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 Objections
Claims 2-5, 11-14, and 19-22 are objected to because of the following informalities:
With respect to claim 2, the phrase “for each pixel” should be positioned immediately after “value” for clarity. As such claim 2 should read “wherein the determined opacity value, for each pixel, is a function of the selected time-based parameter.”
With respect to claim 3, the phrase “for each pixel” should be positioned immediately after “value” for clarity. As such claim 3 should read “wherein the determined opacity value, for each pixel, is a function of an intensity of the contrast agent.”
With respect to claim 4, the phrase “for each pixel” should be positioned immediately after “value” for clarity. As such claim 4 should read “wherein the determined opacity value, for each pixel, is a function of the selected time-based parameter and an intensity of the contrast agent.”
With respect to claim 5, the phrase “for each pixel” at the end of the list is not necessary and can be confusing. Please remove.
With respect to claim 11, the phrase “for each pixel” should be positioned immediately after “value” for clarity. As such claim 11 should read “wherein the determined opacity value, for each pixel, is a function of the selected time-based parameter.”
With respect to claim 12, there appears to be a typographical error/redundant use of “opacity value is” and the phrase “for each pixel” should be positioned immediately after “value” for clarity. As such claim 12 should read “wherein the determined opacity value, for each pixel, is a function of an intensity of the contrast agent.”
With respect to claim 13, the phrase “for each pixel” should be positioned immediately after “value” for clarity. As such claim 13 should read “wherein the determined opacity value, for each pixel, is a function of the selected time-based parameter and an intensity of the contrast agent.”
With respect to claim 14, the phrase “for each pixel” at the end of the list is not necessary and can be confusing. Please remove.
With respect to claim 19, the phrase “for each pixel” should be positioned immediately after “value” for clarity. As such claim 19 should read “wherein the determining the opacity value, for each pixel, further comprises determining the opacity value as a function of the selected time-based parameter.”
With respect to claim 20, the phrase “for each pixel” should be positioned immediately after “value” for clarity. As such claim 20 should read “wherein the determining the opacity value, for each pixel, further comprises determining the opacity value as a function of an intensity of the contrast agent.”
With respect to claim 21, the phrase “for each pixel” should be positioned immediately after “value” for clarity. As such claim 21 should read “wherein the determining the opacity value, for each pixel, further comprises determining the opacity value as a function of the selected time-based parameter and an intensity of the contrast agent.”
With respect to claim 22, the phrase “for each pixel” at the end of the list is not necessary and can be confusing. Please remove.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-22 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 has the following issues that render the claim indefinite:
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(1) The claim limitations following “a tangible, non-transitory computer-readable medium…” are provided in a single paragraph (see below) such that “a display” appears to be an element of the computer readable medium. A computer-readable medium (e.g., memory) cannot include a display nor can the instructions include a display.
(2) The claim limitation “a color value of a contrast agent” is not clear as it suggests the contrast agent has a color. However, as described in Applicant’s specification, a color value is assigned to a pixel based on ultrasound data of the contrast agent. (see, e.g., [0053] of Applicant’s specification.)
(3) The claim limitation “display the color value and the opacity value” is not clear as it recites displaying values (e.g., displaying numbers). However, as described in Applicant’s specification, an image is displayed in which the pixels of the image have the determined color values and the determined opacity values. (see, e.g., Applicant’s specification at [0056]: “Accordingly, for each pixel of the displayed image, 212 and 221 provide a color coded value based on TOA and an opacity value as a function of TOA or contrast intensity, or both.”).
Accordingly, for the purpose of a compact prosecution, Examiner is interpreting claim 1 as shown below:
1. A system for providing ultrasound images, comprising:
a source of ultrasound signal data from a contrast-enhanced ultrasound (CEUS) examination;
a processor;
a tangible, non-transitory computer-readable medium that stores instructions, which when executed by the processor cause the processor to:
determine, for each pixel of an ultrasound image, a color value representing a contrast agent, the color value being a function of a selected time-based parameter; and
determine, for each pixel of the ultrasound image, an opacity value representing the contrast agent; and
a display in communication with the processor and configured to display the ultrasound image in which each pixel has the determined color value and the determined opacity value.
Claim 10 has issues that are similar to (2) and (3) as discussed above with respect to claim 1. For the purpose of a compact prosecution, Examiner is interpreting claim 10 as follows:
10. A tangible, non-transitory computer-readable medium that stores instructions, which when executed by a process cause the processor to:
determine, for each pixel of an ultrasound image, a color value representing a contrast agent, the color value being a function of a selected time-based parameter;
determine, for each pixel of the ultrasound image, an opacity value representing the contrast agent; and
display the ultrasound image in which each pixel has the determined color value and the determined opacity value.
Claim 18 has issues that are similar to (2) and (3) as discussed above with respect to claim 1. For the purpose of a compact prosecution, Examiner is interpreting claim 18 as follows:
18. A method of providing ultrasound images, the method comprising:
determining, for each pixel of an ultrasound image, a color value representing a contrast agent, the color value being a function of a selected time-based parameter;
determining, for each pixel of the ultrasound image, an opacity value representing the contrast agent; and
displaying the ultrasound image in which each pixel has the determined color value[[,]] and the determined opacity value.
