, i.e., each contrast agent density corrected medical image appears to have the same contrast agent density as in the reference image frame at the given time due to the normalization of the image contrasts with respect to the reference image).
It would have been obvious to one having ordinary skill in the art before the effective filing date to modify the invention of Berlin and Sakaguchi by including the contrast agent density in the corrected images appearing to have the same density as the reference image taught by Fartaria. One of ordinary skill in the art would be motivated to combine the references since it obtains a more reliable progression map and decreases misclassifications (Fartaria, Para. 30, teaches the motivation of combination to be to obtain a more reliable biological process progression map and decreases misclassifications).
However, the combination of references of Berlin in view of Sakaguchi and Fartaria does not explicitly teach "thereby reducing effects of degradation and/or dilution of the contrast agent over time".
In an analogous field of endeavor, Florent teaches "thereby reducing effects of degradation and/or dilution of the contrast agent over time"; (Florent, Abstract and Paras. 41-43, teaches normalization based on an estimation of an injected volume of contrast agent flowing through the main collector may allow the cancellation of differences in image data resulting from said differing contrast agent volume or contrast agent amount wherein perfusion is observed through opacification, and since higher blood flow implies a lesser opacification due to higher dilution, any flow discrepancy might potentially lead to a perfusion assessment discrepancy in which measuring the blood volume flow along time in the main collector enables normalization of the two situations, i.e., normalizing contrast agent amount between images so the images appear to have same contrast agent density reduces effect of dilution of the contrast agent over time).
It would have been obvious to one having ordinary skill in the art before the effective filing date to modify the invention of Berlin, Sakaguchi, and Fartaria by including the reduction of the effects of dilution of the contrast over time taught by Florent. One of ordinary skill in the art would be motivated to combine the references since it improves the visibility of the image data (Florent, Para. 12, teaches the motivation of combination to be to improve visibility of perfusion image data).
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date.
Regarding Claim 8, the combination of references of Berlin in view of Sakaguchi, Fartaria, and Florent teaches "The computer-implemented method of claim 1, wherein correcting the set of one or more image frames in the sequence of image frames comprises: defining, for each image frame in the set of one or more image frames, a non-linear transfer function of intensity values such that a mean uncorrected image intensity of the region of interest in the image frame is mapped to a mean image intensity of the region of interest in the reference image frame"; (Sakaguchi, FIG. 15 and Pg. 13 Paras. 2-4, teaches storing correction curves or candidate curves using various concentrations of contrast agents wherein the correction function corrects the luminance value of the pixel in the contrast image using the correction curve and wherein the acquisition function selects a luminance value and contrast in a predetermined region from a plurality of curves indicating a relationship between a luminance value in a contrast image set in advance for each condition of a contrast agent in which the plurality of curves may be averaged, i.e., defining a non-linear transfer function being the curves for each image frame such that the uncorrected image intensity being the contrast agent density of the region of interest is pixel-wise mapped to the image intensity region of the reference image frame wherein the intensity may be averaged);
"applying, for each image frame in the set of one or more image frames, the non-linear transfer function defined for the image frame to at least a part of the image frame"; (Sakaguchi, FIG. 15 and Pg. 13 Paras. 2-4, teaches the acquisition function selecting a luminance value and contrast in a predetermined region from a plurality of curves indicating a relationship between a luminance value in a contrast image set in advance for each condition of a contrast agent, i.e., apply the non-linear transfer function being the curves to each image frame to at least part of the image being the predetermined region).
The proposed combination as well as the motivation for combining the Berlin, Sakaguchi, Fartaria, and Florent references presented in the rejection of Claim 1, applies to claim 8. Thus, the method recited in claim 8 is met by Berlin in view of Sakaguchi, Fartaria, and Florent.
Regarding Claim 10, the combination of references of Berlin in view of Sakaguchi, Fartaria, and Florent teaches "The computer-implemented method of claim 1, wherein the difference in contrast agent density is corrected in the whole of each image frame of the set of one or more image frames"; (Sakaguchi, Pg. 8 Paras. 5-6, teaches a correction function which performs correction processing on a region in the difference image by correcting the entire image by replacing the luminance values of all the pixels in the difference image with the value of density times thickness, i.e., difference in contrast agent density is corrected in the whole of each image frame of the set of image frames).
