The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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 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.
DETAILED ACTION
Election/Restrictions
Applicant’s election without traverse of Species I, claims 1-5, 7-11, and 13-17, in the reply filed on May 11, 2026 is acknowledged.
Claims 6, 12, and 18 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected species, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on May 11, 2026.
Specification
The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant's cooperation is requested in correcting any errors of which applicant may become aware in the specification.
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.
(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.
Claims 1-5,7-11 and 13-17 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Rittscher et al. (U.S. Publication 2022/0207728, hereinafter “Rittscher”).
As to Claim 1, Rittscher discloses a system (1) in [0054]-[0055] for image inpainting of in-vivo images, the system comprising:
at least one processor (10) in [0058]; and
at least one memory (11) in [0057] storing instructions which, when executed by the at least one processor, cause the system to:
access an in-vivo image “images” and “pixels” in [0113], [0137], [0162], and [0167] of a portion of a gastrointestinal tract, the in-vivo image comprising image regions to be reconstructed,
process the in-vivo image by a trained image inpainting deep learning model “model” in [0162] and [0167] to provide a reconstructed in-vivo image, and
provide the reconstructed in-vivo image to a device for viewing by a medical professional via (27) in [0110].
As to Claim 2, Rittscher discloses the system of claim 1, wherein the image regions to be reconstructed comprise regions where gastrointestinal content blocked a view of gastrointestinal tract tissue as described in [0113], [0137], [0162], and [0167].
As to Claim 3, Rittscher discloses the system of claim 2, wherein the reconstructed in-vivo image comprises regions of reconstructed gastrointestinal tract tissue for the regions where the gastrointestinal content blocked the view of the gastrointestinal tract tissue as described in [0113], [0137], [0162], and [0167].
As to Claim 4, Rittscher discloses the system of claim 3, wherein the portion of the gastrointestinal tract comprises a small bowel, and
wherein the regions of reconstructed gastrointestinal tract issue comprise small bowel mucosa (the gastroesophageal anatomy being a portion of gastrointestinal tract in a human).
As to Claim 5, Rittscher discloses the system of claim 2, wherein the image regions to be reconstructed are indicated by a medical professional in [0145].
As to Claim 7, Rittscher discloses a method for image inpainting of in-vivo images, the method comprising:
accessing an in-vivo image “images” and “pixels” in [0113], [0137], [0162], and [0167] of a portion of a gastrointestinal tract, the in-vivo image comprising image regions to be reconstructed;
processing via (10) in [0058] the in-vivo image by a trained image inpainting deep learning model “model” in [0162] and [0167] to provide a reconstructed in-vivo image; and
providing the reconstructed in-vivo image to a device for viewing by a medical professional via (27) in [0110].
As to Claim 8, Rittscher discloses the method of claim 7, wherein the image regions to be reconstructed comprise regions where gastrointestinal content blocked a view of gastrointestinal tract tissue as described in [0139], [0164], and [0169].
As to Claim 9, Rittscher discloses the method of claim 8, wherein the reconstructed in-vivo image comprises regions of reconstructed gastrointestinal tract tissue for the regions where the gastrointestinal content blocked the view of the gastrointestinal tract tissue as described in [0139], [0164], and [0169].
As to Claim 10, Rittscher discloses the method of claim 9, wherein the portion of the gastrointestinal tract comprises a small bowel, and
wherein the regions of reconstructed gastrointestinal tract issue comprise small bowel mucosa (the gastroesophageal anatomy being a portion of gastrointestinal tract in a human).
As to Claim 11, Rittscher discloses the method of claim 8, wherein the image regions to be reconstructed are indicated by a medical professional in [0145].
As to Claim 13, Rittscher discloses a processor-readable medium (11) in [0057] storing instructions which, when executed by at least one processor (10) in [0058] of a system (1) in [0054]-[0055], cause the system to:
access an in-vivo image “images” and “pixels” in [0113], [0137], [0162], and [0167] of a portion of a gastrointestinal tract, the in-vivo image comprising image regions to be reconstructed;
process the in-vivo image by a trained image inpainting deep learning model “model” in [0162] and [0167] to provide a reconstructed in-vivo image; and
provide the reconstructed in-vivo image to a device for viewing by a medical professional via (27) in [0110].
As to Claim 14, Rittscher discloses the processor-readable medium of claim 13, wherein the image regions to be reconstructed comprise regions where gastrointestinal content blocked a view of gastrointestinal tract tissue as described in [0113], [0137], [0162], and [0167].
As to Claim 15, Rittscher discloses the processor-readable medium of claim 14, wherein the reconstructed in-vivo image comprises regions of reconstructed gastrointestinal tract tissue for the regions where the gastrointestinal content blocked the view of the gastrointestinal tract tissue as described in [0113], [0137], [0162], and [0167].
As to Claim 16, Rittscher discloses the processor-readable medium of claim 15, wherein the portion of the gastrointestinal tract comprises a small bowel, and
wherein the regions of reconstructed gastrointestinal tract issue comprise small bowel mucosa (the gastroesophageal anatomy being a portion of gastrointestinal tract in a human).
As to Claim 17, Rittscher discloses the processor-readable medium of claim 14, wherein the image regions to be reconstructed are indicated by a medical professional in [0145].
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See the enclosed 892 form. 20250082416 ([0087]), 20230285621 ([0052]), 20210202063 ([0151] and [0167]), and 20160307303 ([0067]) are cited to show image inpainting. The prior art should be considered to define the claims over the art of record.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WILLIAM B CHOU whose telephone number is (571) 270-3367. The examiner can normally be reached on M-F 9 am - 6 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Michael Carey can be reached on (571) 270-7235. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/WILLIAM CHOU/
Examiner, Art Unit 3795
/MICHAEL J CAREY/Supervisory Patent Examiner, Art Unit 3795
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