DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 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.
Claim(s) 1-4, 6, 11-16 and 19-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Urabe et al. (US Pub No. 2012/0296214) in view of Murashita et al. (JP 3802508) and Manai et al. (CA-2808484), or, as an alternative to Manai et al., Khaleel et al. (“Vessel Centerline Extraction using New Center of Gravity Equations”, March 2013). Note that the below rejection refers to the English translation of JP 3802508.
With regards to claims 1, 11, and 14, Urabe et al. disclose a system and method of ultrasound imaging, the method comprising:
acquiring a volumetric dataset with an ultrasound probe (1, 9) in a volumetric acquisition mode (paragraphs [0092], [0095], referring to the echo data being obtained from the array (9) of transducers and wherein the image generating section (17) generates 3D image data; paragraphs [0086]-[0088], referring to obtaining a stereoscopic (i.e. 3D) image; Figures 1-4, 6);
automatically identifying, with a processor, an object (i.e. carotid artery (6)) representing a structure-of-interest from the volumetric dataset (paragraph [0063], referring to the carotid artery (6) being the ROI; paragraphs [0090]-[0096], referring to the region of interest being set on the carotid artery (6) and defined to be as high as, and lower than, the branching point of the carotid artery (6) and referring to detecting the branches of the carotid artery and locating the carotid artery which appears as an almost circular cross section; paragraphs [0195]-[0196], referring to the detection of the carotid artery (6); Figures 4-6);
automatically identifying, with the processor, a straight line axis (4E, center axis/centerline of the carotid artery (6) [which extends in a generally straight direction and therefore would have a straight centerline at least extending through a portion of it’s length] in 3-dimensions, wherein the centerline passing through at least the sections of L2 and L3 would correspond to a straight line) of the structure-of-interest based on the object (paragraph [0095], referring to the vascular center detecting section (21) calculating the center position of the blood vessel based on the 3D image data; paragraph [0105], referring to the centerline 4E being generated by the probe guiding image generating section (23); paragraphs [0195]-[0196], referring to the vascular center detecting section (21) locating the center axis of the blood vessel; Figures 4-5, 9-10);
automatically calculating, with the processor, a probe position adjustment (i.e. arrow 4H) from a current probe position to enable the acquisition of a target scan plane of the structure-of-interest that either includes and is parallel to the axis or is perpendicular to the axis (paragraph [0085], referring to positioning the linear array (9) of transducers so that the array (9) of transducers is arranged substantially parallel to the direction in which the carotid artery (6) runs, and thus would be parallel to the center axis/centerline of the carotid artery; paragraphs [0094]-[0096], referring to displaying the blood vessel centering guide line 4C to see if the array (9) of transducers is arranged parallel to the carotid artery (6), wherein the probe (1) is determined to be arranged at the right position for detection when the center axis of the carotid artery (6) is aligned with the blood vessel centering guide line 4C; paragraphs [0097]-[0108], referring to the relative positions of the probe (1) and the carotid artery (6) being displayed on the monitor (4), along with a symbol 4H that prompts the operator to change the position of the probe (1) and the arrow (4H) prompting the operator to move the probe until it is confirmed that the probe (1) has been put in a right position on the carotid artery to detect the region of interest; Figures 1-5, 8-10);
presenting the probe position adjustment (4H) on a display device (4) (paragraphs [0097]-[0108], referring to the display of the symbol (4H) that prompts the operator to change the position of the probe (1) on the monitor (4); Figures 1, 9-8); and
applying the probe position adjustment to the ultrasound probe from the current probe position (paragraph [0101], referring to the operator changing the position of the probe (1) so that the probe origin marker (7c) thereof moves in the direction indicated by the arrow (4H), and therefore the probe position adjustment represented by 4H is applied to the ultrasound probe from the current position; paragraphs [0106]-[0109], referring to confirming that the probe (1) has been put in a right position on the carotid artery (6) to detect the region of interest; paragraph [0146], referring to, when the center of the carotid artery is either aligned with, or sufficiently close to, the centerline 4E, the swing of the array (9) of transducers is stopped; Figures 4-5, 9-10).
