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
Claim 21 is objected to because of the following informalities: the claim refers to ML-based compounding but does not spell out the acronym, nor make it clear if the same. Appropriate correction is required.
Claim Rejections - 35 USC § 112
Claims 21-22 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.
Regarding claim 21, the phrase "for example" renders the claim indefinite because it is unclear whether the limitation(s) following the phrase are part of the claimed invention. See MPEP § 2173.05(d). Claim 22 is rejected for failing to remedy the same issue.
Claim Rejections - 35 USC § 102
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 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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-4, 6, 10-13, 15, 18-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Shin (US 2021/0255321 A1).
Regarding claims 1, 11, and 18, Shin discloses an apparatus of a computing device comprising a memory, and one or more processors coupled to the memory to:
receive, simultaneously, electrical signals based on respective reflected frequencies of a reflected ultrasonic waveform reflected from a target object as a result of a transmitted ultrasonic waveform [[0014] transducer array 12 is provided in an ultrasound probe 10 for transmitting ultrasonic waves and receiving echo information. The transducer array 12 may be a one- or two-dimensional array of transducer elements capable of scanning in two or three dimension];
compound information from the electrical signals to generate compounded electrical signals, wherein compounding includes [[0006] resolution or contrast of an ultrasound image is improved by extrapolation of two ultrasound images of different imaging characteristics, such as aperture size, imaging frequency, or degree of image compounding]:
determining a relationship between, on one hand, a first set of electrical signals corresponding to a first image region of the target object at a first one of the reflected frequencies, and, on another hand, a first set of electrical signals corresponding to the first image region of the target object at a second one of the reflected frequencies [[0012] FIGS. 3a and 3b illustrate two filter characteristics suitable for producing images of different imaging frequencies; [0016] the two signal separators when functioning as a high pass and a low pass filter would lead to the production of a high frequency image and a low frequency image. Another way to differentiate the frequencies of the two images would be to allow one signal separator to pass the full bandwidth 60 of signal frequencies, and restrict the other signal separator to pass only a limited central portion of the full band; [0019] An image produced by an N1 number of elements is used with one produced by an N2 number of elements to predict values for an image from Np elements; [0020] parameters N1 and N2 can represent the number of elements in the aperture (aperture size), the imaging frequency or the number of plane or diverging waves coherently compounded, depending on the specific differentiating characteristic for which the equation is used.] and
using the relationship to predict a second set of electrical signals corresponding to a second image region of the target object at the second one of the reflected frequencies based on a second set of electrical signals corresponding to the second image region of the target object at the first one of the reflected frequencies [[0019] image obtained with an imaging frequency of f1 and another image obtained with an imaging frequency of f2, can be used to predict what an image at an imaging frequency of fp would look like]; and
cause generation of an output image on a display based on the compounded electrical signals [[0007] display a final image predicted by extrapolation; [0019] in the case of plane wave imaging and divergent wave imaging, if N2 plane/diverging waves are used, it is possible to form an image with N1 plane/diverging waves coherently compounded and another image with N2 plane/diverging waves coherently compounded and predict what an image with Np plane/diverging waves coherently compounded would look like].
(claim 11: a user interface device including a display device; and a computing device communicatively coupled to the user interface device, the computing device comprising a memory, and one or more processors coupled to the memory to [[0030] computer or processor may include a computing device, an input device, a display unit and an interface, for example, for accessing the internet. The computer or processor may include a microprocessor. The microprocessor may be connected to a communication bus, for example, to access a PACS system or the data network for importing training images. The computer or processor may also include a memory.]).
(claim 18: a tangible non-transitory machine-readable storage medium having instructions stored thereon, the instructions when executed by one or more processors of a computing device to cause the one or more processors to perform operations including [[0033] software may be in various forms such as system software or application software and which may be embodied as a tangible and non-transitory computer readable medium. Further, the software may be in the form of a collection of separate programs or modules such as a transmit control module, a program module within a larger program or a portion of a program module]).
Regarding claim 2, Shin teaches the apparatus of claim 1, wherein the respective reflected frequencies correspond to respective harmonics of a fundamental frequency of the transmitted ultrasonic waveform, the fundamental frequency being a single frequency of the transmitted ultrasonic waveform [[0016] provide sets of signals of different frequencies for imaging. In these drawings the curve 60 represents the full frequency band of the transducer elements.].
