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 .
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.
Claims 1-11 and 13-14 are rejected under 35 U.S.C. 103 as being unpatentable over MEGHERBI et al (Radon Transform based Automatic Metal Artefacts Generation for 3D Threat Image Projection) in view of WANG et al (A Reference Architecture for Plausible Threat Image Projection (TIP) Within 3D X-ray Computed Tomography Volumes).
As per claim 1, Megherbi teaches the claimed “method for generating three-dimensional training data for a detection device for detecting alarm objects (AO) in items of luggage (L)”, comprising: “providing an object scan (OS) of an exempted alarm object (AO)” (Megherbi, 3. METAL ARTEFACTS GENERATION (MAG) USING RADON TRANSFORM - consistent metal artefacts are generated within the bag CT images which are a function of the scan orientation of the bag, the material of the bag content and the material of the inserted threat item), “providing a luggage scan (LS) of an item of luggage (L)” (Megherbi, Figure 7 – Clear bag CT Image), “combining the luggage scan (LS) and the object scan (OS) into a combination scan (CS)” (Megherbi, 3. METAL ARTEFACTS GENERATION (MAG) USING RADON TRANSFORM - The resulting reconstructed CT image corresponds to the original clear bag CT image corrupted by metal artefacts originating from the threat item metal part and the clear bag metal objects. The final 3D TIP image is obtained by combining the resulting CT image with the artefact free threat item CT image). It is noted that Megherbi does not explicitly teach “generating a three-dimensional combination volume (CV) from the combination scan (CS)” as claimed; however, Megherbi’s TIP image (Megherbi, Figure 9 – top, right TIP image) generated from the 3D CT images suggests a generated 3D combination volume from the scanned data (see also Wang, Abstract - we present an approach for 3D TIP in CT volumes targeting realistic and plausible threat object insertion within 3D CT baggage images. The proposed approach consists of dual threat (source) and baggage (target) volume segmentation, particle swarm optimization based insertion determination and metal artefact generation; Fig. 1. The framework of proposed 3D threat image projection approach; given a threat CT volume and a baggage CT volume as inputs, a plausible TIP is generated as the output of the approach with the pipeline consisting of four components: threat isolation, void determination, object insertion optimization and metal artefact generation) (Due to Wang’s relative position and orientation of the threat object, repeating the scans with different orientations of the luggage would increase the accuracy of the Optimizing Insertion Location and Orientation). Thus, it would have been obvious, in view of Wang, to configure Megherbi’s method as claimed by generating a 3D combination volume from the scanned data. The motivation is to enhance the visual detection of the threat object in 3D space.
Claim 2 adds into claim 1 “wherein the object scan (OS) and/or the luggage scan (LS) comprise individual scanning sections, in particular a sinogram” (Megherbi, Figure 7 – Sinogram domain) (Megherbi’s Radom transform is often called a sinogram because the Radon transform of an off-center point source is a sinusoid).
Claim 3 adds into claim 1 “wherein the object scan (OS) and the luggage scan (LS) are provided in the same or substantially identical form, in particular in the form of sinograms” (Megherbi, Figure 7 – Sinogram domain: Metal traces sinogram and Clear bag sinogram).
Claim 4 adds into claim 1 “wherein, during the luggage scan (LS), a detection of the boundaries of the item of luggage (L) is carried out, wherein the object scan (OS) with the alarm object (AO) within the detected boundaries of the item of luggage (L) is then combined with the luggage scan (LS)” (Wang, Figure 3 - To insert the segmented threat into a plausible location in the bag volume, we require to understand different regions in the bag volume. We propose a bag volume segmentation method to segment a bag volume into: outer-bag (background), bag content and inner-void regions) (Wang’s outer-bag region in blue defines the inner-bag region (foreground) enclosed by the boundaries). Thus, it would have been obvious, in view of Wang, to configure Megherbi’s method as claimed by defining the boundaries of the region (i.e., the luggage) potentially containing the threat object. The motivation is to reduce the processing time by limiting the monitoring region.
Claim 5 adds into claim 1 “wherein, during the luggage scan (LS), a detection of free spaces within the item of luggage (L) is carried out, wherein the object scan (OS) with the alarm object (AO) within the detected free space is then combined with the luggage scan (LS)” (Wang, III. AUTOMATIC 3D THREAT IMAGE PROJECTION, B. Void Determination - To segment a volume of bag into an inner-void region and a bag-content region, a simple thresholding is applied so that voxels of smaller values than the threshold form the inner-void region and others form the bag-content region; C. Object Insertion Optimization - To enable plausible and realistic TIP, it is important to find suitable locations in a benign bag and proper orientations of the threat object. Ideally, we tend to insert a threat object into the inner-void region in the bag volume). Thus, it would have been obvious, in view of Wang, to configure Megherbi’s method as claimed by defining the boundaries of the region (i.e., the inner-void region) potentially containing the threat object. The motivation is to reduce the processing time by limiting the monitoring region.
