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 .
Status of Claims
Claims 1 and 3-19 are pending.
Claims 10-14 are withdrawn from prosecution.
Claims 1-9 and 15-19 are currently rejected.
Response to Arguments
The current office action is a second non-final rejection.
Applicant's arguments in Applicant’s responses filed 10/27/2025 with respect to the rejection of claim 1 under have been fully considered but they are not persuasive.
Applicant remarks on page 10 that Olstad, B., US 20040116810 A1 fails to teach a time variance of brightness values of moving image data as required by claim 1.
Examiner respectfully disagrees.
[0021] describes characterizing a moving structure, a heart, by a set of analytic parameter values corresponding to anatomical points within a myocardial segment of the heart. The set of analytic parameter values include tissue velocity values, for which a description of time variance graph is produced in fig. 5 and [0034] as an example, and B-mode tissue intensity values. [0029] even states that “The analytic parameter values (e.g. tissue velocity values) corresponding to the desired myocardial segment 220 are automatically separated from the parameter values of cavities and other cardiac structure of the heart by processor 50 using, for example, B-mode tissue intensity in conjunction with a segmentation algorithm in accordance with an embodiment of the present invention”. Hence, the profile 350 of tracked analytic parameter values, an example of which is velocity parameter over time as shown in fig. 5, also represents changes in B-mode tissue intensity values over time.
Applicant further remarks on pages 11-12 that the steps in claims 1 and 19 transform the image data into display information and hence amount to a practical application, with reference to In re Abele Federal circuit court decision. However, according to MPEP 2106.04(a)(2)(I)(C), “calculating the difference between local and average data values” as achieved in In re Abele, 684 F.2d 902, 903, 214 USPQ 682, 683-84 (CCPA 1982), falls under the mathematical calculations grouping of mathematical concepts in the abstract ideas groupings. In other words, the limitations do not amount to no more than mathematical calculations that can be performed by hand.
Hence, the claims stand rejected.
Withdrawn Rejections
Pursuant of Applicant’s amendments filed 10/27/2025, the rejection of claims 9-10 under 35 U.S.C. 112(b) have been withdrawn
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Statutory Category: YES – Claim 1 recites An ultrasound diagnosis apparatus comprising processing circuitry and, therefore, is a device.
Step 2A, Prong 1, Judicial Exception: YES - The claim recites the following limitations:
“calculate a time variance of brightness values of the moving image data at each position in the moving image data; and determine a position of a cardiac apex of the fetal heart or a position of an atrial blood flow entrance part of the fetal heart by using information of the calculated time variance of the brightness values of the acquired moving image data”.
This limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “processing circuitry”, nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “processing circuitry” language, the claim encompasses a user simply obtaining printed copies of the time series of ultrasound moving images and through visual inspection determining positions of the cardiac apex of the fetal heart or a position of an atrial blood flow entrance part of the fetal heart based on brightness or intensity values. The mere nominal recitation of a generic network appliance does not take the claim limitation out of the mental processes grouping. Thus, the claim recites a mental process.
Step 2A, Prong 2, Integrated into Practical Application: No - The claim recites additional elements: “acquire two- or three-dimensional ultrasonic moving image data rendering a fetal heart and cause a display to display information indicating the determined position of the cardiac apex or the atrial blood flow entrance part”. The image acquisition step is recited at a high level of generality (i.e., as a general means of acquiring and displaying data), and amounts to mere data gathering, which is a form of insignificant pre-extra-solution activity. The processing circuitry that performs the image acquisition step is also recited at a high level of generality, and merely automates the image acquisition step. Each of the additional limitations is no more than mere instructions to apply the exception using a generic computer component (the processing circuitry).
The combination of these additional elements is no more than mere instructions to apply the exception using a generic computer component (processing circuitry). Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to the abstract idea.
Step 2B, Inventive Concept: No - As discussed with respect to Step 2A Prong Two, the additional elements in the claim amount to no more than mere instructions to apply the exception using a generic computer component. The same analysis applies here in 2B, i.e., mere instructions to apply an exception on a generic computer cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. Under the 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B. Here, the image acquisition and displaying steps were considered to be extra-solution activity in Step 2A, and thus it is re-evaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The background of the example does not provide any indication that the processing circuitry is anything other than a generic, off-the-shelf computer component, and the Symantec, TLI, and OIP Techs. court decisions cited in MPEP 2106.05(d)(II) indicate that mere collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here). Accordingly, a conclusion that the ultrasonic image acquisition and displaying steps are well-understood, routine, conventional activity is supported under Berkheimer Option 2. For these reasons, there is no inventive concept in the claim, and thus it is ineligible.
Claim 3 recites “wherein the processing circuitry is further configured to estimate (1) a long axis of the fetal heart, (2) both of the long axis and a short axis of the fetal heart, or (3) a center position of the fetal heart, and the processing circuitry is further configured to determine the position of the cardiac apex or the position of the atrial blood flow entrance part based on the estimated long axis, both the estimated long axis and the estimated short axis, or the estimated center position” which comprises further mental steps of estimating regions of interest within the image that fail to integrate the earlier mental steps into a practical application.
