Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 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.
Claim(s) 1-2, 8, 14-16 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Roffe et al. (US10667776).
To claim 1, Roffe teach a computer-implemented method of determining image perspective score values for X-ray projection images representing a region of interest in a subject (Fig. 4; column 8 lines 24-26, 32-33, 49-50), the method comprising:
receiving a plurality of X-ray projection images representing the region of interest from a plurality of different perspectives of an X-ray imaging system respective the region of interest (column 8 lines 24-26, 32-33, a temporal series of angiographic images is acquired, the positioning of a C-arm may be stored as an attributed of the temporal series of images);
inputting the X-ray projection images into a neural network (column 8 line 48, 63-64, deep learning classifier/neural network); and
in response to the inputting, generating a predicted image perspective score value for each of the X-ray projection images (column 8 lines 49-50, each image may be rated or stored for quality or usefulness; column 9 lines 12-24, the classifier may be trained to output a label of each of the image frames); and
wherein the neural network is trained to generate the predicted image perspective score values for the X-ray projection images (column 6 lines 64-66).
To claim 14, Roffe teach a non-transitory computer-readable storage medium having stored a computer program comprising instructions which, when executed by one or more processors, cause the one or more processors to carry out (as explained in response to claim 1 above).
To claim 15, Roffe teach a system for determining image perspective score values for X-ray projection images representing a region of interest in a subject (as explained in response to claim 1 above).
To claims 2 and 16, Roffe teach claims 1 and 14.
Roffe teach wherein the neural network is further configured to generate a confidence value for each of the predicted image perspective score values, and wherein the method further comprises outputting the confidence values (column 7 lines 49-58; column 9 lines 25-44; column 9 line 65 to column 10 line 7).
To claim 8, Roffe teach claim 1.
Roffe teach further comprising: determining a subsequent perspective of the X-ray imaging system for generating X-ray projection images of the region of interest in the subject; and wherein the subsequent perspective is determined based on at least one of:
the predicted image perspective score values generated by the neural network for the X-ray projection images and the corresponding perspectives of the X-ray imaging system respective the region of interest; and the combined image perspective score values provided for the received X-ray projection images and the corresponding perspectives of the X-ray imaging system respective the region of interest (column 6 lines 1-15, column 10 lines 8-9, a second view of the anatomical structure is identified based on the identification and score; column 10 lines 23-24, the next optimal view may be identified for instance by evaluating the C-arm angulation associated with the temporal series with the highest optimality score from previous scans).
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) 3, 7, 17, 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Roffe et al. (US10667776) in view of Auvray et al. (US9713451).
To claims 3, 17 and 19, Roffe teach claims 1, 14 and 15.
Roffe teach wherein the X-ray projection images represent the region of interest from a corresponding perspective of the X-ray imaging system respective the region of interest in the subject, and wherein the method further comprises:
receiving a 3D X-ray image representing the region of interest (column 10 lines 23-36); and for each of the received X-ray projection images: registering the region of interest in the 3D X-ray image to the region of interest in the X-ray image to provide a perspective of the X-ray imaging system respective the region of interest in the 3D X-ray image; computing an analytical image perspective score value from the 3D X-ray image based on the perspective of the X-ray imaging system respective the region of interest in the 3D X-ray image, the analytical image perspective score value computed from the 3D X-ray image based on one or more of the following metrics: a degree of overlap between a plurality of features in the region of interest, a foreshortening of one or more features in the region of interest, and a presence of one or more artifacts in the region of interest; and combining the analytical image perspective score value and the predicted image perspective score value, to provide a combined image perspective score value for the X-ray projection image (obvious in column 9 line 45 to column 10 line 7, complementary classifiers).
In furthering said obviousness, Aivrau teach receiving a 3D X-ray image representing the region of interest (abstract); and for each of the received X-ray projection images: registering the region of interest in the 3D X-ray image to the region of interest in the X-ray image to provide a perspective of the X-ray imaging system respective the region of interest in the 3D X-ray image; computing an analytical image perspective score value from the 3D X-ray image based on the perspective of the X-ray imaging system respective the region of interest in the 3D X-ray image, the analytical image perspective score value computed from the 3D X-ray image based on one or more of the following metrics: a degree of overlap between a plurality of features in the region of interest, a foreshortening of one or more features in the region of interest, and a presence of one or more artifacts in the region of interest; and combining the analytical image perspective score value and the predicted image perspective score value, to provide a combined image perspective score value for the X-ray projection image (column 1 line 33 to column 5 line 29), which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate into the method and apparatus of Roffe, in order to obtain score implementation by design preference.
To claim 7, Roffe teach claim 1.
