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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
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) 1-4, 7-9, 15-17 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 2014/0094689 to Cohen et al., hereinafter, “Cohen” in view of US 2012/0099774 A1 to Akcakaya et al., hereinafter “Akcakaya”.
Claim 1. (new) Cohen teaches A method, comprising: [Abstract]
receiving, by one or more processors, a set of extraluminal image frames of
extraluminal blood vessels [0031] at least one processor configured to receive from the one or more extraluminal imaging devices: [0032] a first set of extraluminal images of the lumen
detecting, by the one or more processors, one or more anatomic features on one or more frames of the set of extraluminal image frames; [0480] Examples of the anatomical structure to which the aforementioned co-registration of extraluminal and endoluminal images may be applied include a coronary vessel, a coronary lesion, a vessel, a vascular lesion, a lumen, a luminal lesion, and/or a valve
Cohen fails to explicitly teach clustering, by the one or more processors based on the detected one or more anatomic features. Akcakaya, in the field of analyzing medical images teaches clustering, by the one or more processors based on the detected one or more anatomic features, one or more extraluminal image frames of the set, FIG. 1 element 106
[0008] … an acquired image data set. An improved compressed sensing reconstruction method is provided for the reconstruction of target images from undersampled image data
[0037] To utilize low-rankedness of clusters, each N.sub.b.times.N.sub.b image block in the similarity clusters… each image block has similar anatomical features
wherein a cluster corresponds to an anatomic feature detected in two or more extraluminal image frames of the set; [0037] To utilize low-rankedness of clusters, each N.sub.b.times.N.sub.b image block in the similarity clusters… each image block has similar anatomical features
and performing, by the one or more processors, interframe registration of extraluminal image frames using the clusters of the one or more extraluminal image frames. [0028] if more than N.sub.cluster image blocks are matched to the reference image block, only those blocks with the highest degree of similarity in the cluster are considered for further processing. Examiner understands interframe registration to be aligning/matching the cluster image blocks to another cluster image block.
[0037] To utilize low-rankedness of clusters, each N.sub.b.times.N.sub.b image block in the similarity clusters… each image block has similar anatomical features
Thus, before the effective filing date of the present application, it would have been obvious to one of ordinary skill in the art to combine the teachings of Cohen with the teachings of Akcakaya [0007] to provide a method for magnetic resonance image reconstruction that includes the scan time reduction benefits of CS techniques, but that is robust to inter- and intra-patient variabilities without the need for separately acquired training data. Rationale applies to claims 2-4, 7-9, 15-17 and 20.
Claim 2. (new) Cohen teaches The method of claim 1, wherein the one or more anatomic features comprise at least one of a bifurcation, a bend, angles with respect to a vessel centerline, a normalized arc length of the bifurcation, an average image intensity along bifurcations branches, bifurcation scale, bifurcation width, absolute angle on the one or more frames of the set, or bifurcation lumen shape. [0330] features include anatomical features, such as bifurcations, lesions, calcifications, etc
Claim 3. (new) Cohen teaches The method of claim 1, wherein detecting the one or more anatomic features further comprises applying, by the one or more processors, one or more filters to the one or frames of the set. [0341] Identifying features using image processing techniques (e.g., detecting vesselness, using a hessian filter, using corner detection, using directional filters, etc.)
Claim 4. (new) Cohen teaches The method of claim 3, wherein the one or more filters includes at least one of a Hessian based filter, a shadow removal filter, a rib filter, a temporal filter, or a vessel crossing filter. [0341] Identifying features using image processing techniques (e.g., detecting vesselness, using a hessian filter, using corner detection, using directional filters, etc.)
Claim 7. (new) Akcakaya teaches The method of claim 1, further comprising generating, by the one or more processors, one or more distance measurements between two or more clusters. [0025-0026] measures the distance between clusters
Claim 8. (new) Akcakaya teaches The method of claim 7, wherein a distance metric of the one or more distance measurements is a Euclidean metric. Akcakaya [0025-0026] distance measure of two blocks (clusters) of a voxel location.
Claim 9. (new) Akcakaya teaches The method of claim 7, further comprising validating, by the one or more processors, whether the one or more detected anatomic features are present in two or more extraluminal image frames. Akcakaya [0028] if more than N.sub.cluster image blocks are matched to the reference image block, only those blocks with the highest degree of similarity in the cluster are considered for further processing. Examiner interprets matching using a threshold of similarity to be validating.
