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 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (US 2014/0039318 A1) in view of Schneider et al. (US 2019/0059858 A1).
Regarding claim 1, Zhang et al. (‘318) teach a computer-implemented method, comprising: receiving as input from an ultrasound acquisition system a 3D ultrasound image dataset comprising at least one 3D image frame spanning a 3D field (see [0039]); applying a disease detection module adapted for processing input 3D image frames and detecting one or more suspected disease features therein of a pre-defined set of possible disease features (see [0043]); and applying a plane-mapping module adapted to determine for each 3D image frame a set of one or more 2D slices through the 3D field of the image frame based on an output from the disease detection module, for imaging one or more disease regions associated with the detected one or more disease features (see [0052], [0054]-[0055]), but fails to explicitly teach generating control instructions for output to the ultrasound acquisition system for causing automated acquisition of set of new 2D image frames with corresponds to the set of one or more 2D slices. However, Schneider et al. (‘858) from the same field of endeavor do teach generating control instructions for output to the ultrasound acquisition system for causing automated acquisition of set of new 2D image frames with corresponds to the set of one or more 2D slices (see [0025]-[0026]; and Fig. 4). It would be obvious to one of ordinary skill in the art to modify the invention of Zhang et al. with the features of Schneider et al. for the benefit of improved image feature tracking.
Regarding claim 2, Zhang et al. (‘318) in view of Schneider et al. (‘858) teach the method of claim 1, wherein the input 3D ultrasound image dataset comprises a stream of 3D image frames, and wherein the steps of the method are performed in real time with receipt of each 3D image frame (see Zhang et al. [0042]).
Regarding claim 3, Zhang et al. (‘318) in view of Schneider et al. (‘858) teach the method of claim 1, wherein the plane-mapping module is adapted to use a look-up table to select a pre-determined plane based on the one or more detected disease features (see Zhang et al. [0044]).
Regarding claim 4, Zhang et al. (‘318) in view of Schneider et al. (‘858) teach the method of claim 1, wherein the disease detection module is adapted to generate for the at least one 3D image frame a 3D spatial map of disease regions within the 3D field of the image frame corresponding to the disease features; and wherein the plane-mapping module is adapted for receiving as input a 3D map of detected disease regions within a 3D field, and is adapted for determining a set of one or more 2D slices through the 3D field intersecting with the disease regions, in dependence upon the map (see Zhang et al. [0042], [0052], [0054]-[0055]).
Regarding claim 5, Zhang et al. (‘318) in view of Schneider et al. (‘858) teach the method of claim 4, wherein, the plane mapping module is adapted to perform a spatial fitting of planes to the one or more disease regions, to determine a set of one or more 2D slices which intersect all of the regions, and optionally which meet a further one or more constraints (see Zhang et al. [0042], [0044]).
Regarding claim 6, Zhang et al. (‘318) in view of Schneider et al. (‘858) teach the method of claim 4, wherein, for at least a subset of the pre-defined set of disease features, the detection of the disease feature by the disease-detection module comprises segmenting and classifying one or more spatial regions as suspicious regions, and wherein the 3D spatial map output by the disease detection module comprises a map of the segmented suspicious regions (see Zhang et al. [0042], [0044], [0052], [0054]-[0055]).
Regarding claim 7, Zhang et al. (‘318) in view of Schneider et al. (‘858) teach the method of claim 4, wherein, for at least a subset of the pre-defined set of disease features, the detection of the respective disease feature by the disease-detection module comprises computing a 3D saliency map spanning the 3D field in relation to the disease feature, and deriving a discrete classification of the 3D image in relation to the feature based on the saliency map, and wherein the saliency map is used as the 3D spatial map of disease regions (see Zhang et al. [0042], [0044], [0052], [0054]-[0055]).
Regarding claim 8, Zhang et al. (‘318) in view of Schneider et al. (‘858) teach the method of claim 7, wherein the plane mapping module is adapted to determine the set of one or more 2D slices based on fitting planes of maximum saliency through the saliency map (see Zhang et al. [0042], [0044], [0052], [0054]-[0055]).
Regarding claim 9, Zhang et al. (‘318) in view of Schneider et al. (‘858) teach the method of claim 1, wherein the control instructions are adapted to cause the ultrasound acquisition system to interleave acquisition of the set of one or more 2D slices with any other acquisition sequence which the ultrasound acquisition system is currently performing (see Zhang et al. [0042], [0044], [0052], [0054]-[0055]; and Schneider et al. [0025]-[0026]).
Regarding claim 11, Zhang et al. (‘318) in view of Schneider et al. (‘858) teach the method of claim 1, wherein the control instructions are adapted to control acquisition of 2D slices which are of higher spatial resolution than the input 3D ultrasound image data (see Zhang et al. [0042], [0044], [0052], [0054]-[0055]; and Schneider et al. [0025]-[0026]).
Regarding claim 12, Zhang et al. (‘318) in view of Schneider et al. (‘858) teach the method of claim 1, wherein the method further comprises receiving the acquired set of one or more 2D slices; and controlling a user interface to generate a visual output representative thereof (see Zhang et al. [0042]; and Schneider et al. [0025]-[0026]).
Regarding claim 13, Zhang et al. (‘318) in view of Schneider et al. (‘858) teach the method of claim 1, wherein the method further comprises, after determining the set of 2D slices, controlling a user interface to generate a user-perceptible prompt requesting approval to acquire the set of 2D slices, and wherein the generating of the control instructions is performed only responsive to receipt from the user interface of a user input indicative of approval (see Zhang et al. [0042]; and Schneider et al. [0025]-[0026]).
Regarding claim 14, Zhang et al. (‘318) in view of Schneider et al. (‘858) teach a computer program product comprising code means configured, when run on a processor which is operatively coupled with an ultrasound acquisition system, to cause the processor to perform a method in accordance with claim 1 (see Zhang et al. [0039], [0042]-[0043], [0052], [0054]-[0055]; and Schneider et al. [0025]-[0026]).
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (US 2014/0039318 A1) in view of Schneider et al. (US 2019/0059858 A1), as applied to claim 1 above, and further in view of Hope Simpson et al. (US 2019/0336108 A1).
Regarding claim 10, Zhang et al. (‘318) in view of Schneider et al. (‘858) teach the method of claim 1 as cited above but fail to explicitly teach, wherein the disease detection module comprises a convolutional neural network (CNN). However, Hope Simpson et al. (‘108) from the same field of endeavor do teach a convolutional neural network (CNN) (see [0036]). It would be obvious to one of ordinary skill in the art to modify the invention of claim 1 with the features of Hope Simpson et al. for the benefit of improved object detection.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-14 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARK REMALY whose telephone number is (571)270-1491. The examiner can normally be reached Mon - Fri 9:00 - 6:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Christopher Koharski can be reached at (571) 272-7230. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MARK D REMALY/Primary Examiner, Art Unit 3797
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