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 .
DETAILED ACTION
Response to Amendment
Applicant's arguments filed 8/17/2026 have been fully considered but they are not persuasive.
Regarding applicant’s arguments on pages 8-11 are directed toward the combination of Walker et al in view of Hu et al. As discussed during the interview, the examiner noted that the use of weighted prediction (bi directional) in video frames is well known technology. Hu was cited as teaching that the technology could be used in many areas including ultrasound sensors. The references are combinable under 35 USC 103 in light of KSR v Teleflex in that the references can be combined by known techniques (i.e. Switch out a video camera for an ultrasounder) and yield a predictable result. In that ultrasound images will produce a video with frames predicted in between I frames.
Applicant’s response is to incorporate the claim limitations of claim 5 into claim 1. Claim 5 was originally rejected based on (Official Notice) under 35 USC 103. This amendment is effectively challenging the Official Notice. A search did produce prior art which accounts for prediction and averaging of frames based on beamforming delays. Therefore, the obvious rejection is maintained using the newly applied Yang et al reference. Therefore, the arguments on pages 11-15 are not considered persuasive.
On pages 15-16 applicant argues that dependent claims 2-4 are allowable for the reasons the independent claims are. However the examiner can not agree in that the Walker reference teaches each of the dependent claims as shown below.
On pages 16-22 applicant argues claims 6-8 and 20 are not properly rejected. However as discussed below Walker teaches the weighting adjustments are calculated (or learned). To apply this weighting over again (to a second frame) is taught in that multiple frames happen per second in video. So to argue that Walker’s weighting can not be done several times (to a second frame) is not convincing so the rejection is maintained.
As for the arguments on pages 23-28 regarding claims 9-16, applicant argues that dependent claims 2-4 are allowable for the reasons the independent claims are. However, the examiner can not agree in that the Walker reference teaches each of the dependent claims as shown below.
Applicant’s arguments regarding claim 17 are persuasive so the rejection of claim 17 is withdrawn.
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.
Claim(s) 1-4, 18 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Walker et al. US PGPub 2005/0281334 (Walker) in view of Hu et al. US PGPub 2020/0265567 (Hu) in further view of Yang et al. (2022/0299634).
Regarding claims 1 and 18, Walker discloses a computer method and system (figure 1), comprising: a memory (encoder 105) that stores computer executable instructions; and a processor that executes the computer executable instructions that, when executed by the processor, facilitate performance of operations comprising:
generating one or more first images by applying an image prediction function to respective second images (function is considered past image plus changes), wherein the image prediction function leverages redundancies between the respective second images to predict the one or more first images (paragraphs 6 and 24, where inter-prediction P frames and bi-directional prediction B frames leverage redundant (non-motion areas) between frames);
generating a set of images comprising the one or more first images and the respective second images (paragraph 27 i.e. GOP group of pictures which have I, B and P frames); and
generating a compounded image by computing a weighted average of respective images comprised in the set of images (paragraph 6 B or bi-directional predicted frame is a weighted average of I and P frames).
Although Walker fails to show that the required compounded images are produced from an ultrasound device, Hu does (see Hu paragraph 49 also note paragraph 38). Since Walker teaches a well known image encoder which uses temporal redundancies for image prediction and encoding, it would have been obvious to one of ordinary skill in the art before the time of filing to apply image prediction and frame averaging to ultrasound images to achieve image encoding. One would be motivated to use common encoding for many types of images to produce high quality video at reasonable data rates and sizes to save storage requirements.
Walker and Hu also fail to specifically teach applying the image prediction function after applying beamforming delays to the respective second ultrasound images as now present in the independent claims. However, Yang et al in the same field of endeavor teaches that beamforming delays, weighting and averaging cause scan lines to be created (paragraph 122). Therefore, since beamforming delays must be compensated for, it would have been obvious to one of ordinary skill in the art before the time of filing to improve Walker and Hu to compensate for the beamforming time because it is a delay in the creation of ultrasound images. In that ultrasound beamforming is subject to movement and refocusing so one of ordinary skill must process frames (average and predict) knowing that images do not come as consistent as with other forms for image production.