The proposed combination as well as the motivation for combining the Berlin, Sakaguchi, Fartaria, and Florent references presented in the rejection of Claim 1, applies to claim 10. Thus, the method recited in claim 10 is met by Berlin in view of Sakaguchi, Fartaria, and Florent.
Regarding Claim 11, the combination of references of Berlin in view of Sakaguchi, Fartaria, and Florent teaches "The computer-implemented method of claim 1, wherein the difference in contrast agent density is corrected in a part of each image frame of the set of one or more image frames, wherein the part includes the region of interest"; (Sakaguchi, Pg. 8 Paras. 5-6, teaches a correction function which performs correction processing on a region in the difference image by partially correcting the image by replacing the luminance value of a pixel in a predetermined region in the difference image with a value of density times thickness, i.e., difference in contrast agent density is corrected in a part of each image frame of the set of image frames wherein the part includes the region of interest).
The proposed combination as well as the motivation for combining the Berlin, Sakaguchi, Fartaria, and Florent references presented in the rejection of Claim 1, applies to claim 11. Thus, the method recited in claim 11 is met by Berlin in view of Sakaguchi, Fartaria, and Florent.
Claim 12 recites a computer-readable storage medium storing a program with instructions corresponding to the steps recited in Claim 1. Therefore, the recited programming instructions of this claim are mapped to the proposed combination in the same manner as the corresponding steps in its corresponding method claim. Additionally, the rationale and motivation to combine the Berlin, Sakaguchi, Fartaria, and Florent references, presented in rejection of Claim 1, apply to this claim. Finally, the combination of the Berlin, Sakaguchi, Fartaria, and Florent references discloses a computer readable storage medium (for example, see Berlin, Paragraph 183).
Claim 13 recites a system with elements corresponding to the steps recited in Claim 1. Therefore, the recited elements of this claim are mapped to the proposed combination in the same manner as the corresponding steps in its corresponding method claim. Additionally, the rationale and motivation to combine the Berlin, Sakaguchi, Fartaria, and Florent references, presented in rejection of Claim 1, apply to this claim. Finally, the combination of the Berlin, Sakaguchi, Fartaria, and Florent references discloses a processor, i.e., processing system, (for example, see Berlin, Paragraph 183). Additionally, Berlin, Paras. 39 and 182, teaches an onboard display that allows for local viewing and control of images acquired by the probe and allow a user to interface with the base unit wherein results are generated for better diagnostic outcomes, i.e., display corrected images for diagnosing the subject.
Regarding Claim 15, the combination of references of Berlin in view of Sakaguchi, Fartaria, and Florent teaches "A system comprising: an imaging apparatus for obtaining medical images of a subject; and the processing system of claim 13, further configured to receive the sequence of contrast-enhanced image frames from the imaging apparatus"; (Berlin, Para. 6, teaches images acquired by an ultrasound scanner in the presence of molecularly bound contrast agent, i.e., imaging apparatus which obtains medical images of a subject wherein the system receives the sequence of contrast-enhanced images from the apparatus).
Claims 2-5 and 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over Berlin in view of Sakaguchi, Fartaria, Florent, and Stewart, M. J. (2003). Contrast echocardiography. Heart, 89(3), 342-348.
Regarding Claim 2, the combination of references of Berlin in view of Sakaguchi, Fartaria, and Florent does not explicitly teach "The computer-implemented method of claim 1, wherein the sequence of contrast-enhanced image frames is a sequence of ventricular opacification image frames".
In an analogous field of endeavor, Stewart teaches "The computer-implemented method of claim 1, wherein the sequence of contrast-enhanced image frames is a sequence of ventricular opacification image frames"; (Stewart, Fig. 2, teaches acquiring left ventricular opacification images utilizing tissue harmonic imaging and wherein images C and D are imaged after intravenous bolus injection of SonoVue, i.e., sequence of contrast-enhanced images frames of ventricular opacification).
It would have been obvious to one having ordinary skill in the art before the effective filing date to modify the invention of Berlin, Sakaguchi, Fartaria, and Florent by including the ventricular opacification image frames taught by Stewart. One of ordinary skill in the art would be motivated to combine the references since it improves the sensitivity of the contrast ultrasound (Stewart, Pg. 342 Para. 3, teaches the motivation of combination to be to improve the sensitivity of contrast ultrasound).