Claim 4 recites “wherein the processing circuitry is further configured to cause the display to display the information indicating the position of the cardiac apex or the information indicating the position of the atrial blood flow entrance part at a position along a long axis direction of the fetal heart” which is mere data presentation comprising insignificant post-extrasolution activity and hence fails to incorporate the judicial exception into a practical application.
Claim 5 recites “wherein the processing circuitry is further configured to estimate information about a position of the fetal heart or information about a posture of the fetal heart” which comprises further mental steps of estimating regions of interest within the image that fail to integrate the earlier mental steps into a practical application.
Claim 6 recites “wherein the processing circuitry is further configured to estimate a region satisfying a condition where a variance value of a time variance image of the moving image data exceeds a threshold value as a region of a tissue of the fetal heart” which comprises thresholding steps to estimate the region of interest. This step is a mental step and also fails to integrate the determination step of claim 1 into a practical application.
Claim 7 recites “wherein the processing circuitry is further configured to extract a variance distribution image as the region of the tissue of the fetal heart from the time variance image of the moving image data, and the processing circuitry is further configured to cause a display to display an image in which information indicating the position of the cardiac apex or information indicating the position of the atrial blood flow entrance part is superimposed on the variance distribution image”. The recitation comprises further image processing steps to extract features within the region of interest in the image, tantamount to mental step identified for claim 1. The claim further include data presentation steps that comprise insignificant post-extrasolution activity and hence fails to incorporate the judicial exception into a practical application.
Claim 8 recites “wherein the processing circuitry is further configured to estimate (1) a long axis of the fetal heart, (2) both of the long axis and a short axis of the fetal heart, or (3) a center position of the fetal heart, and the processing circuitry is further configured to cause the display to display the information indicating the position of the cardiac apex or the information indicating the position of the atrial blood flow entrance part based on the estimated long axis, both of the estimated long axis and the estimated short axis, or the estimated center position”. The recitation comprises further image processing steps to extract features within the region of interest in the image, tantamount to mental step identified for claim 1. The claim further include data presentation steps that comprise insignificant post-extrasolution activity and hence fails to incorporate the judicial exception into a practical application.
Claim 9 recites “wherein the processing circuitry is further configured to: obtain distribution information of a tissue position of the fetal heart by regarding a region satisfying a condition where a variance value of a time variance image of the moving image data exceeds a threshold value as a region of a tissue of the fetal heart, obtain a plurality of eigenvectors from a principal component analysis related to the distribution information of the tissue position, set a plurality of regions extending parallel to directions of the plurality of eigenvectors respectively, each having a width, in a surrounding of the center position, detect, from among the plurality of regions, a region in which either a sum or an average value of image values of the time variance image is largest as a fetal heart valve region, as the region of the tissue of the the fetal heart, determine a direction of an eigenvector parallel to the fetal heart valve region as the short axis of the fetal heart, and determines a direction perpendicular to a width direction of the fetal heart valve region as the long axis of the fetal heart”. The recitation comprises further image processing steps to extract features within the region of interest in the image, tantamount to mental step identified for claim 1, and fail to integrate the mental step in claim 1 into a practical application.
Claim 15 recites “wherein the processing circuitry is further configured to: determine a region of a tissue of the fetal heart by using information about the calculated time variance of the brightness values of the moving image data at each position; and estimate the position of the cardiac apex of the fetal heart within the region of the tissue of the fetal heart or the position of the atrial blood flow entrance part of the fetal heart within the determined region of the tissue of the fetal heart”, which comprise further mental steps of region of interest determinations, which fail to integrate the mental step in claim 1 into a practical application.
Claim 16 recites “wherein the processing circuitry is further configured to estimate the position of the cardiac apex of the fetal heart or the position of the atrial blood flow entrance part of the fetal heart by using distribution information of the calculated time variance of the brightness values in the determined region of the tissue of the fetal heart”, which comprises a mental step of position estimation of the cardiac apex, hence failing to incorporate the mental step in claim 1 into a practical application.
Claim 17 recites “wherein the processing circuitry is further configured to estimate at least one of a long axis of the fetal heart, both the long axis and a short axis of the fetal heart, and a center position of the fetal heart by using distribution information of the time variance of the brightness values in the determined region of the tissue of the fetal heart, and estimate the position of the cardiac apex of the fetal heart or the position of the atrial blood flow entrance part of the fetal heart based on the at least one of the long axis of the fetal heart, both the long axis and the short axis of the fetal heart, and the center position of the fetal heart, which together comprise further mental steps of region of interest determinations in a manner which fails to integrate the mental steps in claim 1 into a practical application.