Each of the dependent claims 2-9, 11-17, and 19-22 either depends directly or indirectly from claim 1, claim 10, or claim 18. As such, claims 2-9, 11-17, and 19-22 are indefinite based on their dependencies.
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 1-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Each of independent claims 1, 10, and 18 recite or similarly recite:
determining a color value of a contrast agent as a function of a selected time-based parameter for each pixel;
determining an opacity value of the contrast agent for each pixel.
These claim limitations, as drafted and under their broadest reasonable interpretation, recite a mathematical concept. (MPEP 2106.04(a)(2)(I) (see, e.g., Digitech Image Techs., LLC v. Electronics for Imaging, Inc., 758 F.3d 1344, 1350, 111 USPQ2d 1717, 1721 (Fed. Cir. 2014) (although the claims did not recite a particular mathematical formula, the court held “[w]ithout additional limitations, a process that employs mathematical algorithms to manipulate existing information to generate additional information is not patent eligible.”)). These claim limitations are a mathematical concept because they require an algorithm or mathematical function to determine the corresponding value. For example, Applicant’s specification describes using algorithms or functions to determine the color values and the opacity values. (see, e.g., [0059] and [0060]). Figures 3A and 3B show the function (or relationship) between the color and opacity values and time-based parameters.
The next question is to consider whether the claims integrate the judicial exception into a practical application. A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception. (MPEP 2106.04(d)).
In this case, the additional elements/steps do not integrate the judicial exception into a practical application. The additional elements/steps are each addressed here:
The source of ultrasound signal data from a CEUS examination (as recited in claim 1) is insignificant pre-solution activity because ultrasound data is required by the judicial exception. (MPEP 2106.04(d)(I), which also refers to MPEP 2106.05(g).
The opacity values being a function of the selected time-based parameter (claims 2, 4, 11, 13, 19, and 21) or the intensity of the contrast agent (claims 3, 4, 12, 13, 20, and 21) recites a mathematical concept (i.e., abstract idea). Moreover, these limitations do not meaningfully limit the claims as they are recited at a high-level of generality. (MPEP 2106.04(d)(1)).
The selected time-based parameter being one of many parameters associated with CEUS data (as recited claims 5, 14, and 22) merely links the use of a judicial exception to a particular technological environment or field of use. (e.g., contrast-enhanced US). (MPEP 2106.04(d)(I)).
The opacity values being a function of the CEUS intensity recites another mathematical concept. (MPEP 2106.04(a)(2)(I)).
The CEUS data being pre-processed (as recited claims 7, 8, 15, and 16) is insignificant pre-solution activity. (MPEP 2106.04(d)(I), which also refers to MPEP 2106.05(g).
The CEUS data comprises the contrast intensity for each pixel (as recited in claims 5, 9, and 17) merely links the use of a judicial exception to a particular technological environment or field of use. (e.g., contrast-enhanced US). (MPEP 2106.04(d)(I)).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. A shared quality of the additional elements and/or steps is that they do not recite any meaningful limitation that transforms the judicial exception into a patent-eligible application. (MPEP 2106.05(II)). The additional element/steps either recite insignificant extra-solution activity that do not impose meaningfully limits or are themselves a mathematical concept.
Accordingly, the claims do not recite patent-eligible subject matter.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-6, 10-14, and 18-22 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by U.S. Patent Appl. Publ. No. 2009/0016587 A1 (hereinafter “STROBEL”).
With respect to claim 1 (and in light of the Section 112(b) rejection), STROBEL discloses “[a] method for visualizing temporal phenomena and constructing 3D views from a series of medical images includes providing a first time series of digital images of contrast-enhanced blood flow in a patient….” (Abstract).
A system for providing ultrasound images - Figure 3 of STROBEL illustrates an “exemplary computer system” ([0027]) with a signal source. STROBEL also discloses that the medical images may be ultrasound images. “The image may be, for example, a medical image of a subject collected by computer tomography, magnetic resonance imaging, ultrasound, or any other medical imaging system known to one of skill in the art.” ([0029]; see also [0006] describing “Doppler Sonography”)), comprising:
a source of ultrasound signal data from a contrast-enhanced ultrasound (CEUS) examination; - As disclosed in STROBEL (see, e.g., Abstract and [0006], [0029]), the image data can be ultrasound image data of contrast-enhanced blood flow in a patient. Moreover, “[t]he present invention can be implemented as a routine 37 that is stored in memory 33 and executed by the CPU 32 to process the signal from the signal source 38.” ([0067]). Accordingly, the signal source can be a source of ultrasound signal data from a contrast-enhanced ultrasound examination.
a processor; - See, e.g., “a central processing unit (CPU) 32” at [0067]. and
a tangible, non-transitory computer-readable medium that stores instructions, which when executed by the processor cause the processor to: - See, e.g., “present invention can be implemented as a routine 37 that is stored in memory 33 and executed by the CPU 32” at [0067].