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date.
Regarding Claim 3, the combination of references of Berlin in view of Sakaguchi, Fartaria, Florent, and Stewart teaches "The computer-implemented method of claim 2, wherein the reference image frame is selected by: performing an initial segmentation on a subset of image frames comprising a first M frames in the sequence of contrast-enhanced image frames, wherein M is a predetermined number"; (Stewart, Fig. 2 and Pg. 346 Para. 4, teaches intermittent imaging capturing one frame every 1-8 cardiac cycles usually triggered at end systole wherein the sequence of images includes contrast-enhanced image frames showing the end diastolic and end systolic segmented frames, i.e., initial segmentation of a subset of image frames being the given number of frames per a cardiac cycle which includes the end systolic frame and end diastolic frame indicating a predetermined number of frames for the subset of images of contrast-enhanced images);
"determining which image frame of the subset of image frames corresponds to a first end-diastolic frame based on the initial segmentation"; (Stewart, Fig. 2, teaches defining the apical four chamber view by the end diastolic and end systolic frames, i.e., initial segmentation indicating which image frame is the first end-diastolic frame);
"and selecting the determined image frame as the reference image frame"; (Stewart, Fig. 2, teaches the apical four chamber view including end diastolic and end systolic frames imaged after intravenous bolus injection of SonoVue wherein the mechanical index and other parameter are compared as well as the endocardial border being clearly defined and the systolic thickening of the lateral wall is appreciated, i.e., the end-diastolic frame which is contrast-enhanced is used as a reference frame for comparison).
The proposed combination as well as the motivation for combining the Berlin, Sakaguchi, Fartaria, Florent, and Stewart references presented in the rejection of Claim 2, applies to claim 3. Thus, the method recited in claim 3 is met by Berlin in view of Sakaguchi, Fartaria, Florent. and Stewart.
Regarding Claim 4, the combination of references of Berlin in view of Sakaguchi, Fartaria, Florent, and Stewart teaches "The computer-implemented method of claim 2, wherein the region of interest comprises an estimated location of a blood pool in the reference image frame"; (Stewart, Pg. 342 Paras. 4-5, teaches greatly enhancing the blood pool signal by using contrast bubbles oscillating in an ultrasound beam to scatter sound, i.e., the region of interest of the imaging comprises the location of a blood pool).
The proposed combination as well as the motivation for combining the Berlin, Sakaguchi, Fartaria, Florent, and Stewart references presented in the rejection of Claim 2, applies to claim 4. Thus, the method recited in claim 4 is met by Berlin in view of Sakaguchi, Fartaria, Florent, and Stewart.
Regarding Claim 5, the combination of references of Berlin in view of Sakaguchi, Fartaria, Florent, and Stewart teaches "The computer-implemented method of claim 4, wherein identifying the region of interest further comprises: identifying an end-systolic frame in the sequence of contrast-enhanced image frames"; (Stewart, Fig. 2, teaches defining the apical four chamber view by the end diastolic and end systolic frames, i.e., identifying an end-systolic frame in the sequence of contrast-enhanced images);
"estimating a location of the blood pool in the identified end-systolic frame; and defining the region of interest as a region comprising the estimated location of the blood pool in the reference image frame and the estimated location in the end-systolic frame"; (Stewart, Fig. 2 [D] and Pg. 342 Paras. 4-5, teaches the contrast-enhanced end systolic frame highlights the blood that was not ejected during the heart's systolic phase wherein the images are acquired using tissue harmonic imaging at a frequency leading to an enhancement of the blood pool signal, a reduced mechanical index, a clearly defined endocardial border, and systolic thickening of the entire lateral wall for more accurate measurement of the left ventricular volume, i.e., estimate the location of the blood pool in the end-systolic frame and define it as a region which defines the location of the blood pool in the reference end-systolic frame).
The proposed combination as well as the motivation for combining the Berlin, Sakaguchi, Fartaria, Florent, and Stewart references presented in the rejection of Claim 2, applies to claim 5. Thus, the method recited in claim 5 is met by Berlin in view of Sakaguchi, Fartaria, Florent, and Stewart.
