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 .
Response to Arguments
Applicant’s arguments, see page 6, filed 11/21/25, with respect to claim 11 have been fully considered and are persuasive. The objection has been withdrawn.
Applicant's arguments filed 11/21/25 have been fully considered but they are not persuasive.
Regarding applicant’s argument for claim 1, on page 7, that the provisional application filed 5/18/2023 does not disclose a determination of normal/abnormal, examiner disagrees. Paragraphs 2, 3 and 36 of the provisional clearly disclose classifying tissues of regions of interest (e.g. lobes) as either a particular disease or normal. Therefore the argument is overcome and the previous rejection remains.
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)(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.
1) Claim(s) 1, 4, 6, 10, 11, 14, 16 and 20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by U.S. patent application publication 2024/0386552 by Peterson et al.
2) Claims 1, 4, 6 and 10 are taught in the same manner as described in the rejection of claims 11, 14, 16 and 20 below, respectively.
3) Regarding claim 11, Peterson teaches a device for detecting pulmonary function based on low-dose computed tomography (CT) chest images (paragraph 24; data can be obtained from low-dose CT), comprising: a processor; and a memory coupled with the processor, wherein the processor executes computer-readable instructions stored in the memory to perform operations (paragraph 23; memory and processor disclosed), and the operations comprise: receiving a plurality of chest images, the plurality of chest image generated by a low-dose CT method (paragraphs 4 and 23; plurality of images of lungs can be obtained); determining, by the processor, a plurality of regions of interest (ROIs) within each chest image through applying the plurality of chest images to an image processing model, the plurality of ROIs corresponding to five lung lobes (paragraph 25; figure 1, item 3; lobes are segmented); determining, by the processor, Tij descriptors for the j-th ROI of the i-th chest image, each descriptor associated with a radiodensity value of one or more pixels (paragraph 31; Hounsfield units are determined at each voxel); and determining, by the processor, whether a pulmonary function of the respective lung lobe is normal or abnormal based on the descriptors through a classifier model (paragraphs 4, 58 and 59; normal/abnormal determination can be made for regions of interest [ROI can be the lobes]).
4) Regarding claim 14, Peterson teaches the device of claim 11, wherein determining the pulmonary function of the respective lung lobe further comprises: determining whether the pulmonary function of the respective lung lobe is normal or abnormal through applying the descriptors to the classifier model (figure 2; paragraph 42; HUs are utilized to classify lung tissue ROIs).
5) Regarding claim 16, Peterson teaches the device of claim 14, wherein each descriptor is further associated with at least one of: a serial number of ROI, a serial number of chest image, or coordinate values of the one or more pixels (paragraphs 26 and 30; voxel of image data inherently has a coordinate location within the image).
6) Regarding claim 20 , Peterson teaches the device of claim 14, wherein the operations further comprise: determining a feature vector for the j-th ROI of the i-th chest image based on the Tij descriptors; and determining whether the pulmonary function is normal or abnormal through applying the feature vectors to the classifier model (paragraph 31; HU of a particular voxel is a feature vector of the voxel).
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.
8) Claim(s) 3, 5, 13 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. patent application publication 2024/0386552 by Peterson et al. as applied to claims 1 and 11 above, and further in view of U.S. patent application publication 2025/0111516 by Slomka et al.
9) Claims 3 and 5 are taught in the same manner as described in the rejection of claims 13 and 15 below, respectively.
10) Regarding claim 13, Peterson does not specifically teach the device of claim 11, wherein determining the pulmonary function of the respective lung lobe further comprises: determining that the pulmonary function of the respective lung lobe is normal in response to an average of the corresponding descriptors being greater than a threshold; and determining that the pulmonary function of the respective lung lobe is abnormal in response to the average of the corresponding descriptors being smaller than the threshold.
Slomka teaches the device of claim 11, wherein determining the pulmonary function of the respective lung lobe further comprises: determining that the pulmonary function of the respective lung lobe is normal in response to an average of the corresponding descriptors being greater than a threshold; and determining that the pulmonary function of the respective lung lobe is abnormal in response to the average of the corresponding descriptors being smaller than the threshold (paragraph 124; average intensity of voxels across an ROI can be used to score the ROI).
Peterson and Slomka are combinable because they are both from the lung imaging field of endeavor.
