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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 02/14/2024 is/are compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Office Action Summary
Claim(s) 1-6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wiese et al (US 2020/0234404 A1) in view of Shi et al (US 2013/0094748 A1).
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.
Claim(s) 1-6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wiese et al (US 2020/0234404 A1) in view of Shi et al (US 2013/0094748 A1).
Regarding claim(s) 1, 5, and 6, Wiese teaches a non-transitory computer-readable storage medium, including instructions that when executed by a computer (Figure 3; and Paragraph [0050]: “An integrated or external computer processor (not shown) may also be considered a part of the scanning system”), cause the computer to:
(S1) determine a jaw arch form as a model-based prior knowledge about the anatomy of a patient based on one or more previous panoramic images or 3D images or optical 3D scans of the patient (Paragraph [0014] – Paragraph [0016]: “generating a panoramic image of a patient […] obtaining a digital 3D surface representation of at least a part of the patient's teeth […] obtained digital 3D surface representation to define a customized path following the arch form of the patient's teeth”);
(S2) determine a patient-specific x-ray device imaging trajectory for the panoramic image of the patient to be produced by using the said model-based prior knowledge so that the determined jaw arch from, and in particular a position of teeth thereof is optimally exposed and imaged (Paragraph [0016] – Paragraph [0017]: “using the obtained digital 3D surface representation to define a customized path following the arch form of the patient's teeth; obtaining a plurality of x-ray images of at least a part of one of the patient's jaws and/or teeth”; and Paragraph [0033]: “the position of the patient is determined using positioning lasers, it is possible to correlate the position of the patient during the x-ray imaging with the digital 3D surface representation”);
(S3) perform an imaging on the basis of the determined patient-specific x-ray device imaging trajectory to acquire imaging data (Paragraph [0056]: “During the scanning of the patient, thousands of narrow x-ray images are taken of the patient from various angles”);
(S4) adjust reconstruction (Paragraph [0056]: “thousands of narrow x-ray images are taken of the patient from various angles […] a trajectory in space is defined, that defines the average TMJ and/or toothline […] a line in 3D from the tube through a specific pixel in the panoramic image […] will be counted for the given pixel. In this way, every pixel of the final reconstructed panoramic image is the sum of up to hundreds or thousands of individual measurements taken from different angles […] the patient specific path can be used in combination with the post-processing above or alone, to make the actual physical trajectory of the x-ray system during imaging move according to the patient specific path”);
(S7) display the reconstructed panoramic image (Figure 6; Figure 7; Paragraph [0057]: “FIG. 6 shows a panoramic image 601 resulting from using a suboptimal path 602 during the reconstruction”; and Paragraph [0058]: “FIG. 7 shows a panoramic image 701 resulting from using a more optimal path 702 during the reconstruction”).
Wiese fails to teach (S4) adjust reconstruction parameters of the x-ray device according to the determined patient- specific x-ray device imaging trajectory; (S5) determine a patient-specific focal curve for the panoramic image of the patient to be produced by using the said model-based prior knowledge so that the determined jaw arch form, and in particular the position of the teeth therein is optimally reconstructed; and (S6) reconstruct the panoramic image using the acquired imaging data, the adjusted reconstruction parameters including the determined patient-specific focal curve, and a layer to be imaged which overlaps with the determined jaw arch form, wherein the patient-specific focal curve lies within said layer to be imaged.
