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 .
Drawings
The drawings are objected to because FIG. 1 shows blank boxes without any description. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
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.
Claim(s) 1, 3 and 8-12 is/are rejected under 35 U.S.C. 103 as being unpatentable over D1 (U.S. PG-PUB NO. 2022/0296081) view of D2 (U.S. PG-PUB NO. 2020/0311431), D3 (U.S. PG-PUB NO. 2007/0071298) and further in view of D4 (U.S. PG-PUB NO. 2023/0070514).
-Regarding claim 1, D1 discloses a method for detecting polyps from a video sequence comprising a plurality of images (polyp detection in videos from colonoscopy procedures, [0128]), said method comprising the following steps: a) an extraction of regions of interest (ROI) likely to contain a polyp (Methods 1, 2 and 3 were developed and used for polyp detection in videos from colonoscopy procedures, [0128]); b) a description of said regions of interest with at least one predefined descriptor, advantageously with at least one texture descriptor and at least one luminance descriptor (feature 1 may be color expressed by the RGB color model as a triplet of numerical values for red, green and blue with each component varying from zero to a defined maximum value, e.g. 255, [0083]; Edge-Histogram, [0064]); c) a classification of said regions of interest according to the following rules: o if said region of interest is considered as containing a polyp by means of said at least one descriptor, it is classified in a first class, o if said region of interest is considered as not containing any polyp, by means of said at least one descriptor, it is classified in a second class (a trained classifier is applied to each time image for performing (multi-class) classification, wherein the trained classifier determines the detection scores that indicate the likelihoods that the respective time image contains one or more of said anatomical structures, [0069]; in response to the determination that a detection score for a class in the time image is higher than the learned detection threshold, the classification of the time image by the trained classifier is output in real-time, [0074]); e) for each of said successive images, a repetition of step b) and of step c) for said regions of interests that are subject of the follow-up (visual features are extracted (depicted by the arrows in the drawing) from frames within the sliding window for each of its positions and time images 340 to 343 are generated, one for each position of the sliding window, [0082]).
D1 is silent to teaching that characterized in that said method further comprises the following steps: d) a follow-up, by a motion estimation technique, of any region of interest belonging to the first class from a given image and on successive images following said given image; and f) an aggregation of same regions of interest on said images called first aggregation, said first aggregation consisting of maintaining as a region of interest belonging to the first class on a given image, a region of interest also classified in the first class for each successive image. However, the claimed limitation is well known in the art as evidenced by D2.
In the same field of endeavor, D2 teaches characterized in that said method further comprises the following steps: d) a follow-up, by a motion estimation technique, of any region of interest belonging to the first class from a given image and on successive images following said given image (Step 8075 may be preceded by or may include generating or receiving location information indicative of a location of each region of interest within each image, [0355]; The motion of the various regions of interest may be calculated by comparing the location information related to different images. The movement information may take into account the different in the acquisition time of the images, [0372]); and f) an aggregation of same regions of interest on said images called first aggregation, said first aggregation consisting of maintaining as a region of interest belonging to the first class on a given image, a region of interest also classified in the first class for each successive image (Step 8078 may include linking between first identifiers that identify the first group of regions of interest, [0357]).
Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to combine the teaching of D1 with the teaching of D2 in order to follow a temporal-tracking technique to improve a similar video detection method.
The combination of D1 and D2 is silent to teaching that said extraction consisting of determining circular or elliptical shapes within said images. However, the claimed limitation is well known in the art as evidenced by D3.
In the same field of endeavor, D3 teaches said extraction consisting of determining circular or elliptical shapes within said images (m is the magnitude of a gradient at location y. r is the radial distance from y to x. θ is the angle between the gradient at the location y and a ray from x to y, [0034]).
Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to combine the teaching of the combination of D1 and D2 with the teaching of D3 in order to localize the round polyp candidates before description/classification – applying a known shape-based polyp-candidate technique to improve a similar polyp-detection method (KSR).
The combination of D1, D2 and D3 is silent to teaching that g) an aggregation of images called second aggregation, said second aggregation consisting of maintaining as a region of interest on any image comprised between a first image and a second image, a region of interest appearing for the first time on said first image and for the last time on said second image. However, the claimed limitation is well known in the art as evidenced by D4.
In the same field of endeavor, D4 teaches g) an aggregation of images called second aggregation, said second aggregation consisting of maintaining as a region of interest on any image comprised between a first image and a second image, a region of interest appearing for the first time on said first image and for the last time on said second image (objects that are removed from the scene in one or more frames may be re-identified (with a previously-assigned identifier) and tracked (using a bounding box and/or its content) when they reappear within the scene, [0015]; motion infilling is performed for one or more of the tracked objects within the video. In one embodiment, one or more missing portions (e.g., missing information) may exist for one or more tracked objects within one or more frames of the video, [0020]; the predicted pose and shape data may be used to fill in the missing portions of the object within the predetermined frame of the video, [0022]).
Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to combine the teaching of the combination of D1, D2 and D3 with the teaching of D4 in order to maintain the polyp ROI on the images between its first and last appearance – recovering frames in which it is missing (occluded/out of scene) between its first and last appearance.
-Regarding claim 3, the combination further discloses several predetermined descriptors are chosen for step b) among which descriptors related to both the texture and the luminosity (D1, feature 1 may be color expressed by the RGB color model as a triplet of numerical values for red, green and blue with each component varying from zero to a defined maximum value, e.g. 255, [0083]).
-Regarding claim 8, the combination further discloses step e) as well as step f) are carried out with a temporal depth equal or greater than 3 images (D1, the sliding window includes 2, 3, 4, 5, 6 or more frames, [0056]).
-Regarding claim 9, the combination further discloses step g) is carried out with a temporal depth equal or greater than 10 images (D4, videos captured by dynamic cameras often contain severe and long-term occlusions of humans, [0099]).
-Regarding claim 10, the combination further discloses a device comprising: a means for acquiring a video sequence (D1, CCD camera, [0086]), and a processor or a plurality of processors to carry out, from said video sequence (D1, processing system, [0089]), the method according to claim 1.
-Regarding claim 11, the combination further discloses said device is an endoscopic capsule (D1, swallowable device (e.g. a capsule), [0087]).
-Regarding claim 12, the combination further discloses said device is affixed or integrated in an endoscope (D1, the system 400 is physically connected to the endoscope system 410, [0104]).
Allowable Subject Matter
Claims 2 and 4-7 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
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PING Y HSIEH whose telephone number is (571)270-3011. The examiner can normally be reached Monday-Friday, 9am-4pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jennifer Mehmood can be reached at (571) 272-2976. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/PING Y HSIEH/ Primary Examiner, Art Unit 2664
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