As for claims 2 and 19, Hu teaches accessing a first set of training ultrasound images; and learning the image prediction function by predicting a sequence of training ultrasound images comprised in the first set of training ultrasound images based on a preceding sequence of training ultrasound images comprised in the first set of training ultrasound images. (see figure 8)
As for claims 3 and 4, Walker teaches the method and system of claim 1, wherein the compounded image is a sum of delayed data comprised in the set of images (note figure 2B of Walker where delayed images 22 and 24 is part of image 26).
Claims 6-8 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Walker et al. US PGPub 2005/0281334 (Walker) in view of Hu et al. US PGPub 2020/0265567 (Hu) in view of Yang et al. in further view of Condorovici 2019/0108621.
Regarding claim 6-8 and 20, although Walker, Hu and Yang fail to specifically teaches predicting respective weights for the respective ultrasound images by applying a fixed weight prediction function to generate the compounded image; and analyzing contrast present Condorovici does (see paragraph 10, 88 and 94). Since all three systems are in the same field of endeavor it would have been obvious to one of ordinary skill in the art before the time of filing to include the weighting as fixed based on contrast to improve image quality. It should also be noted that one of ordinary skill would recognize the importance of having high quality images as a base for others to depend from, so errors will not propagate.
Claim(s) 9-16 are rejected under 35 U.S.C. 103 as being unpatentable over Condorovici 20190108621 in view of Yang et al. 20210314474 in further view of Yang et al. (2022/0299634)
Regarding claim 9, Condorovici discloses a computer-implemented method, comprising: predicting, by a system operatively coupled to a processor, respective weights for respective images comprised in a set of images (paragraph 54) by applying a weight prediction function to the respective images(paragraphs 42-47 where parameter w is considered a weight applied to each frame x); computing, by the system, based on the respective weights, a weighted average of the respective images in a convolutional manner (figure 1B shows the convolutions and weights proportionally ie averages); and generating, by the system, a compounded image based on the computing (figure 8 shows compounded image).
Although Condorovici fails to specially mention that the weight prediction of images can be used on ultrasound images, Yang does (see paragraph 45) where ultrasound images are taught. Since Yang shows that training a system to enhance images is well known it would have been obvious to one of ordinary skill in the art before the time of filing to combine the teaching of Condorovici’s weighted prediction on to ultrasound images since Yang notes it is well known to apply such enhancement to many types of images.
Condorovici and Yang also fail to specifically teach applying the image prediction function after applying beamforming delays to the respective second ultrasound images as now present in the independent claims. However, Yang et al in the same field of endeavor teaches that beamforming delays, weighting and averaging cause scan lines to be created (paragraph 122). Therefore, since beamforming delays must be compensated for, it would have been obvious to one of ordinary skill in the art before the time of filing to improve Condorovici and Yang to compensate for the beamforming time because it is a delay in the creation of ultrasound images. In that ultrasound beamforming is subject to movement and refocusing so one of ordinary skill must process frames (average and predict) knowing that images do not come as consistent as with other forms for image production.
Regarding claims 10 and 12, Condorovici teaches accessing, by the system, a set of training ultrasound images; and learning, by the system, the weight prediction function by learning respective fixed weights associated with respective training ultrasound images comprised in the set of training ultrasound images (paragraph 88), wherein the learning the fixed weights comprises analyzing contrast present in a training compounded image generated from the set of training ultrasound images (paragraph 94).
Regarding claim 11, both Condorovici and Yang teach that function is learned by a neural network model that applies the weight prediction function in lieu of a set of fixed weights associated with the respective ultrasound images (Condorovici paragraph 15 where weights are changed and Yang paragraph 66).
Regarding claim 13, Condorovici’s figure 1B teaches the compounded image is generated by a multi-stage model comprising the neural network model in a cascading approach, and wherein the generating comprises: inputting, by the system, an overlapping sliding queue of data corresponding to the respective ultrasound images into a plurality of models to generate an output; and inputting, by the system, the output into the neural network model to generate the compounded image.
Regarding claims 14 and 15, Condorovici teaches applying a neural network model and modifying it (paragraph 49).
Regarding claim 16 Condorovici wherein the cascading approach increases contrast in the compounded image (paragraph 10).
Allowable Subject Matter
Claim 17 is 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
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRISTOPHER S KELLEY whose telephone number is (571)272-7331. The examiner can normally be reached Mon-Fri 6:30 to 4 pm alternate Fridays off.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Colleen Fauz can be reached at 571-272-1617. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CHRISTOPHER S KELLEY/Supervisory Patent Examiner, Art Unit 2482
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