Claim 18 recites “wherein the processing circuitry is further configured to estimate the position of the cardiac apex of the fetal heart or the position of the atrial blood flow entrance part of the fetal heart by using a result of principal component analysis concerning distribution infornation of the calculated time variance of the brightness values in the determined region of the tissue of the fetal heart.
Step 1: Statutory Category: YES – Claim 19 recites An ultrasonic diagnostic method and, therefore, is a process.
Step 2A, Prong 1, Judicial Exception: YES - The claim recites the following limitations:
“calculating a time variance of brightness values of the moving image data at each position in the moving image data; and determining a position of a cardiac apex of the fetal heart or a position of an atrial blood flow entrance part of the fetal heart by using information of the calculated time variance of the brightness values of the acquired moving image data”.
This limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. That is nothing in the claim element precludes the step from practically being performed in the mind. For example, the claim encompasses a user simply obtaining printed copies of the time series of ultrasound moving images and through visual inspection determining positions of the cardiac apex of the fetal heart or a position of an atrial blood flow entrance part of the fetal heart based on brightness or intensity values.
Step 2A, Prong 2, Integrated into Practical Application: No - The claim recites additional elements: “acquiring two- or three-dimensional ultrasonic moving image data rendering a fetal heart and causing a display to display information indicating the determined position of the cardiac apex or the atrial blood flow entrance part”. The image acquisition step is recited at a high level of generality (i.e., as a general means of acquiring and displaying data), and amounts to mere data gathering, which is a form of insignificant pre-extra-solution activity.
The combination of these additional elements is no more than mere instructions to apply the judicial exception. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to the abstract idea.
Step 2B, Inventive Concept: No - As discussed with respect to Step 2A Prong Two, the additional elements in the claim amount to no more than mere instructions to apply the judicial exception. The same analysis applies here in 2B, i.e., mere instructions to apply an exception cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. Under the 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B. Here, the image acquisition and displaying steps were considered to be extra-solution activity in Step 2A, and thus it is re-evaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The Symantec, TLI, and OIP Techs. court decisions cited in MPEP 2106.05(d)(II) indicate that mere collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here). Accordingly, a conclusion that the ultrasonic image acquisition and displaying steps are well-understood, routine, conventional activity is supported under Berkheimer Option 2. For these reasons, there is no inventive concept in the claim, and thus it is ineligible.
Claim Objections
Claim 19 is objected to because of the following informalities:
Claim 19 should be amended to include a colon as such: --…method, comprising: --.
Appropriate correction is required.
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.
Claims 1-2, 5-7, 15-16 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Olstad, B., US 20040116810 A1.
Regarding claim 1, Olstad teaches an ultrasound diagnosis apparatus comprising processing circuitry (see fig. 1 and [0022] for the ultrasonic machine 5 comprising a Doppler processor and a non-Doppler processor) configured to:
acquire two- or three-dimensional ultrasonic moving image data rendering a fetal heart ([0028]-[0029] disclose acquiring ultrasound images in a tissue velocity imaging mode of a moving cardiac structure. NB: while the claims include a fetal heart, it is not deemed to change the scope of the claims so prior art the only mention heart or cardiac tissue are interpreted to read on the claims);
calculate a time variance of tissue velocity values of the moving image data at each position in the moving image data (reproduced fig. 5 below shows a profile or graph of velocity parameter changes with respect to time variance, with [0034] stating that “The upper part of FIG. 5 shows a resultant tracked velocity parameter profile 350 of a designated anatomical point (e.g. 295) in the image as a function of time for a complete cardiac cycle. The velocity scale 390 shows the change in velocity over a time axis 401 in, for example, units of cm/sec. The lower part of FIG. 5 shows the corresponding resultant longitudinal motion parameter profile 370 (time-integrated velocity profile, S.sub.1, S.sub.2, . . . . , S.sub.n) of the same designated anatomical point (e.g. 295) in the image”);
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determine a position of a cardiac apex of the fetal heart or a position of an atrial blood flow entrance part of the fetal heart by using information of the calculated time variance of the tissue velocity values of the acquired moving image data ([0021] indicates that the “moving structure is characterized by a set of analytic parameter values corresponding to anatomical points within a myocardial segment of the heart. The set of analytic parameter values may comprise, for example, tissue velocity values, time-integrated tissue velocity values, B-mode tissue intensity values…”. [0034] then indicates tracking an exemplary analytic parameter value, that is tissue velocity, over time, as shown in fig. 5. Meaning the B-mode tissue intensity values are tracked over time, much the same way that the tissue velocity is tracked over time); and
cause a display to display information indicating the determined position of the cardiac apex or the atrial blood flow entrance part ([0050] states “discrete anatomical points in the image at the longitudinal depths 298 and 299 of the anatomical landmarks (apex 292 and AV-plane 296) are automatically labeled with indicia 410 and 420 as shown in FIG. 7. The anatomical points are continually tracked, using the techniques described previously, as imaging continues. The positions of the indicia 410 and 420 are continuously updated and displayed to follow the tracked anatomical points corresponding to the anatomical landmarks”).