Further, with regards to claim 11, Urabe et al. disclose that their ultrasound imaging system comprises an ultrasound probe (1, 9) (paragraphs [0061], [0065]; Figures 1-4), a display device (4) (paragraph [0061]; Figures 1, 4) and a processor (3) in electronic communication with both the ultrasound probe (1, 9) and the display device (4), wherein the processor is configured to perform the above functions (paragraphs [0061]-[0063]; Figure 4), and wherein the processor (3) is further configured to control the ultrasound probe to acquire a two-dimensional dataset of the target scan plane in a two-dimensional acquisition mode after the probe position adjustment has been applied to the ultrasound probe (paragraphs [0061]-[0063]; paragraphs [0109]-[0112], referring to obtaining and displaying image data, such as image data representing the IMT measurable range; paragraph [0146], referring to, after the swing of the array (9) of the transducers is stopped, the same region of the carotid artery is irradiated with a beam in that state and the image representing that region is displayed on the monitor (4) as in ST4; Figures 4-5, 8-10, 14, note that the displayed images are 2D images);
However, though Urabe et al. do disclose automatically identifying a straight line axis (i.e. centerline of an artery that passes at least through the center of the vessel as depicted in sections L1 and L2 in Figure 6; see paragraphs [0095], [0105], [0195]-[0196]) of the structure-of-interest in 3-dimensions (see Figure 6), Urabe et al. do not specifically disclose that the identifying of the straight line axis/centerline comprises determining a single point representing center of gravity (i.e. a point representing a center of gravity [claim 11]) of the object, and passing the straight line through the single point representing the center of gravity (i.e. point [claim 11]).
Further, Urabe et al. do not specifically disclose that the point representing the center of gravity is determined “based on an assigned weight for each voxel in the object”.
Murashita et al. disclose an ultrasonic diagnostic apparatus that acquires three-dimensional image data, wherein an optimum cross section is set based on a reference axis based on a centroid point of the target tissue and an end point of the target tissue located farthest from the centroid point (paragraphs [0001]-[0002], [0006]-[0010]). A long axis inclination calculating unit (30) sets a left ventricular long axis as a straight line passing through two points, the barycentric point calculated by the barycentric detecting unit (26) and the long axis end point detected by the long axis end point detecting unit (28), wherein the barycentric point is calculated by detecting the center of gravity of the left ventricular cavity by acquiring the address of each voxel on which the left ventricular cavity extraction process has been performed from the three-dimensional data memory (paragraphs [0027]-[0030]; Figures 3A-3C, note that the center of gravity is determined as a single point, wherein a long axis of the object is determined by passing a straight line through the single point representing the center of gravity).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to substitute the technique for automatically identifying the straight line axis/centerline/long axis of Urabe et al. with the technique for automatically identifying an axis/centerline, wherein the identifying comprises determining a single point representing center of gravity (i.e. a point representing the center of gravity [claim 11]) of the object in 3-dimensions and passing a line [i.e. straight line in Urabe et al. as would define the centerline passing through at least sections L2 and L3 depicted in Figure 6 of Urabe et al.] through the single point representing the center of gravity (i.e. point [claims 11, 14]), as taught by Murashita et al., as the substitution of one known technique for automatically identifying the axis/centerline for another yields predictable results (i.e. effectively identify a centerline/long axis in an image volume) to one of ordinary skill in the art and further to determine an optimal cross-section (paragraphs [0006]-[0010]). One of ordinary skill in the art would have been able to carry out such a substitution and the results are reasonably predictable.
However, the above combined references do not specifically disclose that the point representing the center of gravity is determined “based on an assigned weight for each voxel in the object”.
Manai et al. disclose determining the center of gravity of a 3D model by assigning a weight to each of the voxels that form the 3D model and determine a center of gravity based on those assigned weights (paragraph [0029]).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to substitute the technique for determining the point representing the center of gravity of the above combined references with a technique for determining a point representing the center of gravity based on an assigned weighted for each voxel in the object, as taught by Manai et al., as the substitution of one known technique for determining the point representing the center of gravity for another yields predictable results (i.e. effectively providing the center of gravity) to one of ordinary skill in the art. One of ordinary skill in the art would have been able to carry out such a substitution and the results are reasonably predictable.