determine a color value of a contrast agent as a function of a selected time-based parameter for each pixel. - STROBEL discloses that “if a contrast agent has been injected into some vascular structure, the temporal behavior of the contrast agent at each pixel or voxel, that is, the bolus arrival times, inside a certain field of view can be recorded using time-density curves. Time-density curves show how the intensity at each pixel location changes over time.” ([0030]). Assigning a color to the pixel based on the contrast agent distinguishes the anatomical structure. “The use of enhanced color coding techniques can eliminate the need to explicitly segment blood vessels.” ([0031]). STROBEL uses the time-density curves and “color coding techniques” to determine a color value at each pixel that represents the contrast agent. “Thus, from a sequence of registered images or volumes, one can generate overview images summarizing how physical properties change at each location, over time, using advanced color coding techniques.” ([0030]). Paragraphs [0031] and [0032] describe the color coding techniques in greater detail. NOTE: Under the broadest reasonable interpretation of “selected,” the claims do not require an active step or operation in which a user or the system selects the time-based parameter. (MPEP 2111). As such, Examiner is interpreting “selected” to include “predetermined.” Nonetheless, STROBEL also discloses the active step of selecting the time-based parameter: “After selecting relevant bolus arrival time definitions most appropriate for the clinical application at hand, color (or even grayscale) composite overview images are generated as displayed in FIGS. 1( a)-(c).” ([0051]).
determine an opacity value of the contrast agent for each pixel; - “According to another embodiment of the invention, an alpha channel, such as the opacity used for image compositing, can be used to help visualize and overlay the image onto other images and volumes. The alpha channel can also be used as a tool to visualize any parameter or just be set to have a linear correlation with Value.” ([0033]). Notably, the “Value” is a parameter of the color-coding technique that is applied to each pixel. “The Value parameter can used to represent the absolute or relative density change for the pixel.” ([0032]). Accordingly, STROBEL discloses determining an opacity value for each pixel.
a display (“display 35” at [0067]) in communication with the processor and configured to display the color value and the opacity value for each pixel - See, e.g., [0032]: “[I]t will be apparent to those skilled in the art how to use other color space coordinates to generate overview images summarizing how physical properties change at pixel locations over time”; [0051]: “…composite overview images are generated as displayed in FIGS. 1( a)-(c)”; and [0065]: “…a 3D image is constructed.”
With respect to claim 2, STROBEL discloses that the determined opacity value is a function of the selected time-based parameter for each pixel. “According to another embodiment of the invention, an alpha channel, such as the opacity used for image compositing, can be used to help visualize and overlay the image onto other images and volumes. The alpha channel can also be used as a tool to visualize any parameter…” ([0033]). STROBEL lists several parameters that can be derived from a “time-density curve.” ([0034]). The list is provided at [0035]-[0049] and includes Time-of-peak opacification, Time-of-leading half-peak opacification, Time-of-trailing half-peak opacification, Time-of-a-single-opacification level, Downslope time differences, Time-of-peak-gradient arrival, Time-of-peak-negative-gradient arrival, Time-of-threshold density, Integral-corrected time (mean concentration time), Mean bolus arrival time, Time-of-level-of area under curve, Leading edge detection, Time-of-contrast arrival, and Isodensity level transit time.
With respect to claim 3, STROBEL discloses that the determined opacity value is a function of an intensity of the contrast agent for each pixel. “According to another embodiment of the invention, an alpha channel, such as the opacity used for image compositing, can be used to help visualize and overlay the image onto other images and volumes. The alpha channel can also be used as a tool to visualize any parameter or just be set to have a linear correlation with Value.” ([0033]). Note that the “Value parameter” in STROBEL can “represent the absolute or relative density change for the pixel. For example, selecting Value to represent the peak density value would emphasis the blood vessels. According to an embodiment of the invention, Value can be a non-linear function of peak density to emphasize blood vessels that are distant from the source of the contrast agent. According to other embodiments of the invention, a color table can be selected as well to map a parameter onto a customized range of colors.” ([0032]).
With respect to claim 4, as discussed immediately above for claims 2 and 3, STROBEL discloses the determined opacity value is a function of the selected time-based parameter and an intensity of the contrast agent for each pixel. “According to another embodiment of the invention, an alpha channel, such as the opacity used for image compositing, can be used to help visualize and overlay the image onto other images and volumes. The alpha channel can also be used as a tool to visualize any parameter or just be set to have a linear correlation with Value.” ([0033]). Note that the “Value parameter” in STROBEL can “represent the absolute or relative density change for the pixel. For example, selecting Value to represent the peak density value would emphasis the blood vessels. According to an embodiment of the invention, Value can be a non-linear function of peak density to emphasize blood vessels that are distant from the source of the contrast agent. According to other embodiments of the invention, a color table can be selected as well to map a parameter onto a customized range of colors.” ([0032]).
STROBEL lists several parameters that can be derived from a “time-density curve.” ([0034]). The list is provided at [0035]-[0049] and includes Time-of-peak opacification, Time-of-leading half-peak opacification, Time-of-trailing half-peak opacification, Time-of-a-single-opacification level, Downslope time differences, Time-of-peak-gradient arrival, Time-of-peak-negative-gradient arrival, Time-of-threshold density, Integral-corrected time (mean concentration time), Mean bolus arrival time, Time-of-level-of area under curve, Leading edge detection, Time-of-contrast arrival, and Isodensity level transit time.