Olstad does not explicitly state calculating a time variance of brightness values.
However, [0021] describes characterizing a moving structure, a heart, by a set of analytic parameter values corresponding to anatomical points within a myocardial segment of the heart. The set of analytic parameter values include tissue velocity values, for which a description of time variance graph is produced in fig. 5 and [0034] as an example, and B-mode tissue intensity values. [0029] even states that “The analytic parameter values (e.g. tissue velocity values) corresponding to the desired myocardial segment 220 are automatically separated from the parameter values of cavities and other cardiac structure of the heart by processor 50 using, for example, B-mode tissue intensity in conjunction with a segmentation algorithm in accordance with an embodiment of the present invention”. Hence, one of ordinary skill in the art would interpret the profile 350 of tracked analytic parameter values, an example of which is velocity parameter over time as shown in fig. 5, as representing changes in B-mode tissue intensity values over time.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Olstad for calculating a time variance of brightness values, as indicated in [0021], as such modification would enable determination of real-time location and tracking of anatomical landmarks of the heart ([0021]).
Regarding claim 2, Olstad further teaches wherein the processing circuitry further causes a display ([0024] discloses a display) to display information indicating the position of the cardiac apex or information indicating the position of the atrial blood flow entrance part
Regarding claim 5, Olstad wherein the processing circuitry is further configured to estimate information about a position of the fetal heart or information about a posture of the fetal heart ([0047] states that “In step 130 of FIG. 2, the time integrated velocity parameter value S.sub.int for each of the designated and tracked anatomical points 290 (the motion gradient profile 370) is used by processor 50 to locate the longitudinal depth position 299 of the apex 292 and the longitudinal depth position 298 of the AV-plane 296 of the heart in the image”).
Regarding claim 6, Olstad further teaches wherein the processing circuitry is further configured to estimate a region satisfying a condition where a variance value of a time variance image of the moving image data exceeds a threshold value as a region of a tissue of the fetal heart ([0029] states “The analytic parameter values (e.g. tissue velocity values) corresponding to the desired myocardial segment 220 are automatically separated from the parameter values of cavities and other cardiac structure of the heart by processor 50 using, for example, B-mode tissue intensity in conjunction with a segmentation algorithm in accordance with an embodiment of the present invention. Anatomical points 290 (see FIG. 4) are automatically designated within the myocardial segment 220. Well-known segmentation, thresholding, centroiding, and designation techniques operating on at least one of the set of analytic parameter values are used to establish the designated points 290 in accordance with an embodiment of the present invention”. In this case, the thresholding based on B-mode tissue intensity reads on the recited thresholding step).
Regarding claim 7, Olstad further teaches wherein the processing circuitry is further configured to extract a variance distribution image as the region of the tissue of the fetal heart from the time variance image of the moving image data ([0048]-[0049] describe extracting images with peaks indicative of motion values), and the processing circuitry is further configured to cause a display to display an image in which information indicating the position of the cardiac apex or information indicating the position of the atrial blood flow entrance part is superimposed on the variance distribution image ([0006]-[0007] disclose overlaying indicia onto the image of the heart corresponding to positions of the anatomical landmarks).
Regarding claim 15, Olstad teaches all the limitations of claim 1.
wherein the processing circuitry is further configured to: determine a region of a tissue of the fetal heart by using information about the calculated time variance of the tissue velocity values of the moving image data at each position ([0037] states that “Processor 50 selects a velocity value V.sub.i for a designated anatomical point in the image from a spatial set of estimated tissue velocity values corresponding to a time T where i=1 and is called T.sub.1. Processor 50 computes the motion value S.sub.i for the designated anatomical point (e.g. 295), as S.sub.i=T*(V.sub.1+V.sub.2+ . . . +V.sub.i) [1]”); and
estimate the position of the cardiac apex of the fetal heart within the region of the tissue of the fetal heart or the position of the atrial blood flow entrance part of the fetal heart within the determined region of the tissue of the fetal heart ([0047] states that “In step 130 of FIG. 2, the time integrated velocity parameter value S.sub.int for each of the designated and tracked anatomical points 290 (the motion gradient profile 370) is used by processor 50 to locate the longitudinal depth position 299 of the apex 292 and the longitudinal depth position 298 of the AV-plane 296 of the heart in the image in accordance with an embodiment of the present invention”).
Olstad does not explicitly state a time variance of brightness values.
However, [0021] of Olstad describes characterizing a moving structure, a heart, by a set of analytic parameter values corresponding to anatomical points within a myocardial segment of the heart. The set of analytic parameter values include tissue velocity values, for which a description of time variance graph is produced in fig. 5 and [0034] as an example, and B-mode tissue intensity values. [0029] even states that “The analytic parameter values (e.g. tissue velocity values) corresponding to the desired myocardial segment 220 are automatically separated from the parameter values of cavities and other cardiac structure of the heart by processor 50 using, for example, B-mode tissue intensity in conjunction with a segmentation algorithm in accordance with an embodiment of the present invention”. Hence, one of ordinary skill in the art would interpret the profile 350 of tracked analytic parameter values, an example of which is velocity parameter over time as shown in fig. 5, as representing changes in B-mode tissue intensity values over time.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Olstad for calculating a time variance of brightness values, as indicated in [0021], as such modification would enable determination of real-time location and tracking of anatomical landmarks of the heart ([0021]).