As an alternative to Manai et al.:
Khaleel et al. disclose a new approach to extract the centerlines of vessels using novel center of gravity equations, wherein the algorithm comprises of using a center of gravity (COG) calculation and connecting the final COG points by lines to determine the centerline in 2D or 3D angiograms (Abstract; pg. 2, left column, 3rd paragraph; Figure 2, note that connecting the final COG points by lines results in the above combined references as passing a straight line [associated with the carotid artery of Urabe et al.] through the center of gravity). The center of gravity is determined using Equations 9 and 10 which are based on an assigned weight (i.e. the terms “i” and “j” which respectively corresponds to the “x-factor” and “y-factor” which are weights assigned for every voxel in Eqs. 9 and 10) for every voxel in the object (Abstract, referring to determining the centerlines in 3D angiograms, and thus intensities for each partition/sub-part correspond to voxels; pg. 3, right column, 2nd full paragraph-pg. 4, left column, 2nd paragraph, see Equations 9 and 10; Figure 2). The approach for extracting the centerline is robust and time-saving (Abstract).
Therefore, alternatively, before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to substitute the technique for determining the point representing the center of gravity of the above combined references with a technique for determining a point representing the center of gravity based on an assigned weighted for each voxel in the object, as taught by Khaleel et al., as the substitution of one known technique for determining the point representing the center of gravity for another yields predictable results (i.e. effectively providing the center of gravity) to one of ordinary skill in the art and further is a robust and time-saving technique for determining a centerline of a vessel (Abstract). One of ordinary skill in the art would have been able to carry out such a substitution and the results are reasonably predictable.
With regards to claims 2 and 12, Urabe et al. disclose that their method further comprises acquiring a two-dimensional ultrasound dataset of the target scan plane with the ultrasound probe in a two-dimensional acquisition mode after applying the probe position adjustment (paragraphs [0109]-[0112], referring to obtaining and displaying image data, such as image data representing the IMT measurable range; paragraph [0146], referring to, after the swing of the array (9) of the transducers is stopped, the same region of the carotid artery is irradiated with a beam in that state and the image representing that region is displayed on the monitor (4) as in ST4; Figures 5, 8-10, 14, note that the displayed images are 2D images); generating a two-dimensional image based on the two-dimensional ultrasound dataset (paragraphs [0109]-[0112], referring to obtaining and displaying image data, such as image data representing the IMT measurable range; paragraph [0146], referring to, after the swing of the array (9) of the transducers is stopped, the same region of the carotid artery is irradiated with a beam in that state and the image representing that region is displayed on the monitor (4) as in ST4; Figures 5, 8-10, 14); and displaying the two-dimensional image on the display device (paragraphs [0109]-[0112], referring to obtaining and displaying image data, such as image data representing the IMT measurable range; paragraph [0146], referring to, after the swing of the array (9) of the transducers is stopped, the same region of the carotid artery is irradiated with a beam in that state and the image representing that region is displayed on the monitor (4) as in ST4; Figures 5, 8-10, 14, note that the displayed images are 2D images).
With regards to claims 3 and 13, Urabe et al. disclose that their method further comprises calculating a measurement (i.e. IMT measurement) of the structure-of-interest along the axis based on the representation of the axis in the two-dimensional image; and displaying the measurement on the display device (paragraphs [0109]-[0112], referring to calculating/measuring the IMT value based on the image data; paragraphs [0146]-[0147], referring to measuring and displaying the IMT values; Figure 5, steps ST5-ST8).
With regards to claim 4, Murashita et al. disclose that determining a center of gravity of the object comprises determining a center point of the object that represents the balance point for the object (paragraphs [0027]-[0028], wherein the axis/centerline is determined by determining a “center of gravity” of the object, wherein the definition of “center of gravity” is “the point at which the entire weight of a body may be considered as concentrated so that if supported at this point the body would remain in equilibrium in any position” and thus, by definition, the center of gravity disclosed by Murashita et al. comprises a center point of the object that represents the balance/equilibrium point for the object).
With regards to claims 6 and 16, Murashita et al. disclose that the identifying the axis of the structure-of-interest comprises identifying a longest line (i.e. left ventricular long axis) passing through the center of gravity that connects two boundaries (i.e. end points of the left ventricle) of the structure-of-interest (paragraphs [0027]-[0031], referring to the voxel with the longest distance being detected as the long axis; Figure 3).
With regards to claim 15, Urabe et al. disclose that the processor is configured to present the probe position adjustment by displaying one or more arrows (“arrow 4H”) in relation to an ultrasound probe icon (4F) displayed on the display device (paragraphs [0097]-[0107]; Figures 9-10).