It would have been obvious to a person of ordinary skill in the art at the time the invention was effectively filed to combine Peterson with Slomka to add determining normality through averaging. The motivation for doing so would have been to help diagnose disease in each lobe of the lungs (paragraph 131). Therefore it would have been obvious to combine Peterson with Slomka to obtain the invention of claim 13.
11) Regarding claim 5, Slomka (as combined with Peterson in the rejection of claim 13 above) teaches the device of claim 14, wherein the classifier model includes at least one of a support vector machine, a decision tree, a neural network, a random forest, or a regression model (paragraph 33; neural networks are utilized for classification).
12) Claim(s) 7 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. patent application publication 2024/0386552 by Peterson et al. as applied to claims 1 and 11 above, and further in view of U.S. patent application publication 2021/0059765 by Ye.
13) Claim 7 is taught in the same manner as described in the rejection of claims 13 and 17 below.
14) Regarding claim 17, Peterson does not specifically teach the device of claim 14, wherein the Tij descriptors for the j-th ROI of the i-th chest image are determined based on one of: the scale-invariant feature transform (SIFT) algorithm, the dense trajectory (DT) algorithm, or the improved dense trajectory (iDT) algorithm.
Ye teaches the device of claim 14, wherein the Tij descriptors for the j-th ROI of the i-th chest image are determined based on one of: the scale-invariant feature transform (SIFT) algorithm, the dense trajectory (DT) algorithm, or the improved dense trajectory (iDT) algorithm (paragraphs 101 and 148; features in low-dose CT can be identified with SIFT).
Peterson and Ye are combinable because they are both from the lung imaging field of endeavor.
It would have been obvious to a person of ordinary skill in the art at the time the invention was effectively filed to combine Peterson with Ye to add utilizing the SIFT algorithm. The motivation for doing so would have to efficiently determine features of an image. Therefore it would have been obvious to combine Peterson with Ye to obtain the invention of claim 17.
15) Claim(s) 8 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. patent application publication 2024/0386552 by Peterson et al. as applied to claims 1 and 11 above, and further in view of U.S. patent 11,684,293 by Slepian.
16) Claim 8 is taught in the same manner as described in the rejection of claims 13 and 18 below.
17) Regarding claim 18, Peterson does not specifically teach the device of claim 11, wherein the classifier model is configured to determine whether a value of FEV1/FVC is greater or less than 70% based on the descriptors.
Slepian teaches the device of claim 11, wherein the classifier model is configured to determine whether a value of FEV1/FVC is greater or less than 70% based on the descriptors (column 6, table 1, lines 63-65 and column 8, line 65 – column 9, line 3; determination of FEV1/FVC is performed by a classifier).
Peterson and Slepian are combinable because they are both from the lung imaging field of endeavor.
It would have been obvious to a person of ordinary skill in the art at the time the invention was effectively filed to combine Peterson with Slepian to add determining FEV1/FVC. The motivation for doing so would have been to determine normality of lung function. Therefore it would have been obvious to combine Peterson with Slepian to obtain the invention of claim 18.
18) Claim(s) 9 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. patent application publication 2024/0386552 by Peterson et al. as applied to claims 1 and 11 above, and further in view of U.S. patent application publication 2022/0180514 by Vlasimsky.
19) Claim 9 is taught in the same manner as described in the rejection of claims 13 and 19 below.
20) Regarding claim 19, Peterson does not specifically teach the device of claim 11, wherein the image processing model include a U-NET model.
Vlasimsky teaches the device of claim 11, wherein the image processing model include a U-NET model (paragraph 103; lung segmentation can utilize a U-NET model).
Peterson and Vlasimsky are combinable because they are both from the lung imaging field of endeavor.
It would have been obvious to a person of ordinary skill in the art at the time the invention was effectively filed to combine Peterson with Vlasimsky to add a U-NET model. The motivation for doing so would have been to efficiently identify segments of an image. Therefore it would have been obvious to combine Peterson with Vlasimsky to obtain the invention of claim 19.
Allowable Subject Matter
Claims 2 and 12 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
THIS ACTION IS MADE FINAL. 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.
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BENJAMIN O. DULANEY
Primary Examiner
Art Unit 2676
/BENJAMIN O DULANEY/Primary Examiner, Art Unit 2683