Regarding claim 16, Olstad further teaches wherein the processing circuitry is further configured to estimate the position of the cardiac apex of the fetal heart or the position of the atrial blood flow entrance part of the fetal heart by using distribution information of the calculated time variance of the tissue velocity values in the determined region of the tissue of the fetal heart ([0047] states that “In step 130 of FIG. 2, the time integrated velocity parameter value S.sub.int for each of the designated and tracked anatomical points 290 (the motion gradient profile 370) is used by processor 50 to locate the longitudinal depth position 299 of the apex 292 and the longitudinal depth position 298 of the AV-plane 296 of the heart in the image in accordance with an embodiment of the present invention”, the longitudinal depth position being the position of the cardiac apex).
Olstad does not explicitly state a time variance of brightness values.
However, [0021] of Olstad describes characterizing a moving structure, a heart, by a set of analytic parameter values corresponding to anatomical points within a myocardial segment of the heart. The set of analytic parameter values include tissue velocity values, for which a description of time variance graph is produced in fig. 5 and [0034] as an example, and B-mode tissue intensity values. [0029] even states that “The analytic parameter values (e.g. tissue velocity values) corresponding to the desired myocardial segment 220 are automatically separated from the parameter values of cavities and other cardiac structure of the heart by processor 50 using, for example, B-mode tissue intensity in conjunction with a segmentation algorithm in accordance with an embodiment of the present invention”. Hence, one of ordinary skill in the art would interpret the profile 350 of tracked analytic parameter values, an example of which is velocity parameter over time as shown in fig. 5, as representing changes in B-mode tissue intensity values over time.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Olstad for calculating a time variance of brightness values, as indicated in [0021], as such modification would enable determination of real-time location and tracking of anatomical landmarks of the heart ([0021]).
Regarding claim 19, Olstad teaches an ultrasonic diagnostic method (the abstract discloses “a method and apparatus for generating an image responsive to moving cardiac structure and for locating anatomical landmarks of the heart by generating received signals in response to ultrasound waves transmitted into and then backscattered from the moving cardiac structure over a time period”), comprising
acquiring two- or three-dimensional ultrasonic moving image data rendering a fetal heart ([0028]-[0029] disclose acquiring ultrasound images in a tissue velocity imaging mode of a moving cardiac structure. NB: while the claims include a fetal heart, it is not deemed to change the scope of the claims so prior art the only mention heart or cardiac tissue are interpreted to read on the claims);
calculating a time variance of tissue velocity values of the moving image data at each position in the moving image data (reproduced fig. 5 below shows a profile or graph of velocity parameter changes with respect to time variance, with [0034] stating that “The upper part of FIG. 5 shows a resultant tracked velocity parameter profile 350 of a designated anatomical point (e.g. 295) in the image as a function of time for a complete cardiac cycle. The velocity scale 390 shows the change in velocity over a time axis 401 in, for example, units of cm/sec. The lower part of FIG. 5 shows the corresponding resultant longitudinal motion parameter profile 370 (time-integrated velocity profile, S.sub.1, S.sub.2, . . . . , S.sub.n) of the same designated anatomical point (e.g. 295) in the image”);
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determining a position of a cardiac apex of the fetal heart or a position of an atrial blood flow entrance part of the fetal heart by using information of the calculated time variance of the tissue velocity values of the acquired moving image data ([0021] indicates that the “moving structure is characterized by a set of analytic parameter values corresponding to anatomical points within a myocardial segment of the heart. The set of analytic parameter values may comprise, for example, tissue velocity values, time-integrated tissue velocity values, B-mode tissue intensity values…”. [0034] then indicates tracking an exemplary analytic parameter value, that is tissue velocity, over time, as shown in fig. 5. Meaning the B-mode tissue intensity values are tracked over time, much the same way that the tissue velocity is tracked over time); and
causing a display to display information indicating the determined position of the cardiac apex or the atrial blood flow entrance part ([0050] states “discrete anatomical points in the image at the longitudinal depths 298 and 299 of the anatomical landmarks (apex 292 and AV-plane 296) are automatically labeled with indicia 410 and 420 as shown in FIG. 7. The anatomical points are continually tracked, using the techniques described previously, as imaging continues. The positions of the indicia 410 and 420 are continuously updated and displayed to follow the tracked anatomical points corresponding to the anatomical landmarks”).
Olstad does not explicitly state calculating a time variance of brightness values.