Regarding claim 3, Shin teaches the apparatus of claim 1, wherein the transmitted ultrasonic waveform is a multimodal waveform with fundamental frequencies that correspond to the respective reflected frequencies of the reflected ultrasonic waveform [[0016] provide sets of signals of different frequencies for imaging. In these drawings the curve 60 represents the full frequency band of the transducer elements.].
Regarding claims 4, 12, and 19, Shin teaches the apparatus of claim 1, wherein: the reflected frequencies include N reflected frequencies, and the electrical signals including N sets of electrical signals [[0014] ultrasound probe 10 for transmitting ultrasonic waves and receiving echo information], with each set of electrical signals corresponding to one of the reflected frequencies [[0012]], the N sets of electrical signals corresponding respectively to N input images of the target object [[0007] separate signals received by the transducer array probe into two imaging signal paths of different imaging characteristics; beamform signals, from each imaging signal path, for images of different imaging characteristics; produce ultrasound images of different imaging characteristics; predict an image by extrapolation of the ultrasound images], individual input images including pixels at respective pixel locations, each pixel location of the N input images is defined by a depth and an angle [[0014] direction, spacing, amplitude, phase, frequency, polarity, and diversity of transmit waveforms. Beams formed in the direction of pulse transmission may be steered straight ahead from the transducer array, or at different angles on either side of an unsteered beam for a wider sector field of view]; compounding information includes compounding information from the N sets of electrical signals [[0006] ultrasound image is improved by extrapolation of two ultrasound images of different imaging characteristics, such as aperture size, imaging frequency, or degree of image compounding]; and the one or more processors are to compound the information from the N sets of electrical signals by using at least one of simple averaging, weighted averaging, alpha blending with depth adaptive compounding, maximum and minimum adaptive compounding, predictive compounding, lateral frequency compounding and color Doppler compounding [[abstract] image compounding; [0022] I p′(x,y)=max[min{I 2(x,y),I p(x,y)},0]; [0023] Ip′ by the min operator, but if not, the I2 image value is selected for Ip′ by the preceding equation. The max operator avoids the inclusion of out-of-range negative image values; [0028] predicted images I3 . . . Ip can also be averaged to further enhance the robustness of the technique.].
Regarding claim 6, Shin teaches the apparatus of claim 4, wherein simple averaging includes, for each pixel location, performing one of a simple averaging or a weighted averaging of respective pixel irradiances across the N input images [[0019] image processors 30 b and 30 a are processed by a pixel intensity extrapolator 32 to extrapolate an enhanced image; [0028] predicted images I3 . . . Ip can also be averaged to further enhance the robustness of the technique].
Regarding claims 10 and 13, Shin teaches the apparatus of claim 4, wherein maximum and minimum adaptive compounding includes, for each pixel location, using a blend of maximum, minimum and mean pixel irradiances as between the N input images [[0022] artifact-free image Ip′ is obtained by taking the minimum of the two images I2 (x, y) and the predicted image Ip (x, y) on a pixel-by-pixel basis and then forcing any negative values to zero … I p′(x,y)=max[min{I 2(x,y),I p(x,y)},0]; [0028] predicted images I3 . . . Ip can also be averaged to further enhance the robustness of the technique].
Regarding claims 15 and 20, Shin teaches the system of claim 12, wherein predictive compounding includes: determining a relationship between first electrical signals corresponding to a first region at a first input image corresponding to a first reflected frequency, and second electrical signals corresponding to the first region at a second input image corresponding to a second reflected frequency; and predicting, based on the relationship, third electrical signals corresponding to a second region of the second input image [[0004] paper proposes to extrapolate the pixel values of two images of different aperture sizes (i.e., different numbers of transducer elements) to produce a resultant image with improved resolution].
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 5 is rejected under 35 U.S.C. 103 as being unpatentable over Shin (US 2021/0255321 A1) as applied to claim 1 above, and further in view of Hossack (US 2003/0097068 A1).
Regarding claim 5, Shin does not explicitly teach and yet Hossack teaches the apparatus of claim 1, where the one or more processors are further to subject the electrical signals to gain compensation or dynamic range compensation prior to compounding [[prior art 147] The method of claim 141 wherein steps (b) and (e) comprise a type of ultrasound image processing selected from the group consisting of: persistence compounding, spatial compounding, depth gain compensation, focal gain compensation, post-process mapping, dynamic range alteration, histogram equalization and combinations thereof.; [0227] receive path includes a gain block 418, a receive beamformer 420, a focal gain compensation processor 422, a log compression device 424, a persistence processor 426, a memory 428, a filter 430, a post-processing look-up table 432, a scan converter, and a depth gain compensation processor 434; [0224] ultrasound image processing of ultrasound data to generate an image the same or similar to an image previously generated … as another example, different amounts of compounding, including persistence, may be applied as discussed in the various embodiments above].
