DETAILED ACTION
Claims 1-20 are currently pending.
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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 11/04/2024 has been considered by the Examiner.
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.
Claims 1, 7-8, and 14-15 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Li (“AIVUS: Guidewire Artifacts Inpainting for Intravascular Ultrasound Imaging With United Spatiotemporal Aggregation Learning”).
Regarding claim 1, Li teaches:
A system comprising:
a memory configured to store instructions; (Li, page 686m Nvidia Tesla V100 GPU) and
one or more processors configured to execute the instructions to (Li, page 686m Nvidia Tesla V100 GPU) :
acquire a first medical image, of a region of interest of a subject, in which a medical instrument is present in the region of interest of the subject; (Li, page 685, However, the Type II dataset is collected without removing the device’s guidewire, which makes it closer to the real clinical scenario, and thus its panoptic information will be disrupted by guidewire artifacts)
determine a region of the first medical image corresponding to the medical instrument; (Li, page 682, The ultimate goal is to remove the interference of the guidewire artifacts and reveal the original morphological details lost in IVUS images… Specifically, image completion module Hc restore the input sequence frame by frame, and it has an encoder-decoder structure that comprised of stacked gated convolutional blocks to obtain the preliminary repair results)
generate a second medical image in which the medical instrument is absent using first medical image data of the first medical image external to the region and inpainted data internal to the region; (Li, page 682, The ultimate goal is to remove the interference of the guidewire artifacts and reveal the original morphological details lost in IVUS images. To simplify the task and restore high-fidelity original details, we case our work as a supervised learning-video inpainting problem. It takes the incomplete IVUS image sequence and the corresponding mask sequence as input. Finally, it generate the complete output sequence…and the outputs are expected to be consistent with the ground truth frames) and
display the second medical image. (Li, Figure 3, See outputs of the generator network)
Regarding claim 7, Li teaches:
The system of claim 1, wherein the first medical image depicts one or more medical instruments, and wherein the one or more medical instruments are absent in the second medical image. (Li, page 682, The ultimate goal is to remove the interference of the guidewire artifacts and reveal the original morphological details lost in IVUS images… Specifically, image completion module Hc restore the input sequence frame by frame, and it has an encoder-decoder structure that comprised of stacked gated convolutional blocks to obtain the preliminary repair results)
Regarding claim 8, Li teaches:
A method comprising:
acquiring a first medical image, of a region of interest of a subject, in which a medical instrument is present in the region of interest of the subject; (Li, page 685, However, the Type II dataset is collected without removing the device’s guidewire, which makes it closer to the real clinical scenario, and thus its panoptic information will be disrupted by guidewire artifacts)
determining a region of the first medical image corresponding to the medical instrument; (Li, page 682, The ultimate goal is to remove the interference of the guidewire artifacts and reveal the original morphological details lost in IVUS images… Specifically, image completion module Hc restore the input sequence frame by frame, and it has an encoder-decoder structure that comprised of stacked gated convolutional blocks to obtain the preliminary repair results)
generating a second medical image in which the medical instrument is absent using first medical image data of the first medical image external to the region and inpainted data internal to the region; (Li, page 682, The ultimate goal is to remove the interference of the guidewire artifacts and reveal the original morphological details lost in IVUS images. To simplify the task and restore high-fidelity original details, we case our work as a supervised learning-video inpainting problem. It takes the incomplete IVUS image sequence and the corresponding mask sequence as input. Finally, it generate the complete output sequence…and the outputs are expected to be consistent with the ground truth frames) and
displaying the second medical image. (Li, Figure 3, See outputs of the generator network)
Regarding claim 14, Li teaches:
The method of claim 8, wherein the generating the second medical image comprises generating the second medical image using an artificial intelligence model that is trained using first training images in which the medical instrument is absent, and second training images in which the medical instrument is present. (Li, page 682, The ultimate goal is to remove the interference of the guidewire artifacts and reveal the original morphological details lost in IVUS images… Specifically, image completion module Hc restore the input sequence frame by frame, and it has an encoder-decoder structure that comprised of stacked gated convolutional blocks to obtain the preliminary repair results)
Regarding claim 15, Li teaches:
A non-transitory computer-readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to: (Li, page 686m Nvidia Tesla V100 GPU) :
acquire a first medical image, of a region of interest of a subject, in which a medical instrument is present in the region of interest of the subject; (Li, page 685, However, the Type II dataset is collected without removing the device’s guidewire, which makes it closer to the real clinical scenario, and thus its panoptic information will be disrupted by guidewire artifacts)
determine a region of the first medical image corresponding to the medical instrument; (Li, page 682, The ultimate goal is to remove the interference of the guidewire artifacts and reveal the original morphological details lost in IVUS images… Specifically, image completion module Hc restore the input sequence frame by frame, and it has an encoder-decoder structure that comprised of stacked gated convolutional blocks to obtain the preliminary repair results)
generate a second medical image in which the medical instrument is absent using first medical image data of the first medical image external to the region and inpainted data internal to the region; (Li, page 682, The ultimate goal is to remove the interference of the guidewire artifacts and reveal the original morphological details lost in IVUS images. To simplify the task and restore high-fidelity original details, we case our work as a supervised learning-video inpainting problem. It takes the incomplete IVUS image sequence and the corresponding mask sequence as input. Finally, it generate the complete output sequence…and the outputs are expected to be consistent with the ground truth frames) and
display the second medical image. (Li, Figure 3, See outputs of the generator network)
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.