Claim 17 recites a system with elements corresponding to the steps recited in Claim 2. Therefore, the recited elements of this claim are mapped to the proposed combination in the same manner as the corresponding steps in its corresponding method claim. Additionally, the rationale and motivation to combine the Berlin in view of Sakaguchi, Fartaria, Florent, and Stewart references, presented in rejection of Claim 2, apply to this claim. Finally, the combination of the Berlin in view of Sakaguchi, Fartaria, Florent, and Stewart references discloses a processor, i.e., processing system, (for example, see Berlin, Paragraph 183).
Claim 18 recites a system with elements corresponding to the steps recited in Claim 3. Therefore, the recited elements of this claim are mapped to the proposed combination in the same manner as the corresponding steps in its corresponding method claim. Additionally, the rationale and motivation to combine the Berlin in view of Sakaguchi, Fartaria, Florent, and Stewart references, presented in rejection of Claim 2, apply to this claim. Finally, the combination of the Berlin in view of Sakaguchi, Fartaria, Florent, and Stewart references discloses a processor, i.e., processing system, (for example, see Berlin, Paragraph 183).
Claim 19 recites a system with elements corresponding to the steps recited in Claim 4. Therefore, the recited elements of this claim are mapped to the proposed combination in the same manner as the corresponding steps in its corresponding method claim. Additionally, the rationale and motivation to combine the Berlin in view of Sakaguchi, Fartaria, Florent, and Stewart references, presented in rejection of Claim 2, apply to this claim. Finally, the combination of the Berlin in view of Sakaguchi, Fartaria, Florent, and Stewart references discloses a processor, i.e., processing system, (for example, see Berlin, Paragraph 183).
Claim 20 recites a system with elements corresponding to the steps recited in Claim 5. Therefore, the recited elements of this claim are mapped to the proposed combination in the same manner as the corresponding steps in its corresponding method claim. Additionally, the rationale and motivation to combine the Berlin in view of Sakaguchi, Fartaria, Florent, and Stewart references, presented in rejection of Claim 2, apply to this claim. Finally, the combination of the Berlin in view of Sakaguchi, Fartaria, Florent, and Stewart references discloses a processor, i.e., processing system, (for example, see Berlin, Paragraph 183).
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Berlin in view of Sakaguchi, Fartaria, Florent, and Bruch-el et al. (US 20220335612 A1).
Regarding Claim 6, the combination of references of Berlin in view of Sakaguchi, Fartaria, and Florent does not explicitly teach "The computer-implemented method of claim 1, wherein the reference image frame is selected by: determining which image frame of a first N frames in the sequence of contrast-enhanced image frames has a largest average intensity, wherein N is a predetermined number; and selecting the determined image frame as the reference image frame".
In an analogous field of endeavor, Bruch-el teaches "The computer-implemented method of claim 1, wherein the reference image frame is selected by: determining which image frame of a first N frames in the sequence of contrast-enhanced image frames has a largest average intensity, wherein N is a predetermined number; and selecting the determined image frame as the reference image frame"; (Bruch-el, Paras. 37 and 85, teaches choosing an image from the angiogram video including one or more images, i.e., a predetermined number of frames in the video, wherein the optimal image is chosen to obtain structural data wherein the optimal image is an image showing the maximum amount of contrast agent, i.e., selecting a determined image frame for reference by determining which frame of the sequence of contrast-enhanced frames has the largest average intensity indicating contrast density).
It would have been obvious to one having ordinary skill in the art before the effective filing date to modify the invention of Berlin, Sakaguchi, Fartaria, and Florent by including the determination of the reference image frame being the image frame with the largest average intensity taught by Bruch-el. One of ordinary skill in the art would be motivated to combine the references since it improves accuracy of results (Bruch-el, Para. 68, teaches the motivation of combination to be to provide an optimal image that shows the most detail to improve accuracy of results).
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date.
Claims 7, 14, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Berlin in view of Sakaguchi, Fartaria, Florent, and Yoshida et al. (US 20210228174 A1).
Regarding Claim 7, the combination of references of Berlin in view of Sakaguchi, Fartaria, and Florent does not explicitly teach "The computer-implemented method of claim 1, wherein the reference image frame is an image frame in which the contrast agent density is the highest in the sequence of contrast-enhanced image frames".