With respect to claim 5, STROBEL discloses that the selected time-based parameter is one of a time of arrival (TOA) of the contrast agent, a time to peak of the contrast agent, a wash-in rate of the contrast agent, a rise time of the contrast agent, a peak intensity of the contrast agent, a wash- out rate of the contrast agent, a mean transit time of the contrast agent, a fall time of the contrast agent, and an area under a curve of the contrast agent for each pixel. STROBEL lists several time-based parameters that can be derived from a “time-density curve.” ([0034]). The list is provided at [0035]-[0049] and includes Time-of-peak opacification, Time-of-leading half-peak opacification, Time-of-trailing half-peak opacification, Time-of-a-single-opacification level, Downslope time differences, Time-of-peak-gradient arrival, Time-of-peak-negative-gradient arrival, Time-of-threshold density, Integral-corrected time (mean concentration time), Mean bolus arrival time, Time-of-level-of area under curve, Leading edge detection, Time-of-contrast arrival, and Isodensity level transit time.
With respect to claim 6, STROBEL discloses that the opacity values are a function of the CEUS intensity, or temporal statistics of the CEUS intensity. As discussed above with respect to claims 2-5, STROBEL discloses that an alpha channel (i.e., opacity) can be used to “visualize any parameter.” ([0033]). These parameters are derived from a “time-density curve” ([0034]) and the time-density curve shows “intensity at each pixel location changes over time.” ([0030]). Thus, in the context of contrast-enhanced ultrasound examinations, the values would necessarily be a function of the CEUS intensity.
With respect to claim 10, as discussed above with respect to claim 1, STROBEL discloses:
a tangible, non-transitory computer-readable medium that stores instructions, which when executed by a processor cause the processor to: (see, e.g., “present invention can be implemented as a routine 37 that is stored in memory 33 and executed by the CPU 32” at [0067]):
determine a color value of a contrast agent as a function of a selected time-based parameter for each pixel. STROBEL teaches that “if a contrast agent has been injected into some vascular structure, the temporal behavior of the contrast agent at each pixel or voxel, that is, the bolus arrival times, inside a certain field of view can be recorded using time-density curves. Time-density curves show how the intensity at each pixel location changes over time.” ([0030]). STROBEL uses “color coding techniques” to determine a color value at each pixel that represents the contrast agent. “Thus, from a sequence of registered images or volumes, one can generate overview images summarizing how physical properties change at each location, over time, using advanced color coding techniques.” ([0030]). Paragraphs [0031] and [0032] describe the color coding techniques in greater detail. NOTE: Under the broadest reasonable interpretation of “selected,” the claims do not require an active step or operation in which a user or the system selects the time-based parameter. As such, Examiner is interpreting “selected” to include “predetermined.” Nonetheless, STROBEL does disclose the active step of selecting the time-based parameter: “After selecting relevant bolus arrival time definitions most appropriate for the clinical application at hand, color (or even grayscale) composite overview images are generated as displayed in FIGS. 1( a)-(c).” ([0051]).
determine an opacity value of the contrast agent for each pixel. “According to another embodiment of the invention, an alpha channel, such as the opacity used for image compositing, can be used to help visualize and overlay the image onto other images and volumes.” ([0033]).
display the color and opacity value for each pixel (see “display 35” at [0067] and [0051]: “composite overview images are generated as displayed in FIGS. 1( a)-(c)”; see also [0065]: “a 3D image is constructed”).
With respect to claim 11, as discussed above regarding claim 2, STROBEL discloses that the determined opacity value is a function of the selected time-based parameter for each pixel. “According to another embodiment of the invention, an alpha channel, such as the opacity used for image compositing, can be used to help visualize and overlay the image onto other images and volumes. The alpha channel can also be used as a tool to visualize any parameter…” ([0033]). STROBEL lists several parameters that can be derived from a “time-density curve.” ([0034]). The list is provided at [0035]-[0049] and includes Time-of-peak opacification, Time-of-leading half-peak opacification, Time-of-trailing half-peak opacification, Time-of-a-single-opacification level, Downslope time differences, Time-of-peak-gradient arrival, Time-of-peak-negative-gradient arrival, Time-of-threshold density, Integral-corrected time (mean concentration time), Mean bolus arrival time, Time-of-level-of area under curve, Leading edge detection, Time-of-contrast arrival, and Isodensity level transit time.
With respect to claim 12, as discussed above regarding claim 3, STROBEL discloses that the determined opacity value is a function of an intensity of the contrast agent for each pixel. “According to another embodiment of the invention, an alpha channel, such as the opacity used for image compositing, can be used to help visualize and overlay the image onto other images and volumes. The alpha channel can also be used as a tool to visualize any parameter or just be set to have a linear correlation with Value.” ([0033]). Note that the “Value parameter” in STROBEL can “represent the absolute or relative density change for the pixel. For example, selecting Value to represent the peak density value would emphasis the blood vessels. According to an embodiment of the invention, Value can be a non-linear function of peak density to emphasize blood vessels that are distant from the source of the contrast agent. According to other embodiments of the invention, a color table can be selected as well to map a parameter onto a customized range of colors.” ([0032]).