Claim 6 adds into claim 1 “wherein one the alarm object (AO) is positioned relative to the item of luggage (L) in that the object scan (OS) is offset in time” (Megherbi, 2. CT METAL ARTEFACTS - In Figures 3 and 4 we show an example of a scanned bag containing a threat object (e.g., gun) placed in different orientations. As can be seen, the generated artefacts in both scans are different. This is due to the fact that the size of the gun metal part that the X-rays have intersected is not the same because of the different orientation. Figure 3 and 4 demonstrate thus that the intensity of the metal artefacts and their direction depend on the direction of the scanned objects (bag)) (Due to the gun’s orientation, the detected gun-representations on different-in-time slices are shifted (i.e., offset in time)).
Claim 7 adds into claim 1 “wherein one a detection of areas with a material density above a specified limit value is carried out during the combination scan (CS), whereby the areas with a material density above the limit value are combined with an adjustment factor when generating the three-dimensional combination volume (CV)” (Megherbi, 2. CT METAL ARTEFACTS - Metal artefacts are caused by the presence of high density objects in the scan field of view; 4. EXPERIMENTAL RESULTS - Since in our work we are interested in metal artefacts generation in the TIP images we use guns as threat items as they are mostly made from metal) (Megherbi’s detected gun is based on the high density object’s property in which the metal artefacts, caused by the presence of high density objects in the scan field of view, needs adjustment on display).
Claim 8 adds into claim 1 “wherein one the object scan (OS) and/or the luggage scan (LS) are selected from a scans database” (Wang, III. AUTOMATIC 3D THREAT IMAGE PROJECTION - These threat objects of interest are prepared beforehand and scanned in a controlled condition (e.g. background voxels with lower values than threat object voxels) for easy segmentation). Thus, it would have been obvious, in view of Wang, to configure Megherbi’s method as claimed by preparing different possible visual representations of the threat object. The motivation is to increase the efficiency of determining the threat object based on its scanned information.
Claim 9 adds into claim 1 “wherein one at least providing the object scan (OS) and the luggage scan (LS), the combination of the object scan (OS) with the luggage scan (LS) and the generation of the three-dimensional combination volume (CV) are carried out several times” (Wang, Fig. 1. The framework of proposed 3D threat image projection approach; given a threat CT volume and a baggage CT volume as inputs, a plausible TIP is generated as the output of the approach with the pipeline consisting of four components: threat isolation, void determination, object insertion optimization and metal artefact generation) (Due to Wang’s relative position and orientation of the threat object within the luggage, repeating the scans with different orientations of the luggage would increase the accuracy of the Optimizing Insertion Location and Orientation). Thus, it would have been obvious, in view of Wang, to configure Megherbi’s method as claimed by repeating the scanning process of the luggage in different orientations. The motivation is to increase the efficiency of determining the threat object based on its scanned information.
Claim 10 adds into claim 1 “wherein the preceding claims, characterized in that the luggage scan (LS) is generated in a detection device on a real item of luggage (L)” (Wang, Fig. 7. Baggage volume segmentation results. Top row: original baggage CT volumes; bottom row: projection cost volume defined in Eq. (2) with the green color representing void regions and the red color representing regions having high projection cost). Thus, it would have been obvious, in view of Wang, to configure Megherbi’s method as claimed by generating the scanned luggage in a detection device. The motivation is to visually represent the luggage with potential threat object for monitoring.
Claims 11 and 14 claim a generation device and a computer program product based on the method of claims 1-10; therefore, they are rejected under a similar rationale.
Claim 13 adds into claim 11 “wherein the scans module (20) has a scans database (22) in which a large number of object scans (OS) and/or luggage scans (LS) are stored” (Wang, III. AUTOMATIC 3D THREAT IMAGE PROJECTION - These threat objects of interest are prepared beforehand and scanned in a controlled condition (e.g. background voxels with lower values than threat object voxels) for easy segmentation). Thus, it would have been obvious, in view of Wang, to configure Megherbi’s method as claimed by preparing different possible visual representations of the threat object. The motivation is to increase the efficiency of determining the threat object based on its scanned information.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 2 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
In claim 2, line 3, “in particular” is ambiguous. It is unclear if "in particular" is meant to pick out one item as a specific example, or if it is meant to imply only that item is relevant, creating a logical ambiguity.
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 14 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the “computer program product” can be a wave carrier embodying the signals.
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/PHU K NGUYEN/Primary Examiner, Art Unit 2616