In an analogous field of endeavor, Yoshida teaches "The computer-implemented method of claim 1, wherein the reference image frame is an image frame in which the contrast agent density is the highest in the sequence of contrast-enhanced image frames"; (Yoshida, Para. 6, teaches the optimum reference image frame having the highest filling degree of a contrast agent, reference image frame is an image frame in which the contrast agent density is the highest in the sequence of frames).
It would have been obvious to one having ordinary skill in the art before the effective filing date to modify the invention of Berlin, Sakaguchi, Fartaria, and Florent by including the highest contrast agent density image being the reference image taught by Yoshida. One of ordinary skill in the art would be motivated to combine the references since it easily and properly selects a moving image (Yoshida, Para. 7, teaches the motivation of combination to be to easily and properly select a moving image and a frame feeding operation).
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date.
Claim 14 recites a system with elements corresponding to the steps recited in Claim 7. Therefore, the recited elements of this claim are mapped to the proposed combination in the same manner as the corresponding steps in its corresponding method claim. Additionally, the rationale and motivation to combine the Berlin, Sakaguchi, Fartaria, Florent, and Yoshida references, presented in rejection of Claim 7, apply to this claim. Finally, the combination of the Berlin, Sakaguchi, Fartaria, Florent, and Yoshida references discloses a processor, i.e., processing system, (for example, see Berlin, Paragraph 183).
Claim 16 recites a computer-readable storage medium storing a program with instructions corresponding to the steps recited in Claim 7. Therefore, the recited programming instructions of this claim are mapped to the proposed combination in the same manner as the corresponding steps in its corresponding method claim. Additionally, the rationale and motivation to combine the Berlin, Sakaguchi, Fartaria, Florent, and Yoshida references, presented in rejection of Claim 7, apply to this claim. Finally, the combination of the Berlin, Sakaguchi, Fartaria, Florent, and Yoshida references discloses a computer readable storage medium (for example, see Berlin, Paragraph 183).
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Berlin in view of Sakaguchi, Fartaria, Florent, and Bordes et al. (US 20150248746 A1).
Regarding Claim 9, the combination of references of Berlin in view of Sakaguchi, Fartaria, and Florent does not explicitly teach "The computer-implemented method of claim 1, wherein the step of correcting the set of one or more image frames in the sequence of image frames comprises: defining, for each image frame in the set of one or more image frames, a function based on histogram matching such that gray-value statistics of at least a part of the image frame are aligned to gray-value statistics of the region of interest in the reference image frame; and applying, for each image frame in the set of one or more image frames, the function defined for the image frame to at least a part of the image frame".
In an analogous field of endeavor, Bordes teaches "The computer-implemented method of claim 1, wherein the step of correcting the set of one or more image frames in the sequence of image frames comprises: defining, for each image frame in the set of one or more image frames, a function based on histogram matching such that gray-value statistics of at least a part of the image frame are aligned to gray-value statistics of the region of interest in the reference image frame"; (Bordes, Paras. 34-46, teaches determining a histogram and a cumulative histogram for a current block of an image in the sequence of images and a reference block of a reference image wherein a mapping function is computed for the reference block resulting in a corrected luminance block used as a prediction for coding the current block luminance values, i.e., defining a histogram matching function for each image frame of a set of image frames such that histogram matching is performed to align gray value statistics of a region of the image with gray-value statistics of a reference region of the reference image frame);
"and applying, for each image frame in the set of one or more image frames, the function defined for the image frame to at least a part of the image frame"; (Bordes, Paras. 34-46, teaches determining a histogram and a cumulative histogram for a current block of an image in the sequence of images and a reference block of a reference image wherein a mapping function is computed for the reference block resulting in a corrected luminance block used as a prediction for coding the current block luminance values, i.e., the function is applied to at least part of the image frame being the current block of the image).
It would have been obvious to one having ordinary skill in the art before the effective filing date to modify the invention of Berlin, Sakaguchi, Fartaria, and Florent by including the histogram matching function of statistics of part of an image to align them with the region of the reference image taught by Bordes. One of ordinary skill in the art would be motivated to combine the references since it improves prediction accuracy and efficiency (Bordes, Para. 19, teaches the motivation of combination to be to improve inter-view prediction and increase the coding efficiency of the sequence of images).
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date.
Conclusion
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/ANDREW S BUDISALICH/Examiner, Art Unit 2662
/AMANDEEP SAINI/Supervisory Patent Examiner, Art Unit 2662
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