With respect to claim 13, as discussed above regarding claim 4, STROBEL discloses the determined opacity value is a function of the selected time-based parameter and an intensity of the contrast agent for each pixel. “According to another embodiment of the invention, an alpha channel, such as the opacity used for image compositing, can be used to help visualize and overlay the image onto other images and volumes. The alpha channel can also be used as a tool to visualize any parameter or just be set to have a linear correlation with Value.” ([0033]). Note that the “Value parameter” in STROBEL can “represent the absolute or relative density change for the pixel. For example, selecting Value to represent the peak density value would emphasis the blood vessels. According to an embodiment of the invention, Value can be a non-linear function of peak density to emphasize blood vessels that are distant from the source of the contrast agent. According to other embodiments of the invention, a color table can be selected as well to map a parameter onto a customized range of colors.” ([0032]).
STROBEL lists several parameters that can be derived from a “time-density curve.” ([0034]). The list is provided at [0035]-[0049] and includes Time-of-peak opacification, Time-of-leading half-peak opacification, Time-of-trailing half-peak opacification, Time-of-a-single-opacification level, Downslope time differences, Time-of-peak-gradient arrival, Time-of-peak-negative-gradient arrival, Time-of-threshold density, Integral-corrected time (mean concentration time), Mean bolus arrival time, Time-of-level-of area under curve, Leading edge detection, Time-of-contrast arrival, and Isodensity level transit time.
With respect to claim 14, as discussed above regarding claim 5, STROBEL discloses that the selected time-based parameter is one of one of a TOA of the contrast agent, a time to peak of the contrast agent, a wash-in rate of the contrast agent, a rise time of the contrast agent, a peak intensity of the contrast agent, a wash-out rate of the contrast agent, a mean transit time of the contrast agent, a fall time of the contrast agent, and an area under a curve of the contrast agent for each pixel. STROBEL lists several time-based parameters that can be derived from a “time-density curve.” ([0034]). The list is provided at [0035]-[0049] and includes Time-of-peak opacification, Time-of-leading half-peak opacification, Time-of-trailing half-peak opacification, Time-of-a-single-opacification level, Downslope time differences, Time-of-peak-gradient arrival, Time-of-peak-negative-gradient arrival, Time-of-threshold density, Integral-corrected time (mean concentration time), Mean bolus arrival time, Time-of-level-of area under curve, Leading edge detection, Time-of-contrast arrival, and Isodensity level transit time.
With respect to claim 18, as discussed above with respect to claims 1 and 10, STROBEL discloses:
a method of providing ultrasound images: See, Title and [0029]: “The image may be, for example, a medical image of a subject collected by computer tomography, magnetic resonance imaging, ultrasound, or any other medical imaging system known to one of skill in the art.” ([0029]; see also [0006] describing “Doppler Sonography”)):
determining a color value of a contrast agent as a function of a selected time-based parameter for each pixel. STROBEL teaches that “if a contrast agent has been injected into some vascular structure, the temporal behavior of the contrast agent at each pixel or voxel, that is, the bolus arrival times, inside a certain field of view can be recorded using time-density curves. Time-density curves show how the intensity at each pixel location changes over time.” ([0030]). STROBEL uses “color coding techniques” to determine a color value at each pixel that represents the contrast agent. “Thus, from a sequence of registered images or volumes, one can generate overview images summarizing how physical properties change at each location, over time, using advanced color coding techniques.” ([0030]). Paragraphs [0031] and [0032] describe the color coding techniques in greater detail. NOTE: Under the broadest reasonable interpretation of “selected,” the claims do not require an active step or operation in which a user or the system selects the time-based parameter. As such, Examiner is interpreting “selected” to include “predetermined.” Nonetheless, STROBEL does disclose the active step of selecting the time-based parameter: “After selecting relevant bolus arrival time definitions most appropriate for the clinical application at hand, color (or even grayscale) composite overview images are generated as displayed in FIGS. 1( a)-(c).” ([0051]).
determining an opacity value of the contrast agent for each pixel. “According to another embodiment of the invention, an alpha channel, such as the opacity used for image compositing, can be used to help visualize and overlay the image onto other images and volumes.” ([0033]).
displaying the color value, and the opacity value for each pixel (see “display 35” at [0067] and [0051]: “composite overview images are generated as displayed in FIGS. 1( a)-(c)”; see also [0065]: “a 3D image is constructed”).
With respect to claim 19, STROBEL discloses that determining the opacity value further comprises determining the opacity value as a function of the selected time- based parameter for each pixel. “According to another embodiment of the invention, an alpha channel, such as the opacity used for image compositing, can be used to help visualize and overlay the image onto other images and volumes. The alpha channel can also be used as a tool to visualize any parameter…” ([0033]). STROBEL lists several parameters that can be derived from a “time-density curve.” ([0034]). The list is provided at [0035]-[0049] and includes Time-of-peak opacification, Time-of-leading half-peak opacification, Time-of-trailing half-peak opacification, Time-of-a-single-opacification level, Downslope time differences, Time-of-peak-gradient arrival, Time-of-peak-negative-gradient arrival, Time-of-threshold density, Integral-corrected time (mean concentration time), Mean bolus arrival time, Time-of-level-of area under curve, Leading edge detection, Time-of-contrast arrival, and Isodensity level transit time.