Claim 15. (new) Reviewed and analyzed in the same way as claim 1. See the above analysis and rationale.
Claim 16. (new) Reviewed and analyzed in the same way as claim 3. See the above analysis and rationale.
Claim 17. (new) Reviewed and analyzed in the same way as claim 7. See the above analysis and rationale.
Claim 20. (new) Reviewed and analyzed in the same way as claim 1. See the above analysis and rationale.
Claim(s) 5-6, 14 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 2014/0094689 to Cohen et al., hereinafter, “Cohen” in view of US 2012/0099774 A1 to Akcakaya et al., hereinafter “Akcakaya” and in further view of US 2014/0270436 A1 to Dascal et al., hereinafter, “Dascal”.
Claim 5. (new) Cohen fails to explicitly teach generating, by the one or more processors a plurality of centerlines from imaged regions of blood vessels. Dascal, in the field of analyzing medical images, teaches the method of claim 1, further comprising: generating, by the one or more processors a plurality of centerlines from imaged regions of blood vessels; [0024] generating a vessel centerline for the plurality of frames of angiography image data… tracking…along one or more vessel centerlines
generating by the one or more processors, a binary image for a plurality of extraluminal image frames of the set of extraluminal image frames for which centerlines have been generated; [0122] For each angiography image, a set of preprocessing steps is applied to create a binary map
and generating, by the one or more processors, a skeleton image frame for each extraluminal image frame of the plurality of extraluminal image frames using the binary images of each such extraluminal image frame [0124] a distance map is a tool that is used to determine the vessel skeleton from the binary map
[0128] A binary image generated from the Hessian image can be used to generate skeletons in the angiography image as shown in FIG. 7B
and a centerline generated from blood vessel regions imaged in each such extraluminal image frame. [0127] skeletons can be used for detecting and generating a smooth vessel centerline
Thus, before the effective filing date of the present application, it would have been obvious to one of ordinary skill in the art to combine the teachings of Cohen with the teachings of Dascal [0005] to alleviate challenges regarding real time co-registration of intravascular image data and angiography image data.
Claim 6. (new) Cohen fails to explicitly teach anatomic features are detected one or more anatomic features are detected on one or more frames of a group of skeleton image frames. Dascal, in the field of analyzing medical images, teaches the method of claim 1, wherein the detected one or more anatomic features are detected on one or more frames of a group of skeleton image frames. Dascal [0127] generating skeletons to detect anatomic features like side branches and vessel geometry is implemented during preprocessing of the angiography images 160d. Skeletons can be used for detecting anatomical features
Thus, before the effective filing date of the present application, it would have been obvious to one of ordinary skill in the art to combine the teachings of Cohen with the teachings of Dascal [0005] to alleviate challenges regarding real time co-registration of intravascular image data and angiography image data.
Claim 14. (new) Cohen fails to explicitly teach a contrast cloud region in the set of extraluminal image frames. Dascal, in the field of analyzing medical images, teaches the method of claim 1, further comprising: identifying, by the one or more processors, a contrast cloud region in the set of extraluminal image frames; Dascal [0087] a cloud of contrast agent
and determining, by the one or more processors, a subset of the set of extraluminal image frames excluding regions of the set of extraluminal image frames that include the identified contrast cloud region. Dascal [0087] In some of the angiography frames, the marker bands appear blurred/faint due to fast pullback motion combined with fast cardiac motion.
Thus, before the effective filing date of the present application, it would have been obvious to one of ordinary skill in the art to combine the teachings of Cohen with the teachings of Dascal [0005] to alleviate challenges regarding real time co-registration of intravascular image data and angiography image data.
Claim 18. (new) Reviewed and analyzed in the same way as claim 5. See the above analysis and rationale.
Allowable Subject Matter
Claims 10-13 and 19 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
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US 2017/0140531 A1 to Dascal et al., US 2014/0094691 A1 to Steinberg et al.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DELOMIA L GILLIARD whose telephone number is (571)272-1681. The examiner can normally be reached 8am-5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, John Villecco can be reached at (571) 272-7319. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DELOMIA L GILLIARD/Primary Examiner, Art Unit 2661