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the invention with a reasonable expectation of success to modify the compounding as taught by Shin, with the depth gain compensation, dynamic range alteration, and compounding as taught by Hossack so that previously imaged ultrasound data may be improved [[abstract]] (Hossack).
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Shin (US 2021/0255321 A1) as applied to claim 4 above, and further in view of Manabu (JP 2016209173 A).
Regarding claim 7, Shin does not explicitly teach and yet Manabu teaches the apparatus of claim 4, wherein alpha blending with depth adaptive compounding includes, for each pixel location, multiplying, by a corresponding alpha multiplier, respective pixel irradiances as between the N input images, each alpha multiplier a function of one or more alpha values, the one or more alpha values a function of at least one of depth of said each pixel location or angle of said each pixel location [[abstract] Icomp=Wmax×Imax+(1-Wmax)×Iavg; [pg. 6-7 bridging] C is a sequence for obtaining the ultrasound image data FC, L is a sequence for obtaining the ultrasound image data FL, and R is a sequence for obtaining the ultrasound image data FR. First, the ultrasound image data FC at time T0, the ultrasound image data FL at time T1, and the ultrasound image data FR at time T2 are synthesized (this is referred to as first synthesized image data), and then at time T1. The ultrasonic image data FL, the ultrasonic image data FR at time T2, and the ultrasonic image data FC at time T3 are combined (this is referred to as second combined image data), and then combined in order. Image data is displayed as a moving image in order. Further, it is assumed that the maximum value of the received energy of the pixel among the ultrasonic image data FC, FL, FR at times T0 to T5 is Ir. In spatial compounding using α blending (weighted average compound), the composite received energy of the pixels of the composite image data is the respective composite image data (in the example of FIG. 6, the first composite image data to the fourth composite image data). WmaxIr + (1−Wmax) ((Ic + Il + Ir) / 3). The time contribution in the composite image data is WmaxT2 + (1−Wmax) (T0 + T1 + T2) / 3 (time contribution of the first composite image data) in the first composite image data to the fourth composite image data, respectively. WmaxT2 + (1-Wmax) (T1 + T2 + T3) / 3 (time contribution of second composite image data), WmaxT2 + (1-Wmax) (T2 + T3 + T4) / 3 (time contribution of third composite image data), WmaxT5 + ( 1−Wmax) (T3 + T4 + T5) / 3 (time contribution of the fourth composite image data). Note that the time contribution degree indicates how much time the image data taken contributes to the composite image data.].
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the invention with a reasonable expectation of success to implement the compounding as taught by Shin, with the alpha blending as taught by Manabu to improve a drawing capability of a part of a strong anisotropy and display an image in high image quality in display of ultrasonic image data in a space compound [[abstract]] (Manabu).
Claim 23 is rejected under 35 U.S.C. 103 as being unpatentable over Shin (US 2021/0255321 A1) as applied to claim 19 above, and further in view of Vignon (US 2021/0248724 A1).
Regarding claim 23, Shin does not explicitly teach and yet Vignon teaches the machine-readable storage medium of claim 19, wherein color Doppler compounding includes combining, for each pixel location, respective pixel irradiances as between the N input images based on at least one of depth, angle, signal-to-noise ratio, information regarding flow velocity or power [[0016] coherent echo signals undergo signal processing by a signal processor 26, which includes filtering by a digital filter and optionally noise reduction as by spatial or frequency compounding [0017] Doppler shift is proportional to motion at points in the image field, e.g., blood flow and tissue motion. For a color Doppler image, the estimated Doppler flow values at each point in a blood vessel are wall filtered and converted to color values using a look-up table].
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the invention with a reasonable expectation of success to implement the compounding as taught by Shin, with the compounding with color Doppler as taught by Vignon so that moving blood flow may be estimated [[0017]] (Vignon).
Allowable Subject Matter
Claims 8-9, 14, 16-17, and 24 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Regarding claim 8, the closest prior art does not appear to teach the apparatus of claim 7, wherein, for said each pixel location, an output irradiance at the output image is given by: Iout=Ihigh + (1 - αhigh).(αmid-Imid + (1 - αmid)-Ilow) where: Iout is an output pixel irradiance for said each pixel location for the output image; Ihigh is a pixel irradiance for said each pixel location for an input image corresponding to a highest one of received frequencies; Imid is a pixel irradiance for said each pixel location for an input image corresponding to a middle one of the received frequencies; Ilow is a pixel irradiance for said each pixel location for an input image corresponding to a lowest one of the received frequencies; corresponds to a depth dependent a value of the highest one of the received frequencies; and αmid corresponds to a depth dependent a value of the middle one of the received frequencies.