With respect to claim 20, STROBEL discloses that determining the opacity value further comprises determining the opacity value as a function of an intensity of the contrast agent for each pixel. “According to another embodiment of the invention, an alpha channel, such as the opacity used for image compositing, can be used to help visualize and overlay the image onto other images and volumes. The alpha channel can also be used as a tool to visualize any parameter or just be set to have a linear correlation with Value.” ([0033]). Note that the “Value parameter” in STROBEL can “represent the absolute or relative density change for the pixel. For example, selecting Value to represent the peak density value would emphasis the blood vessels. According to an embodiment of the invention, Value can be a non-linear function of peak density to emphasize blood vessels that are distant from the source of the contrast agent. According to other embodiments of the invention, a color table can be selected as well to map a parameter onto a customized range of colors.” ([0032]).
With respect to claim 21, STROBEL discloses that determining the opacity value further comprises determining the opacity value as a function of the selected time-based parameter and an intensity of the contrast agent for each pixel. “According to another embodiment of the invention, an alpha channel, such as the opacity used for image compositing, can be used to help visualize and overlay the image onto other images and volumes. The alpha channel can also be used as a tool to visualize any parameter or just be set to have a linear correlation with Value.” ([0033]). Note that the “Value parameter” in STROBEL can “represent the absolute or relative density change for the pixel. For example, selecting Value to represent the peak density value would emphasis the blood vessels. According to an embodiment of the invention, Value can be a non-linear function of peak density to emphasize blood vessels that are distant from the source of the contrast agent. According to other embodiments of the invention, a color table can be selected as well to map a parameter onto a customized range of colors.” ([0032]).
STROBEL lists several parameters that can be derived from a “time-density curve.” ([0034]). The list is provided at [0035]-[0049] and includes Time-of-peak opacification, Time-of-leading half-peak opacification, Time-of-trailing half-peak opacification, Time-of-a-single-opacification level, Downslope time differences, Time-of-peak-gradient arrival, Time-of-peak-negative-gradient arrival, Time-of-threshold density, Integral-corrected time (mean concentration time), Mean bolus arrival time, Time-of-level-of area under curve, Leading edge detection, Time-of-contrast arrival, and Isodensity level transit time.
With respect to claim 22, STROBEL discloses that the selected time-based parameter is one of a TOA of the contrast agent, a time to peak of the contrast agent, a wash-in rate of the contrast agent, a peak intensity of the contrast agent, and an area under a curve of the contrast agent for each pixel. STROBEL lists several time-based parameters that can be derived from a “time-density curve.” ([0034]). The list is provided at [0035]-[0049] and includes Time-of-peak opacification, Time-of-leading half-peak opacification, Time-of-trailing half-peak opacification, Time-of-a-single-opacification level, Downslope time differences, Time-of-peak-gradient arrival, Time-of-peak-negative-gradient arrival, Time-of-threshold density, Integral-corrected time (mean concentration time), Mean bolus arrival time, Time-of-level-of area under curve, Leading edge detection, Time-of-contrast arrival, and Isodensity level transit time.
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.
Claims 7-9 and 15-17 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Appl. Publ. No. 2009/0016587 A1 (hereinafter “STROBEL”) and U.S. Patent Appl. Publ. No. 2022/0292637 A1 (hereinafter “HUANG”).
Each of claims 7-9 depend directly or indirectly from claim 1, and each of claims 15-17 depend directly or indirectly from claim 10. Claims 1 and 10 are each taught by STROBEL as discussed above in the Section 102 rejection.
With respect to claim 7, STROBEL does not explicitly teach that the instructions further cause the processor initially to pre-process an input of contrast-enhanced ultrasound (CEUS) data for each pixel.
In the same field of endeavor, HUANG teaches systems and methods for high spatial and temporal resolution ultrasound imaging of microvessels using contrast agents. (Abstract). “By imaging microbubbles (MB), a cross-correlation map between each MB image and a point spread function (PSF) of the system can be generated.” ([0043]). Embodiments may use “the Nth power of the MB signal and PSF to improve the resolution of the cross-correlation maps, which may not use the center position of microbubbles.” ([0063]). After obtaining the MB signal, HUANG teaches that the “MB signal may be separated from the tissue signal via an MB signal detection by processing the ultrasound data at step 320, such as by using a tissue clutter filtering technique, and the like. Pre-processing may be used to improve the signal-to-noise ratio (SNR) and prepare the data for high-resolution imaging at step 330.” ([0063]). HUANG further teaches that this step “may include denoising, enhancement, equalization, and the like, of the MB signals.” ([0067]). Notably, this operation can be applied per pixel. “[D]enoising can be implemented using an intensity-based thresholding method. Such methods are more accurate when it can be assumed that the microbubble signals are stronger than the background noise signals. For example, by suppressing pixels with intensity values less than a selected value (e.g., −30 dB to the maximum intensity value in the current field-of-view), a significant amount of background noise can be suppressed.” ([0058]). Other methods of denoising are described. (see, e.g., [0059]-[0060]).