With regards to claim 19, Urabe et al. disclose the processor is further configured to: control the ultrasound probe to acquire an updated volumetric dataset after the probe position adjustment has been applied to the ultrasound probe (paragraphs [0087]-[0088], referring to generating the 3D image; paragraphs [0097]-[0107], Figure 5, in particular see the loop from Steps ST2->ST3->ST1, wherein in ST1 3D data is generated; generate at least one rendering based on the updated volumetric dataset (paragraphs [0097]-[0107], referring to generating and displaying the images); and display the at least one rendering on the display device (paragraphs [0097]-[0107], referring to displaying the images; Figures 5-10).
With regards to claim 20, Urabe et al. disclose that the at least one rendering comprises an A-plane of the target scan plane (paragraphs [0097]-[0107], Figures 6-11, wherein at least one of the displayed images is parallel to the acquisition plane and thus corresponds to an “A-plane” of the target scan plane).
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Urabe et al. in view of Murashita and Manai et al. (or Khaleel et al.), as applied to claim 1 above, and further in view of Rouet et al. (US Pub No. 2019/0015076).
With regards to claim 5, as discussed above, the above combined references meet the limitations of claim 1. Further, the above combined references disclose that the probe position adjustment to the ultrasound probe position comprises one or more of a pitch adjustment, a yaw adjustment, or a roll adjustment (paragraphs [0070]-[0073], referring to the positioning mode including a swing angle movement of the array (9) of the transducers, which would include one or more of a rotational adjustment (i.e. a pitch, yaw or roll adjustment); Figures 2-5, in Figure 5, see steps ST1-ST3).
However, the above combined references do not specifically disclose that the probe position adjustment further comprises a translation adjustment.
Rouet et al. disclose an ultrasound imaging apparatus for inspecting a volume of a subject, wherein the ultrasound probe includes a plurality of ultrasound transducer elements for acquiring three-dimensional ultrasound data in a field of view (Abstract; paragraphs [0042], [0048]). A precise alignment of the ultrasound probe (14) with respect to the anatomical feature and at least one of the image planes is necessary for measuring the anatomical feature and to provide high quality image data so that high quality measurements of the anatomical feature can be achieved (paragraphs [0047]-[0048]; Figures 1-4). An alignment unit (28) is arranged to indicate an improved alignment of the image planes with respect to the anatomical feature, wherein an indication (46) is shown in the ultrasound image which indicates a rotation and/or translation of the position of the ultrasound probe (14) to align the anatomical feature (30) with respect to the field of view (paragraph [0062], Figures 1 and 4).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have the probe position adjustment of the above combined references further comprise a translation adjustment, as taught by Rouet et al., in order to provide precise alignment of the ultrasound probe with respect to the anatomical feature and thus provide high quality image data so that high quality measurements of the anatomical feature can be achieved (paragraphs [0047]-[0048]).
Claim(s) 7 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Urabe et al. in view of Murashita and Manai et al. (or Khaleel et al.), as applied to claims 1 and 11 above, and further in view of Sasahara et al. (JP 2008-253379). Note that, with regards to Sasahara et al., the Examiner refers to the English translation of Sasahara et al..
With regards to claims 7 and 17, as discussed above, the above combined references meet the limitations of claims 1 and 11. However, they do not specifically disclose that identifying the axis of the structure-of-interest comprises identifying a shortest line passing through the center of gravity that connects two boundaries of the structure of interest.
Sasahara et al. disclose ultrasonic diagnostic equipment which can automatically measure the blood vessel diameter irrespective of types of a short axis/long axis when measuring the diameter of the blood vessel (Abstract). Sasahara et al. disclose that their equipment includes a distance calculating means for calculating a plurality of distances from the center of gravity position to the extracted contour at different angles, and a dispersion value determination means for calculating a dispersion value of the calculated distance and performing a determination based on the dispersion value whether the image is a short axis image or a long axis image (pg. 5). Further, a diameter of a long axis image can be obtained based on the shortest distance/line between the contours of the long axis image, wherein the distance is calculated between the contours located on the opposite side of the center of gravity of the extracted contour by 180 degrees (pg. 8, wherein the contours located on opposite side of the center of gravity corresponds to two boundaries of the structure of interest; Figure 21).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have the identifying of the axis of the structure-of-interest of the above combined reference comprise identifying a shortest line passing through the center of gravity that connects two boundaries of the structure of interest, as taught by Sasahara et al., in order to be able to determine a diameter of a long axis image, which can provide diagnosis benefits and/or in order to be able to distinguish from a short-axis image or a long-axis image (pgs. 5, 8).
