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 1 and 5 are objected to because of the following informalities:
In claim 1, line 32, it appears the last ‘a’ should be ‘the’, as the target object is previously set forth.
In claim 5, line 10, it appears ‘group is’ should be ‘groups are’ to set forth which groups are being referred to.
Appropriate correction is required.
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 1-4 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Apostolakis et al (US Pub 2023/0228873 -cited by applicant).
Re claim 1: Apostolakis discloses an ultrasound diagnostic apparatus comprising:
a transmission unit that transmits ultrasound pulses N times through an ultrasound probe, where N is an integer of 2 or more [0032, 0038, fig 2; see the transmit control 220 where the probe transmits an ensemble of ultrasound pulses which includes a plurality of pulses];
a reception unit that receives reflected waves generated N times in a measurement target object through the ultrasound probe [0038, fig 2; see beamformer 222 where the probe receives ultrasound signals responsive to the transmitted ensemble]; and
an information processing unit that generates N reception Doppler signals from N reception pulse signals output from the reception unit in response to the reflected waves generated N times in the measurement target object and that executes processing on each of the reception Doppler signals [0033, 0034, 0037, fig 2; Doppler signal path 262 and the Doppler image data], wherein the information processing unit includes
a filter that performs high-pass filter processing on the N reception Doppler signals [0037; see that processor 260 filters out unwanted signals and see the high pass wall filter],
a Doppler measurement section that generates Doppler measurement information of the measurement target object based on the N reception Doppler signals that have been subjected to the high-pass filter processing [0037, fig 2; the Doppler processor 260 estimates Doppler shift and generates Doppler image data], and
a machine learning model that is constructed based on training data, under a condition that J and K are integers of 2 or more, with J being greater than K, the training data includes training information that is at least one of reception characteristic information, which is derived from each of the reception Doppler signals in a case in which N is set to K, or the Doppler measurement information, which is generated by the Doppler measurement section in a case in which N is set to K, and target information that is at least one of the reception characteristic information, which is derived from each of the reception Doppler signals in a case in which N is set to J, or the Doppler measurement information, which is generated by the Doppler measurement section in a case in which N is set to J, for the same measurement target object as that in a case in which N is set to K [0028, 0053, 0056, fig 4; see the artificial intelligence that includes neural networks with short/decimated ensembles as inputs and long/high PRF ensemble images as output; see the linking of short/undersampled ensembles to CD images generated using longer ensembles or ensembles with higher PRF; once trained, the deep learning framework provides CD images from short ensembles that are higher quality], and
the machine learning model generates the Doppler measurement information based on input information that is at least one of the reception characteristic information, which is derived from each of the reception Doppler signals in a case in which N is set to K, or the Doppler measurement information, which is generated by the Doppler measurement section in a case in which N is set to K, for a measurement target object in a subject [0027, 0057; the CD images from the deep learning are closer in quality to CD images generated from long/high PRF ensembles; the signals may or may not be wall filtered].
Re claim 2: The reception characteristic information includes at least one of: the N reception Doppler signals before the high-pass filter processing [0057]; or the N reception Doppler signals after the high-pass filter processing [0057; the neural network receives previously unseen portions of signals from short ensembles as inputs].
Re claim 3: The Doppler measurement information includes at least one of: autocorrelation values of the N reception Doppler signals after the high-pass filter processing; a velocity of the measurement target object obtained from the N reception Doppler signals after the high-pass filter processing; a Doppler frequency variation degree for the N reception Doppler signals after the high-pass filter processing; or a value indicating a magnitude of the N reception Doppler signals after the high-pass filter processing [0037, 0056; the outputs 506 include components of CD images such as the phase of the autocorrelation; the processor filters out unwanted signals and receives velocity estimates using an auto-correlator].
Re claim 4: The transmission unit transmits an ultrasound wave for B-mode image generation through the ultrasound probe, the reception unit receives a reflected wave for B-mode image generation generated in the measurement target object through the ultrasound probe, the information processing unit further includes a B-mode image generation section that generates B-mode image data based on a B-mode image reception signal output from the reception unit in response to the reflected wave for B-mode image generation, and the B-mode image reception signal output from the reception unit is utilized as any of the N reception pulse signals output from the reception unit in response to the reflected wave for B-mode image generation [0025, 0033, 0035; see that both Doppler and B-mode frames are acquired; see the B-mode signal path 258 which couples the signals from the processor to a B-mode processor 228 for producing B-mode image data].
Allowable Subject Matter
Claims 5 and 6 are 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.
Conclusion
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/MICHAEL T ROZANSKI/Primary Examiner, Art Unit 3797