It would have been obvious to one having ordinary skill in the art at the time of filing to modify the STROBEL system to include initially pre-processing an input of contrast-enhanced ultrasound (CEUS) data for each pixel. One of ordinary skill in the art would have been motivated to denoise the signal data, as taught in HUANG, by applying an intensity-based threshold per pixel (or other denoising technique) noise can be removed from the signal data, thereby leading to more accurate “microvessel delineation and velocity estimation.” ([0057]). There would have been a reasonable expectation of success as HUANG teaches that such denoising techniques can be applied to CEUS data.
With respect to claim 8 (depending from claim 7), STROBEL does not explicitly teach that the pre-process comprises one or more of: normalizing CEUS data, reducing background noise to increase a contrast-to-noise ratio (CNR); and rejecting clutter.
HUANG teaches that the “MB signal may be separated from the tissue signal via an MB signal detection by processing the ultrasound data at step 320, such as by using a tissue clutter filtering technique, and the like. Pre-processing may be used to improve the signal-to-noise ratio (SNR) and prepare the data for high-resolution imaging at step 330.” ([0063]). HUANG further teaches that this step “may include denoising, enhancement, equalization, and the like, of the MB signals.” ([0067]). Notably, this operation can be applied per pixel. “[D]enoising can be implemented using an intensity-based thresholding method. Such methods are more accurate when it can be assumed that the microbubble signals are stronger than the background noise signals. For example, by suppressing pixels with intensity values less than a selected value (e.g., −30 dB to the maximum intensity value in the current field-of-view), a significant amount of background noise can be suppressed.” ([0058]). Other methods of denoising are described. (see, e.g., [0059]-[0060]).
It would have been obvious to one having ordinary skill in the art at the time of filing to modify the STROBEL system to include reducing background noise to increase a contrast-to-noise ratio (CNR). One of ordinary skill in the art would have been motivated to suppress the background noise, thereby leading to more accurate “microvessel delineation and velocity estimation.” ([0057]). There would have been a reasonable expectation of success as HUANG teaches that such denoising techniques can be applied to CEUS data.
With respect to claim 9 (depending from claim 8), STROBEL does not explicitly teach that the CEUS data comprises the contrast intensity for each pixel. However, STROBEL teaches that embodiments may be directed to ultrasound data and that, for particular embodiments related to X-ray imaging, the relevant data is the time-density curve, which is equivalent to the time-intensity curve in CEUS. (see, e.g., [0030] of STROBEL: “Time-density curves show how the intensity at each pixel location changes over time.”)
Nonetheless, HUANG teaches that the signal data that is pre-processed includes intensity values from CEUS data. “Conventional ultrasound imaging and CEUS imaging generally displays the image as signal intensities. In accordance with the present disclosure, high spatial and temporal resolution ultrasound imaging techniques may utilize correlation maps to generate images with substantially improved spatial resolution and CNR.” ([0043]). As discussed above, at least one denoising technique includes applying an intensity-based thresholding per pixel. “[D]enoising can be implemented using an intensity-based thresholding method…For example, by suppressing pixels with intensity values less than a selected value (e.g., −30 dB to the maximum intensity value in the current field-of-view), a significant amount of background noise can be suppressed.” ([0058]).
It would have been obvious to one having ordinary skill in the art at the time of filing to modify the STROBEL system to pre-process CEUS data comprising contrast intensity for each pixel. One of ordinary skill in the art would have been motivated to denoise the signal data, as taught in HUANG, to suppress the background noise, thereby leading to more accurate “microvessel delineation and velocity estimation.” ([0057]). There would have been a reasonable expectation of success as HUANG teaches that such denoising techniques can be applied to CEUS data.
With respect to claim 15 (depending from Claim 10), STROBEL does not explicitly teach that the instructions further cause the processor initially to pre-process an input of contrast-enhanced ultrasound (CEUS) data for each pixel.
As discussed above for claim 7, HUANG teaches systems and methods for high spatial and temporal resolution ultrasound imaging of microvessels using contrast agents. (Abstract). “By imaging microbubbles (MB), a cross-correlation map between each MB image and a point spread function (PSF) of the system can be generated.” ([0043]). Embodiments may use “the Nth power of the MB signal and PSF to improve the resolution of the cross-correlation maps, which may not use the center position of microbubbles.” ([0063]). After obtaining the MB signal, HUANG teaches that the “MB signal may be separated from the tissue signal via an MB signal detection by processing the ultrasound data at step 320, such as by using a tissue clutter filtering technique, and the like. Pre-processing may be used to improve the signal-to-noise ratio (SNR) and prepare the data for high-resolution imaging at step 330.” ([0063]). HUANG further teaches that this step “may include denoising, enhancement, equalization, and the like, of the MB signals.” ([0067]). Notably, this operation can be applied per pixel. “[D]enoising can be implemented using an intensity-based thresholding method. Such methods are more accurate when it can be assumed that the microbubble signals are stronger than the background noise signals. For example, by suppressing pixels with intensity values less than a selected value (e.g., −30 dB to the maximum intensity value in the current field-of-view), a significant amount of background noise can be suppressed.” ([0058]). Other methods of denoising are described. (see, e.g., [0059]-[0060]).