However, [0021] describes characterizing a moving structure, a heart, by a set of analytic parameter values corresponding to anatomical points within a myocardial segment of the heart. The set of analytic parameter values include tissue velocity values, for which a description of time variance graph is produced in fig. 5 and [0034] as an example, and B-mode tissue intensity values. [0029] even states that “The analytic parameter values (e.g. tissue velocity values) corresponding to the desired myocardial segment 220 are automatically separated from the parameter values of cavities and other cardiac structure of the heart by processor 50 using, for example, B-mode tissue intensity in conjunction with a segmentation algorithm in accordance with an embodiment of the present invention”. Hence, one of ordinary skill in the art would interpret the profile 350 of tracked analytic parameter values, an example of which is velocity parameter over time as shown in fig. 5, as representing changes in B-mode tissue intensity values over time.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Olstad for calculating a time variance of brightness values, as indicated in [0021], as such modification would enable determination of real-time location and tracking of anatomical landmarks of the heart ([0021]).
Claims 3-4, 8, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Olstad in view of Lotjonen, J., US 20070088209 A1.
Regarding claim 3, Olstad teaches all the limitations of claim 2 above.
Olstad fails to teach wherein the processing circuitry is further configured to estimate (1) a long axis of the fetal heart, (2) both of the long axis and a short axis of the fetal heart, or (3) a center position of the fetal heart, and the processing circuitry determines the position of the cardiac apex or the position of the atrial blood flow entrance part based on the estimated long axis, both the estimated long axis and the estimated short axis, or the estimated center position.
However, Lotjonen teaches a method, implemented on a computer with computer readable medium (claim 41) for cardiac analysis where during scanning (i.e. imaging sessions) the subject, a short-axis (SA) and a long-axis (LA) image volumes are acquired using a known imaging protocol adopted for cardiac subjects e.g. magnetic resonance imaging or other imaging system producing slice images of different levels of the region of interest. Image sets in this description refers to such an image sets that are formed of image slices. Claim 29 indicates that the imaging modality is ultrasound imaging. Also see [0018]. Lotjonen further states in [0019] that “Simultaneous tracking of short-axis (SA) and long-axis (LA) images broadens the heart image processing. The LA images provide comprehensive information especially on tracking the movement of the basal and apical regions of the ventricles in the heart's long-axis direction” and [0020] states that “The image sets that are acquired at least from short-axis and long-axis contribute differently on various regions in the algorithm. For example, the information on the apex of the heart can be extracted from long-axis images as the information on the medial parts of the heart can be retrieved from short-axis images. The simultaneous tracking of two image orientations allows to track more precisely the basal and apical movement of the ventricles. In addition, the motion of the atria can be tracked”.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Olstad wherein the processing circuitry is further configured to estimate (1) a long axis of the fetal heart, (2) both the long axis and a short axis of the fetal heart, or (3) a center position of the fetal heart, and the processing circuitry is further configured to determine the position of the cardiac apex or the position of the atrial blood flow entrance part based on the estimated long axis, both the estimated long axis and the estimated short axis, or the estimated center position, as taught by Lotjonen, as such modification allows to track more precisely the basal and apical movement of the ventricles ([0020]).
Regarding claim 4, Olstad in view of Lotjonen teaches all the limitations of claim 3 above.
Olstad further teaches wherein the processing circuitry is further configured to cause the display to display the information indicating the position of the cardiac apex or the information indicating the position of the atrial blood flow entrance part at a position along a long axis direction of the fetal heart (see fig. 3 for the apical 4-chamber view of the heart which is along the long axis of the heart).
Regarding claim 8, Olstad teaches all the limitations of claim 7 above.
Olstad fails to teach wherein the processing circuitry is further configured to estimate (1) a long axis of the fetal heart, (2) both the long axis and a short axis of the fetal heart, or (3) a center position of the fetal heart, and the processing circuitry is further configured to cause the display to display the information indicating the position of the cardiac apex or the information indicating the position of the atrial blood flow entrance part based on the estimated long axis, both the estimated long axis and the estimated short axis, or the estimated center position.
However, Lotjonen teaches a method, implemented on a computer with computer readable medium (claim 41) for cardiac analysis where during scanning (i.e. imaging sessions) the subject, a short-axis (SA) and a long-axis (LA) image volumes are acquired using a known imaging protocol adopted for cardiac subjects e.g. magnetic resonance imaging or other imaging system producing slice images of different levels of the region of interest. Image sets in this description refers to such an image sets that are formed of image slices. Claim 29 indicates that the imaging modality is ultrasound imaging. Also see [0018]. Lotjonen further states in [0019] that “Simultaneous tracking of short-axis (SA) and long-axis (LA) images broadens the heart image processing. The LA images provide comprehensive information especially on tracking the movement of the basal and apical regions of the ventricles in the heart's long-axis direction” and [0020] states that “The image sets that are acquired at least from short-axis and long-axis contribute differently on various regions in the algorithm. For example, the information on the apex of the heart can be extracted from long-axis images as the information on the medial parts of the heart can be retrieved from short-axis images. The simultaneous tracking of two image orientations allows to track more precisely the basal and apical movement of the ventricles. In addition, the motion of the atria can be tracked”. See fig. 1 [0032] depict a representation of images with segmented volumes in the short axis and long axis directions. Claim 39 recites a displaying means for presenting images.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Olstad wherein the processing circuitry is further configured to estimate (1) a long axis of the fetal heart, (2) both the long axis and a short axis of the fetal heart, or (3) a center position of the fetal heart, and the processing circuitry is further configured to cause the display to display the information indicating the position of the cardiac apex or the information indicating the position of the atrial blood flow entrance part based on the estimated long axis, both the estimated long axis and the estimated short axis, or the estimated center position, as taught by Lotjonen, as such modification allows to track more precisely the basal and apical movement of the ventricles ([0020]).