Roffe teach wherein the plurality of X-ray projection images represent the region of interest from a corresponding perspective of the X-ray imaging system respective the region of interest in the subject, and wherein the method further comprises:
obtaining, from a database, a reference value of an analytical image perspective score for the X-ray projection image, the analytical image perspective score representing one or more of the following metrics: a degree of overlap between a plurality of features in the region of interest, a foreshortening of one or more features in the region of interest, and a presence of one or more artifacts in the region of interest; and outputting the reference analytical image perspective score value for the X-ray projection image, wherein the reference value of the analytical image perspective score is obtained from the database by (column 1 lines 55-65; column 12 lines 56-65): comparing the X-ray projection image with a database of reference X-ray projection images and corresponding reference analytical image perspective score values; and selecting the reference analytical image perspective score value from the database based on a computed value of a similarity metric representing a similarity between the X-ray projection image and the reference X-ray projection images in the database (obvious thru classification, column 5 line 13 to column 10 line 49).
In furthering said obviousness, Aivrau teach obtaining, from a database, a reference value of an analytical image perspective score for the X-ray projection image, the analytical image perspective score representing one or more of the following metrics: a degree of overlap between a plurality of features in the region of interest, a foreshortening of one or more features in the region of interest, and a presence of one or more artifacts in the region of interest; and outputting the reference analytical image perspective score value for the X-ray projection image, wherein the reference value of the analytical image perspective score is obtained from the database by: comparing the X-ray projection image with a database of reference X-ray projection images and corresponding reference analytical image perspective score values; and selecting the reference analytical image perspective score value from the database based on a computed value of a similarity metric representing a similarity between the X-ray projection image and the reference X-ray projection images in the database (column 4 lines 11-39, column 12 lines 3-23, column 14 lines 45-63), which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate into the method of Roffe, in order to obtain score implementation by design preference.
Claim(s) 10-11, 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Roffe et al. (US10667776).
To claim 10, Roffe teach claim 1.
Roffe teach wherein the neural network is trained to generate the predicted image perspective score values for the X-ray projection images by: receiving X-ray projection image training data comprising a plurality of training projection images representing the region of interest from different perspectives of an X-ray imaging system respective the region of interest, the training projection images comprising corresponding ground truth image perspective score values; and
inputting the training projection images, and the corresponding ground truth image perspective score values, into the neural network, and adjusting parameters of the neural network until a difference between the image perspective score values predicted by the neural network, and the corresponding inputted ground truth image perspective score values, meet a stopping criterion (obvious in column 5 lines 37-40, despite lack of detailed disclosure, the claimed training steps are typical in neural network training involving cyclical process of forward propagation, loss calculation, backpropagation, and weight updates over multiple epochs until meeting a stopping criterion, which is well-known in the art for obvious training implementation, hence Official Notice is taken).
To claim 11, Roffe teach claim 1.
Roffe teach wherein the neural network is trained to generate the predicted image perspective score values for the X-ray projection images by: receiving volumetric training data comprising one or more 3D X-ray images representing the region of interest; generating virtual projection image training data by projecting the one or more 3D X-ray images onto a virtual detector plane of the X-ray imaging system at a plurality of different perspectives of the X-ray imaging system with respect to each 3D X-ray image to provide a plurality of synthetic projection images; computing, for each synthetic projection image, an analytical image perspective score value for each corresponding perspective of the X-ray imaging system respective the 3D X-ray image, the analytical image perspective score value being computed from the 3D X-ray image based on one or more of the following metrics: a degree of overlap between a plurality of features in the region of interest, a foreshortening of one or more features in the region of interest, and a presence of one or more artifacts in the region of interest;
selecting a subset of the synthetic projection images having analytical image perspective score values meeting a predetermined selection criterion for use in training the neural network;
receiving ground truth image perspective score values for the selected subset of the synthetic projection images; and inputting the subset of the synthetic projection images, and the corresponding ground truth image perspective score values, into the neural network, and adjusting parameters of the neural network until a difference between the image perspective score values predicted by the neural network, and the corresponding inputted ground truth image perspective score values, meet a stopping criterion (obvious in column 5 lines 37-40, despite lack of detailed disclosure, the claimed training steps are typical in neural network training involving cyclical process of forward propagation, loss calculation, backpropagation, and weight updates over multiple epochs until meeting a stopping criterion, which is well-known in the art for obvious training implementation, hence Official Notice is taken).
To claim 13, Roffe teach claim 10.
Roffe teach wherein the respective training projection images, or the selected subset of the synthetic projection images, comprise at least some projection images having ground truth image perspective score values that exceed a first threshold value, and at least some ground truth image perspective score values that are below a second threshold value (obvious in column 5 lines 37-40, despite lack of detailed disclosure, the claimed training steps are typical in neural network training involving cyclical process of forward propagation, loss calculation, backpropagation, and weight updates over multiple epochs until meeting a stopping criterion such as threshold comparisons, which is well-known in the art for obvious training implementation, hence Official Notice is taken).
Allowable Subject Matter
Claims 4-6, 9, 12, 18, 20 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
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ZHIYU LU whose telephone number is (571)272-2837. The examiner can normally be reached Weekdays: 8:30AM - 5:00PM.
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ZHIYU . LU
Primary Examiner
Art Unit 2669
/ZHIYU LU/Primary Examiner, Art Unit 2665 February 9, 2026