However, Shi teaches (S4) adjust reconstruction parameters of the x-ray device according to the determined patient- specific x-ray device imaging trajectory (Paragraph [0050]: “The direction of the normal vector is from the inside of the central curve to the outside of the central curve. Ray summation is performed along the normal vector […] the default path is 14 mm in length and with the point of the central curve as the center. Based on empirical evidence, this 14 mm thickness is a typical thickness of jaw arches”);
(S5) determine a patient-specific focal curve for the panoramic image of the patient to be produced by using the said model-based prior knowledge so that the determined jaw arch form, and in particular the position of the teeth therein is optimally reconstructed (Figure 7; and Paragraph [0041] – Paragraph [0044]: “the inner and outer boundaries of the jaw arch (or inner and outer arches) are processed so to produce an outer curve, inner curve, and central curve for each slice. The inner and outer boundaries are smoothed in three-dimensional shells formed by the boundaries themselves […] a master arch detection process is performed. One goal of the master arch detection process is to find an arch (central curve) on an axial slice which has the appearance of a solid shape”); and
(S6) reconstruct the panoramic image using the acquired imaging data, the adjusted reconstruction parameters including the determined patient-specific focal curve, and a layer to be imaged which overlaps with the determined jaw arch form, wherein the patient-specific focal curve lies within said layer to be imaged (Paragraph [0050]: “The direction of the normal vector is from the inside of the central curve to the outside of the central curve. Ray summation is performed along the normal vector […] the default path is 14 mm in length and with the point of the central curve as the center. Based on empirical evidence, this 14 mm thickness is a typical thickness of jaw arches”; and Paragraph [0051]: “For each point on the central curve, one pixel is identified and each central curve represents one horizontal line on the panoramic image. The slices form the entire panoramic image. However, the central curve on the separation slice is employed for all the slices above the separation level”).
Wiese teaches a method of producing a panoramic image using patient-specific anatomical information, including obtaining patient dental geometry and determining a customized, patient-specific x-ray imaging trajectory that follows the dental arch to optimize exposure and imaging of the teeth, and performing imaging and reconstruction based on the customized trajectory. Shi teaches segmenting volumetric x-ray image data into slices, generating jaw-arch curves including a central curve and a master arch, and reconstructing a panoramic image using a defined image layer of predetermined thickness centered on the jaw-arch central curve.
It would have been obvious to a person of ordinary skill in the art at the time of the invention to incorporate Shi’s jaw-arch curve determination and curve-centered, layer-based reconstruction techniques into the patient-specific panoramic imaging method of Wiese in order to improve reconstruction accuracy and image quality by ensuring that the region corresponding to the dental arch is optimally reconstructed, thereby resulting in a method that includes determining a patient-specific focal curve and reconstructing the panoramic image using an image layer overlapping the jaw arch with the focal curve lying within the layer. This motivation for the combination of Wiese and Shi is supported by KSR exemplary rationale (G) Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention. MPEP 2141 (III).
Regarding claim(s) 2, Wiese as modified by Shi teaches the method of claim 1, where Shi teaches wherein the jaw arch form is determined using a neural network, wherein the neural network is trained by data pairs each comprising a 3D volume and the jaw arch form marked therein, or comprising an optical 3D scan and the jaw arch form marked therein (Figure 2 – Figure 5; Paragraph [0021]: “received from the scanner 12 (a volumetric x-ray image data set or a portion of a volumetric data set) […] the first overall step in the process includes jaw segmentation and visualization […] The curve fitting generates three curves for each slice: an outer curve 74, inner curve 76, and central curve 78. These steps are performed by an automatic jaw arch detection process. As shown in FIG. 4, the curves 74-78 are used in a master arch detection process (step 85), which generates a master arch 90 […]”; and Paragraph [0041] – Paragraph [0044]: “the inner and outer boundaries of the jaw arch (or inner and outer arches) are processed so to produce an outer curve, inner curve, and central curve for each slice. The inner and outer boundaries are smoothed in three-dimensional shells formed by the boundaries themselves […] a master arch detection process is performed. One goal of the master arch detection process is to find an arch (central curve) on an axial slice which has the appearance of a solid shape”).