It would have been obvious to one having ordinary skill in the art at the time of filing to modify the STROBEL system to include initially pre-processing an input of contrast-enhanced ultrasound (CEUS) data for each pixel. One of ordinary skill in the art would have been motivated to denoise the signal data, as taught in HUANG, by applying an intensity-based threshold per pixel (or other denoising technique) noise can be removed from the signal data, thereby leading to more accurate “microvessel delineation and velocity estimation.” ([0057]). There would have been a reasonable expectation of success as HUANG teaches that such denoising techniques can be applied to CEUS data.
With respect to claim 16 (depending from claim 15), STROBEL does not explicitly teach that the pre-process comprises one or more of: normalizing CEUS data, reducing background noise to increase a contrast-to-noise ratio (CNR); and rejecting clutter.
As discussed above for claim 8, HUANG teaches that the “MB signal may be separated from the tissue signal via an MB signal detection by processing the ultrasound data at step 320, such as by using a tissue clutter filtering technique, and the like. Pre-processing may be used to improve the signal-to-noise ratio (SNR) and prepare the data for high-resolution imaging at step 330.” ([0063]). HUANG further teaches that this step “may include denoising, enhancement, equalization, and the like, of the MB signals.” ([0067]). Notably, this operation can be applied per pixel. “[D]enoising can be implemented using an intensity-based thresholding method. Such methods are more accurate when it can be assumed that the microbubble signals are stronger than the background noise signals. For example, by suppressing pixels with intensity values less than a selected value (e.g., −30 dB to the maximum intensity value in the current field-of-view), a significant amount of background noise can be suppressed.” ([0058]). Other methods of denoising are described. (see, e.g., [0059]-[0060]).
It would have been obvious to one having ordinary skill in the art at the time of filing to modify the STROBEL system to include reducing background noise to increase a contrast-to-noise ratio (CNR). One of ordinary skill in the art would have been motivated to suppress the background noise, thereby leading to more accurate “microvessel delineation and velocity estimation.” ([0057]). There would have been a reasonable expectation of success as HUANG teaches that such denoising techniques can be applied to CEUS data.
With respect to claim 17 (depending from claim 16), STROBEL does not explicitly teach that the CEUS data comprises the contrast intensity for each pixel. However, STROBEL teaches that embodiments may be directed to ultrasound data and that, for particular embodiments related to X-ray imaging, the relevant data is the time-density curve, which is equivalent to the time-intensity curve in CEUS.
Nonetheless, HUANG teaches that the signal data that is pre-processed includes intensity values from CEUS data. “Conventional ultrasound imaging and CEUS imaging generally displays the image as signal intensities. In accordance with the present disclosure, high spatial and temporal resolution ultrasound imaging techniques may utilize correlation maps to generate images with substantially improved spatial resolution and CNR.” ([0043]). As discussed above, at least one denoising technique includes applying an intensity-based thresholding per pixel. “[D]enoising can be implemented using an intensity-based thresholding method…For example, by suppressing pixels with intensity values less than a selected value (e.g., −30 dB to the maximum intensity value in the current field-of-view), a significant amount of background noise can be suppressed.” ([0058]).
It would have been obvious to one having ordinary skill in the art at the time of filing to modify the STROBEL system to pre-process CEUS data comprising contrast intensity for each pixel. One of ordinary skill in the art would have been motivated to denoise the signal data, as taught in HUANG, to suppress the background noise, thereby leading to more accurate “microvessel delineation and velocity estimation.” ([0057]). There would have been a reasonable expectation of success as HUANG teaches that such denoising techniques can be applied to CEUS data.
Prior Art Made of Record
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US-20150245819-A1 teaches a contrast-enhanced ultrasound (CEUS) system that stores color information for each pixel in which “the opacity of the tone ‘R1’” changes as time elapses. ([0134]). “[T]he pixels are rendered in a manner that the earlier the location of a pixel exceeded the threshold value, the higher is the level of opacity of the color in which the pixel is rendered and in a manner that the later the location a pixel exceeded the threshold value, the higher is the level of transparency of the color in which the pixel is rendered. Accordingly, the doctor is able to distinguish the bloodstream from the perfusion by understanding the levels of transparency, even if the same tone is used.” ([0134]).
CN-109741444-A teaches a 4D contrast-enhanced ultrasound system in which the images are based on time information, color values, and opacity. For example, “[i]n the embodiment of the present application, a color information table that changes with cumulative opacity and time integration is created in advance. As shown in FIG. 5, different cumulative opacity and different time integration values correspond to different colors….” (p.9, lines 27-29).
Conclusion
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/JASON P GROSS/ Examiner, Art Unit 3797
/ANNE M KOZAK/Supervisory Patent Examiner, Art Unit 3797
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