Claim(s) 8-9 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Urabe et al. in view of Murashita and Manai et al. (or Khaleel et al.), as applied to claims 1 and 11 above, and further in view of Perrey et al. (US Pub No. 2018/0125460).
With regards to claims 6, 8-9, 16 and 18, as discussed above, the above combined references meet the limitations of claims 1 and 11. However, they do not specifically disclose that automatically identifying the axis comprises implementing an artificial intelligence technique with the processor.
Perrey et al. discloses an ultrasound system wherein the symmetry of a shape of the anatomical structure (502) may be determined by executing a machine learning algorithm stored in the memory (Abstract; paragraph [0045]). For example, the machine learning algorithm may represent a model based on decision tree learning, neural network, etc., wherein the model may be configured to determine a symmetrical axis (510) based on the overall shape of the anatomical structure (502) (paragraph [0045], note that, as depicted in Figure 5, the symmetrical axis (510) corresponds to a center line of the structure (502), and thus an artificial intelligence technique (i.e. decision tree learning, neural network, etc.) is used to identify a central line axis). Further, a variety of techniques, such as applying as edge detection, threshold, border detection methods, pattern recognition technique, a machine learning algorithm, etc., may be used to detect and identify the anatomical structure (502) (paragraphs [0046]-[0047], note that an object (502) is automatically identified by implementing an artificial intelligence technique (i.e. machine learning algorithm, pattern recognition technique, etc.); Figure 5).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to substitute the technique for automatically identifying the object from the volumetric dataset by implementing an artificial intelligence technique with the processor and substitute the technique for identifying the axis by implementing an artificial intelligence technique with the processor, as taught by Perrey et al., as the substitution of one known technique for automatically identifying the object for another and the substitution of one known technique for automatically identifying the axis for another yields predictable results (i.e. effective identification of the object and effective identification of the axis/centerline) to one of ordinary skill in the art. One of ordinary skill in the art would have been able to carry out such a substitution and the results are reasonably predictable.
Note that by performing the above substitutions, said automatically identifying the object from the volumetric dataset of Urabe et al. comprises implementing a first artificial intelligence technique with the processor and said automatically identifying the axis of Urabe et al. comprises implementing a second artificial intelligence technique with the processor [claim 9].
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Urabe et al. in view of Murashita and Manai et al. (or Khaleel et al.) and Perrey et al. as applied to claim 9 above, and further in view of Al-Noor et al. (US Pub No. 2021/0128099).
With regards to claim 10, as discussed above, the above combined references meet the limitations of claim 9.
However, though Perrey et al. do disclose that the artificial intelligence technique (i.e. first artificial intelligence technique) for automatically identifying the object is a machine learning algorithm and that the second artificial intelligence technique is a neural network (paragraphs [0045], [0047]), the above combined references do not specifically disclose that the artificial intelligence technique (i.e. first artificial intelligence technique) for automatically identifying the object is specifically a neural network or a U-Net network and that the second artificial intelligence technique is specifically a convolutional neural network.
Al-Noor et al. disclose using learned approaches, including machine learning and/or deep learning, to perform automated vessel segmentation on ultrasound images, wherein Deep learning is a subfield of machine learning based on algorithms inspired by the human brain and using software-implemented neural networks (paragraphs [0064]-[0066], [0067], [0069]). The algorithms may include convolutional neural networks, U-Nets with skip connections, etc. (paragraphs [0067], [0069]).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to substitute the artificial intelligence technique (i.e. first artificial intelligence technique) for automatically identifying the object with an artificial intelligence technique comprising a neural network or a U-Net network and substitute the second artificial intelligence technique with a convolutional neural network, as taught by Al-Noor et al., as the substitution of one known artificial intelligence technique for another yields predictable results (i.e. effective identification of a desired target (i.e. object and/or the axis/centerline)) to one of ordinary skill in the art. One of ordinary skill in the art would have been able to carry out such a substitution and the results are reasonably predictable.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Murashita has been introduced to teach determining a “single” point representing center of gravity, etc..
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/KATHERINE L FERNANDEZ/Primary Examiner, Art Unit 3798