Regarding claim(s) 3, Wiese as modified by Shi teaches the method according to claim 2, where Shi teaches wherein the jaw arch form is marked manually or automatically by image processing while taking into account the anatomical features of the patient (Figure 2 – Figure 5; Paragraph [0021]: “received from the scanner 12 (a volumetric x-ray image data set or a portion of a volumetric data set) […] the first overall step in the process includes jaw segmentation and visualization […] The curve fitting generates three curves for each slice: an outer curve 74, inner curve 76, and central curve 78. These steps are performed by an automatic jaw arch detection process. As shown in FIG. 4, the curves 74-78 are used in a master arch detection process (step 85), which generates a master arch 90 […]”; and Paragraph [0041] – Paragraph [0044]: “the inner and outer boundaries of the jaw arch (or inner and outer arches) are processed so to produce an outer curve, inner curve, and central curve for each slice. The inner and outer boundaries are smoothed in three-dimensional shells formed by the boundaries themselves […] a master arch detection process is performed. One goal of the master arch detection process is to find an arch (central curve) on an axial slice which has the appearance of a solid shape […] the slice containing a predetermined anatomical feature is the slice from which to determine the master arch”).
Regarding claim(s) 4, Wiese as modified by Shi teaches the method according to claim 1, where Shi teaches wherein during the reconstruction in step (S6), the overlap of the jaw arch form and the layer to be imaged is maximal (Figure 2 – Figure 5; Paragraph [0021]: “received from the scanner 12 (a volumetric x-ray image data set or a portion of a volumetric data set) […] the first overall step in the process includes jaw segmentation and visualization […] The curve fitting generates three curves for each slice: an outer curve 74, inner curve 76, and central curve 78. These steps are performed by an automatic jaw arch detection process. As shown in FIG. 4, the curves 74-78 are used in a master arch detection process (step 85), which generates a master arch 90 […]”; Paragraph [0041] – Paragraph [0044]: “the inner and outer boundaries of the jaw arch (or inner and outer arches) are processed so to produce an outer curve, inner curve, and central curve for each slice. The inner and outer boundaries are smoothed in three-dimensional shells formed by the boundaries themselves […] a master arch detection process is performed. One goal of the master arch detection process is to find an arch (central curve) on an axial slice which has the appearance of a solid shape”; Paragraph [0050]: “The direction of the normal vector is from the inside of the central curve to the outside of the central curve. Ray summation is performed along the normal vector […] the default path is 14 mm in length and with the point of the central curve as the center. Based on empirical evidence, this 14 mm thickness is a typical thickness of jaw arches”; and Paragraph [0051]: “For each point on the central curve, one pixel is identified and each central curve represents one horizontal line on the panoramic image. The slices form the entire panoramic image. However, the central curve on the separation slice is employed for all the slices above the separation level”).
Relevant Prior Art Directed to State of Art
Han et al (US 2024/0169607 A1) are relevant prior art not applied in the rejection(s) above. Han discloses an X-ray imaging apparatus comprising: an X-ray generator for emitting X-rays toward parts of an object to be imaged; an X-ray sensor for receiving the X-rays and obtaining projection image data for the parts of the object to be imaged; a driving part for moving the X-ray generator and the X-ray sensor along at least one partial section of the object to be imaged and causing the X-ray sensor to obtain a plurality of pieces of projection image data for the at least one partial section; and an image processor for obtaining a plurality of pieces of partial projection image data corresponding to partial areas of the X-ray sensor from the plurality of pieces of projection image data, and reconstructing tomographic images of the at least one partial section by using the plurality of pieces of partial projection image data.
Eichner et al (US 2021/0407159 A1) are relevant prior art not applied in the rejection(s) above. Eichner discloses Device for editing a panoramic radiography image of an examination object generated by a panoramic X-ray machine, comprising: an input interface for receiving the panoramic radiography image as well as reconstruction data of the panoramic radiography image, the reconstruction data including information on a course of projection lines of the panoramic radiography image between an X-ray source and an X-ray detector of the panoramic X-ray machine as well as information on an image surface of the panoramic radiography image; an evaluation unit for evaluating the reconstruction data and for determining, on the basis of one of the projection lines with two intersection points with the image surface, an image section of the panoramic radiography image that has been generated; an image editing unit for editing the panoramic radiography image based on the determined image section; and an output unit for outputting the edited panoramic radiography image.
Conclusion
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/JONGBONG NAH/Examiner, Art Unit 2674
/ONEAL R MISTRY/ Supervisory Patent Examiner, Art Unit 2674