Regarding claim 17, Olstad does not teach wherein the processing circuitry is further configured to estimate at least one of a long axis of the fetal heart, both the long axis and a short axis of the fetal heart, and a center position of the fetal heart by using distribution information of the time variance of the brightness values in the determined region of the tissue of the fetal heart, and estimate the position of the cardiac apex of the fetal heart or the position of the atrial blood flow entrance part of the fetal heart based on the at least one of the long axis of the fetal heart, both the long axis and the short axis of the fetal heart, and the center position of the fetal heart.
However, Lotjonen further teaches wherein the processing circuitry is further configured to estimate at least one of a long axis of the fetal heart, both the long axis and a short axis of the fetal heart, and a center position of the fetal heart by using distribution information of the time variance of the brightness values in the determined region of the tissue of the fetal heart, and estimate the position of the cardiac apex of the fetal heart or the position of the atrial blood flow entrance part of the fetal heart based on the at least one of the long axis of the fetal heart, both the long axis and the short axis of the fetal heart, and the center position of the fetal heart. Lotjonen states in [0019] that “Simultaneous tracking of short-axis (SA) and long-axis (LA) images broadens the heart image processing. The LA images provide comprehensive information especially on tracking the movement of the basal and apical regions of the ventricles in the heart's long-axis direction” and [0020] states that “The image sets that are acquired at least from short-axis and long-axis contribute differently on various regions in the algorithm. For example, the information on the apex of the heart can be extracted from long-axis images as the information on the medial parts of the heart can be retrieved from short-axis images. The simultaneous tracking of two image orientations allows to track more precisely the basal and apical movement of the ventricles. In addition, the motion of the atria can be tracked”. [0004] discloses using gray-value of each pixel exemplified in [0047].
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure modified Olstad wherein the processing circuitry is further configured to estimate at least one of a long axis of the fetal heart, both the long axis and a short axis of the fetal heart, and a center position of the fetal heart by using distribution information of the time variance of the brightness values in the determined region of the tissue of the fetal heart, and estimate the position of the cardiac apex of the fetal heart or the position of the atrial blood flow entrance part of the fetal heart based on the at least one of the long axis of the fetal heart, both the long axis and the short axis of the fetal heart, and the center position of the fetal heart, as taught by Lotjonen, as such modification allows to track more precisely the basal and apical movement of the ventricles ([0020]).
Claims 9 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Olstad in view of van der Kouwe, et al., US 20080103383 A1.
Regarding claim 9, Olstad teaches all the limitations of claim 3 above.
wherein the processing circuitry is further configured to: obtain distribution information of a tissue position of the fetal heart by regarding a region satisfying a condition where a variance value of a time variance image of the moving image data exceeds a threshold value as a region of a tissue of the fetal heart ([0029] states “The analytic parameter values (e.g. tissue velocity values) corresponding to the desired myocardial segment 220 are automatically separated from the parameter values of cavities and other cardiac structure of the heart by processor 50 using, for example, B-mode tissue intensity in conjunction with a segmentation algorithm in accordance with an embodiment of the present invention. Anatomical points 290 (see FIG. 4) are automatically designated within the myocardial segment 220. Well-known segmentation, thresholding, centroiding, and designation techniques operating on at least one of the set of analytic parameter values are used to establish the designated points 290 in accordance with an embodiment of the present invention”. In this case, the thresholding based on B-mode tissue intensity reads on the recited thresholding step),
The embodiment of Olstad relied upon for the rejection above fails to teach the processing circuitry is configured to detect, from among the plurality of regions, a region in which either a sum or an average value of image values of the time variance image is largest as a fetal heart valve region, the region of the tissue of the fetal heart.