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.
Claims 5, 12, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Li as applied to claims 1, 8, and 15 above, and further in view of Gharaibeh (“Correction of metallic stent struts and guidewire shadows in intravascular optical coherence tomography images using conditional generative adversarial networks”).
Regarding claim 5, Li fails to teach:
determine a second region of the first medical image corresponding to a shadow the medical instrument; and
determine a second region of the first medical image corresponding to the shadow of the medical instrument,
wherein the generating the second medical image comprises generating the second medical image in which the medical instrument and the shadow of the medical instrument are absent using the first medical image data of the first medical image external to the first region and the second region and inpainted data internal to the first region and the second region.
Gharaibeh teaches:
The system of claim 1, wherein the region is a first region, and wherein the one or more processors are further configured to:
determine a second region of the first medical image corresponding to a shadow the medical instrument; (Gharaibeh, page 3 Section 2.3, To correct the stent strut shadows of a new post stent image, the stent structs detected and blocked and fed into the trained generator to produce the shadow free image)and
determine a second region of the first medical image corresponding to the shadow of the medical instrument, (Gharaibeh, page 3 Section 2.3, To correct the stent strut shadows of a new post stent image, the stent structs detected and blocked and fed into the trained generator to produce the shadow free image)
wherein the generating the second medical image comprises generating the second medical image in which the medical instrument and the shadow of the medical instrument are absent using the first medical image data of the first medical image external to the first region and the second region and inpainted data internal to the first region and the second region. (Gharaibeh, page 3 Section 2.3, To correct the stent strut shadows of a new post stent image, the stent structs detected and blocked and fed into the trained generator to produce the shadow free image)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to add the shadow detection of Gharaibeh to the artifact removal system of Li. The inventions lie in the same field of endeavor of artifact removal and Gharaibeh was known at the time of Li. The motivation for the combination is to improve visualization and analysis of medical images. See Gharaibeh Abstract.
Regarding claim 12, the combination of Li and Gharaibeh teaches:
The method of claim 8, wherein the region is a first region, and wherein the method further comprises:
determining a second region of the first medical image corresponding to a shadow the medical instrument; (Gharaibeh, page 3 Section 2.3, To correct the stent strut shadows of a new post stent image, the stent structs detected and blocked and fed into the trained generator to produce the shadow free image) and
determining a second region of the first medical image corresponding to the shadow of the medical instrument, (Gharaibeh, page 3 Section 2.3, To correct the stent strut shadows of a new post stent image, the stent structs detected and blocked and fed into the trained generator to produce the shadow free image)
wherein the generating the second medical image comprises generating the second medical image in which the medical instrument and the shadow of the medical instrument are absent using the first medical image data of the first medical image external to the first region and the second region and inpainted data internal to the first region and the second region. (Gharaibeh, page 3 Section 2.3, To correct the stent strut shadows of a new post stent image, the stent structs detected and blocked and fed into the trained generator to produce the shadow free image)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to add the shadow detection of Gharaibeh to the artifact removal system of Li. The inventions lie in the same field of endeavor of artifact removal and Gharaibeh was known at the time of Li. The motivation for the combination is to improve visualization and analysis of medical images. See Gharaibeh Abstract.
Regarding claim 19, the combination of Li and Gharaibeh teaches:
The non-transitory computer-readable medium of claim 15, wherein the region is a first region, and wherein the instructions further cause the one or more processors to:
determine a second region of the first medical image corresponding to a shadow the medical instrument; (Gharaibeh, page 3 Section 2.3, To correct the stent strut shadows of a new post stent image, the stent structs detected and blocked and fed into the trained generator to produce the shadow free image)
determine a second region of the first medical image corresponding to the shadow of the medical instrument, (Gharaibeh, page 3 Section 2.3, To correct the stent strut shadows of a new post stent image, the stent structs detected and blocked and fed into the trained generator to produce the shadow free image)
wherein the generating the second medical image comprises generating the second medical image in which the medical instrument and the shadow of the medical instrument are absent using the first medical image data of the first medical image external to the first region and the second region and inpainted data internal to the first region and the second region. (Gharaibeh, page 3 Section 2.3, To correct the stent strut shadows of a new post stent image, the stent structs detected and blocked and fed into the trained generator to produce the shadow free image)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to add the shadow detection of Gharaibeh to the artifact removal system of Li. The inventions lie in the same field of endeavor of artifact removal and Gharaibeh was known at the time of Li. The motivation for the combination is to improve visualization and analysis of medical images. See Gharaibeh Abstract.
Allowable Subject Matter
Claims 2-4, 6, 9-11, 13, 16-18, and 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
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure. Refer to PTO-892, Notice of References Cited for a listing of analogous art.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Molly K Wilburn whose telephone number is (571)272-3589. The examiner can normally be reached Monday-Friday 8am-4pm.
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/Molly Wilburn/Primary Examiner, Art Unit 2666
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