Regarding claim 9, the closest prior art does not appear to teach the apparatus of claim 7, wherein for said each pixel location, an output irradiance at the output image is given by: (r, e)= (r, 0) + (1 - (r, 0)) (r, e)-Imid + (1 - amid(r,0)).low) where:r: depth;0: angle;Iowt(r,0): output pixel irradiance at depth r and at image angle 0;Ihigh: pixel irradiance at depth r and at image angle 0 for a highest one of received frequencies;Imid: pixel irradiance at depth r and at image angle 0 for a middle one of the received frequencies; : pixel irradiance at depth r and at image angle 0 for a lowest one of the received frequencies;ang corresponds to an alpha value of the highest one of the received frequencies at depth r and image angle 0; andamid corresponds to an alpha value at the middle one of the received frequencies at depth r and image angle 0.
Regarding claim 14, the closest prior art does not appear to teach the system of claim 13, wherein for said each pixel location, an output irradiance at the output image is given by:lout =Imax.amax + (1 - amax).(amin-Imin + (1 - amin)-Idepthcomp) where:Imax MAX(Iigh,Imid'Ilow);Imin: MIN Ideptncomp corresponds to pixel irradiance at said each pixel location after alpha blending with depth compensation; amax corresponds to a maximum transparency alpha value coefficient based on at least one of Imax,Imin, or a set first value between and including 0 and 1;and amin corresponds to a minimum transparency alpha value coefficient based on at least one of Imax,Imin, or amin having a set second value different from the set first value and between and including 0 and 1.
Regarding claim 16, the closest prior art does not appear to teach the system of claim 15, wherein pixel irradiance of a pixel at the second region is given by:IFF2 IFFI.INF2/INF where:FF1 is the second region in the first input image; FF2 is the second region in the second input image; NF1 is the first region in the first input image; NF2 is the first region in the second input image; IFF2 is pixel irradiance at FF2; IFF1 is pixel irradiance at region FF1; INF2 is pixel irradiance at region NF2; andINF1 is pixel irradiance at region NFl.
Regarding claim 17, the closest prior art does not appear to teach the system of claim 15, wherein pixel irradiance of a pixel at the second region is given by:IFF2 INF2 x (IFFI * PSF2 inverse)/(INF1*PSFlinverse) where:FF1 is the second region in the first input image; FF2 is the second region in the second input image; NF2 is the first region in the second input image; IFF2 is pixel irradiance at FF2; IFF1 is pixel irradiance at region FF1; INF2 is pixel irradiance at region NF2; PSF1 corresponds to point spread function (PSF) for a first received frequency; PSF2 corresponds to PSF for a second received frequency; PSFlinverse is an inverse of PSF1 corresponding to a deconvolution; and PSFlinverse is an inverse of PSF1 corresponding to a deconvolution.
Regarding claim 24, the closest prior art does not appear to teach the machine-readable storage medium of claim 23, wherein a ROout and Rlout of the output image is given by:= a. ROout.max + (1 - a). R0out.mean and R10ut= a. R1out.max + (1 - a). R10ut.mean where:ROour : zero lag output corresponding to an alpha blended value of max and mean zero lag autocorrelations;RIour : first lag output corresponding to an alpha blended value of the max and mean first lag autocorrelations;a: alpha value for the alpha blending;R Oout.max: maximum zero lag output value of the autocorrelation corresponding to an alpha-blending to be used;R1out.max: maximum first lag output value of the autocorrelation;ROout.mean: mean zero lag output value of the autocorrelation corresponding to the alpha-blending to be used;R1out.mean: mean first lag output value of the autocorrelation;(i): zero lag input value corresponding to frequency band of imaging waveforms for the autocorrelation corresponding to the alpha-blending to be used; andR (i): first lag input value corresponding to the frequency band of imaging waveforms for the autocorrelation corresponding to the alpha-blending to be used.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JONATHAN D ARMSTRONG whose telephone number is (571)270-7339. The examiner can normally be reached M - F 9am-5pm.
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/JONATHAN D ARMSTRONG/ Examiner, Art Unit 3645
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