However, [0055] states that In another alternative embodiment of the present invention, since the mitral valve is connected to the ventricle in the AV-plane, AV-plane localization may be inferred if the mitral valves may be localized. The mitral valves have characteristic shape that may be identified with B-mode imaging and are the tissue reflectors having the highest velocities in the heart. Also, color flow, PW-Doppler, and/or CW-Doppler of blood flow may be used to localize the AV-plane due to known flow singularities across the mitral valve at specific time in the cardiac cycle. [0043]-[0045] disclose temporally integrating the tracked velocity parameter profile array for each of the designated anatomical points 290.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure the embodiment [0021] of Olstad relied upon above, wherein the processing circuitry detects, from among the plurality of regions, a region in which either a sum or an average value of image values of the time variance image is largest as a fetal heart valve region, and as for the size of the fetal heart, as taught by the embodiment in [0055], to afford a relatively simple approach to automatically locate key anatomical landmarks of the heart, such as the apex and the AV-plane, and track the landmarks with a degree of convenience and accuracy previously unattainable in the prior art.
Olstad fails to teach that the processing circuitry is configured to obtain a plurality of eigenvectors from a principal component analysis related to the distribution information of the tissue position, the processing circuitry is configured to set a plurality of regions extending parallel to directions of the plurality of eigenvectors respectively and each having a width, in a surrounding of the center position, the processing circuitry is configured to determine a direction of an eigenvector parallel to the fetal heart valve region as the short axis of the fetal heart, and the processing circuitry is configured to determine a direction perpendicular to a width direction of the fetal heart valve region as the long axis of the fetal heart.
However, van der Kouwe teaches an image segmentation process (abstract) wherein the processing circuitry (processor of [0019]) is configured to obtain a plurality of eigenvectors from a principal component analysis related to the distribution information of the tissue position ([0048] describes a centroid method of calculating position, orientation, and shape of anatomical structures of interest [0047], [0048] stating that “The centroid method also calculates the covariance matrix for the voxel coordinates. The principal eigenvector is considered as the long axis of the structure. The second eigenvector is the wide axis of the structure and the cross product (remaining perpendicular direction) is the short axis”),
the processing circuitry is configured to set a plurality of regions extending parallel to directions of the plurality of eigenvectors respectively and each having a width, in a surrounding of the center position([0048] describes a centroid method of calculating position, orientation, and shape of anatomical structures of interest [0047], [0048] stating that “The centroid method also calculates the covariance matrix for the voxel coordinates. The principal eigenvector is considered as the long axis of the structure. The second eigenvector is the wide axis of the structure and the cross product (remaining perpendicular direction) is the short axis”. Here one eigenvector is normal to a second eigenvector),
the processing circuitry is configured to determine a direction of an eigenvector parallel to the target structure as the short axis of the target structure, and the processing circuitry is configured to determine a direction perpendicular to a width direction of the target structure region as the long axis of the target structure([0048] describes a centroid method of calculating position, orientation, and shape of anatomical structures of interest [0047], [0048] stating that “The centroid method also calculates the covariance matrix for the voxel coordinates. The principal eigenvector is considered as the long axis of the structure. The second eigenvector is the wide axis of the structure and the cross product (remaining perpendicular direction) is the short axis”. Here one eigenvector is normal to a second eigenvector).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Olstad wherein the processing circuitry is configured to obtain a plurality of eigenvectors from a principal component analysis related to the distribution information of the tissue position, the processing circuitry is configured to set a plurality of regions extending parallel to directions of the plurality of eigenvectors respectively and each having a width, in a surrounding of the center position, the processing circuitry is configured to determine a direction of an eigenvector parallel to the fetal heart valve region as the short axis of the fetal heart, and the processing circuitry is configured to determine a direction perpendicular to a width direction of the fetal heart valve region as the long axis of the fetal heart, as taught by van der Kouwe, to optimize the segmentation and identification of the structures of interest ([006]-[0007]).
Regarding claim 18, Olstad fails to teach wherein the processing circuitry is further configured to estimate the position of the cardiac apex of the fetal heart or the position of the atrial blood flow entrance part of the fetal heart by using a result of principal component analysis concerning distribution information of the calculated time variance of the brightness values in the determined region of the tissue of the fetal heart.
However, Kouwe further teaches wherein the processing circuitry is further configured to estimate the position of the cardiac apex of the fetal heart or the position of the atrial blood flow entrance part of the fetal heart by using a result of principal component analysis concerning distribution information of the calculated time variance of the brightness values in the determined region of the tissue of the fetal heart ([0048] describes a centroid method of calculating position, orientation, and shape of anatomical structures of interest [0047], [0048] stating that “The centroid method also calculates the covariance matrix for the voxel coordinates. The principal eigenvector is considered as the long axis of the structure. The second eigenvector is the wide axis of the structure and the cross product (remaining perpendicular direction) is the short axis” and [0020] states that “The image sets that are acquired at least from short-axis and long-axis contribute differently on various regions in the algorithm. For example, the information on the apex of the heart can be extracted from long-axis images as the information on the medial parts of the heart can be retrieved from short-axis images.”)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US-20040249281-A1 real-time extraction of wall function information within a heart, including temporal variations in wall motion and wall thickening, after locating and tracking certain anatomical landmarks of the heart.
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/FAROUK A BRUCE/ Examiner, Art Unit 3797