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 .
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.
Claims 1-7, and 9-10, are rejected under 35 U.S.C. 103 as being unpatentable over Elbaz (US 20190269485 A1; hereinafter referred to as Elbaz) in view of
Regarding Claim 1, Elbaz discloses a scanning system for determining a health-condition or a probability thereof based on scanning of an intraoral object (“Described herein are methods and apparatuses (e.g., devices and systems) that apply scans of both external and/or internal structures of teeth. These methods and apparatuses may generate and/or manipulate a model of a subject's oral cavity (e.g. teeth, jaw, palate, gingiva, etc.) that may include both surface topography and internal features (e.g., dentin, dental filling materials (including bases and linings), cracks and/or caries).” [0008]), the scanning system comprising:
a scanning device to scan the intraoral object (“Described herein are intraoral scanners for generating a three-dimensional (3D) model of a subject's intraoral region (e.g., tooth or teeth, gums, jaw, etc.)” [0230]. see Fig 1A for the scanning device wand 103), comprising:
an illumination-unit configured to illuminate the intraoral object with light (“The wand may include … one or more light sources 109, 110, 111…Although separate illumination sources are shown in FIG. 1B, in some variations a selectable light source may be used.” [0230]);
an image-sensor configured to record images of light from the illuminated intraoral object (“The wand may include one or more sensors 105 (e.g., cameras such as CMOS, CCDs, detectors, etc.) is emitted from a light source 203 and passed from one side of the tooth 201, and a sensor 205 (e.g., camera)” [0234], the purpose of camera 105 is to detect light from light sources 109,110,111; cameras 105 configuration can be changed to a specific angle as seen with camera 205 in [0234]);
and a controller configured to operate the image-sensor in a first acquisition-mode (“The intraoral scanner 101 may also include one or more processors, including linked processors or remote processors, for both controlling the wand 103 operation, including coordinating the scanning and in reviewing and processing the scanning and generation of the 3D model including surface and internal features.” [0232], “the system may alternate (switch) between scanning a portion of the tooth using a first modality 705 (e.g., surface scanning, using emitting light in an appropriate wavelength of range of wavelengths)” [0262]),
and configured to operate the image- sensor in a second acquisition-mode (“After an appropriate duration in the first modality, the method and apparatus may briefly switch to a second modality (e.g., a penetrative wavelength or range of wavelengths)” [0262]),
wherein the scanning device is configured to change between the first acquisition-mode and the second acquisition-mode (“after positioning the scanner adjacent to the target intraoral structure to be modeled 701, the wand may be moved over the target while the apparatus automatically scans 703 the target for both surface data and internal data. As part of this method, the system may alternate (switch) between scanning a portion of the tooth using a first modality 705 (e.g., surface scanning, using emitting light in an appropriate wavelength of range of wavelengths) to collect surface data such as 3D surface model data and scanning with a second modality 707 (e.g. a penetrative wavelength).” [0262], “The intraoral scanner 101 may also include one or more processors, including linked processors or remote processors, for both controlling the wand 103 operation, including coordinating the scanning and in reviewing and processing the scanning and generation of the 3D model including surface and internal features.” [0232], “a first light source 109 configured to emit light in a first spectral range for detection of surface features (e.g., visible light, monochromatic visible light, etc.; this light does not have to be visible light), a second color light source (e.g., white light between 400-700 nm, e.g., approximately 400-600 nm), and a third light source 111 configured to emit light in a second spectral range for detection of internal features within the tooth (e.g., by trans-illumination, small-angle penetration imaging” [0230]),
whereby the scanning device forms a first dataset of the intraoral object when in the first acquisition-mode (“a first light source 109 configured to emit light in a first spectral range for detection of surface features (e.g., visible light, monochromatic visible light, etc.; this light does not have to be visible light), a second color light source (e.g., white light between 400-700 nm, e.g., approximately 400-600 nm) [0230], ”For example, internal feature data such as penetration imaging data may be combined with surface data (surface imaging data) collected from the same or approximately the same position of an intraoral scanner so that the same coordinate system may be applied to both types of data.” [0247])
and whereby the scanning device forms a second dataset of the intraoral object when in the second acquisition-mode (“and a third light source 111 configured to emit light in a second spectral range for detection of internal features within the tooth (e.g., by trans-illumination, small-angle penetration imaging” [0230], ”For example, internal feature data such as penetration imaging data may be combined with surface data (surface imaging data) collected from the same or approximately the same position of an intraoral scanner so that the same coordinate system may be applied to both types of data.” [0247]);
a data processor (“The intraoral scanner 101 may also include one or more processors, including linked processors or remote processors, for both controlling the wand 103 operation, including coordinating the scanning and in reviewing and processing the scanning and generation of the 3D model including surface and internal features.” [0232]) configured to:
form, from the first dataset, a 3D-model of the intraoral object (“the one or more processors configured to: generate a three-dimensional (3D) surface model of at least a portion of a subject's tooth using light from a first spectral range” [0025]);
form, from the second dataset, a 2D-image of the intraoral object and/or further details of the 3D-model (“a plurality of images taken at the second spectral range showing internal structures.” [0025], “any of the apparatuses (e.g., systems, devices, software, etc.) and methods described herein may use the two-dimensional penetrative images along with position and/or orientation information about the scanner relative to the object being imaged (e.g., the teeth) to segment the 2D penetrative images to form a three-dimensional model of the teeth including an internal structure from within the teeth.” [0064];
apply, on the 2D-image and/or the 3D-model, a diagnostic algorithm to identify a diagnostic feature of the intraoral object (“In any of the methods and apparatuses configured to perform these methods described herein, the data may be analyzed automatically or manually by the system. In particular, the method and apparatuses described herein may include examining internal features and/or identifying features of interest, including crack and caries. Features may be recognized based on feature-recognition criterion (e.g., dark or light regions in the penetration images), pattern-recognition, machine learning, or the like…Feature may be marked directly in the 3D model, on the penetration image, or in a data structure that references (e.g., shares a coordinate system with) the 3D model of the tooth formed by the methods and apparatuses described herein.” [0024],
determine, based on the diagnostic feature of the intraoral object, the health-condition or probability thereof (“In particular, the method and apparatuses described herein may include examining internal features and/or identifying features of interest, including crack and caries.” [0024],
redefine, during the scan where the diagnostic feature is determined and based on the diagnostic feature or the related determined health-condition or the probability thereof, the first acquisition-mode and the second acquisition-mode (“Features may be marked, including coloring, labeling or the like. Feature may be marked directly in the 3D model, on the penetration image, or in a data structure that references (e.g., shares a coordinate system with) the 3D model of the tooth formed” [0024], “cycling between the first modality and the second modality using a scanning scheme wherein cycling rapidly switches between the first modality and the second modality so that the internal data uses the same coordinate system as the 3D surface model data captured in the first modality; and adjusting the scanning scheme based on the captured 3D surface model data, the internal data, or both the 3D surface model data and the internal data.” [0029]):
and a display, whereon the 3D-model and the health-condition or the probability thereof are displayed (“One or more additional outputs 119 may also be included for outputting or presenting information, including display screens, printers, etc.” [0232], “Features may be marked, including coloring, labeling or the like. Feature may be marked directly in the 3D model, on the penetration image, or in a data structure that references (e.g., shares a coordinate system with) the 3D model of the tooth formed by the methods and apparatuses described herein.” [0024]).
Elbaz does not specifically disclose an acquisition-controller and the first acquisition mode is defined by a first gain-value and said second acquisition-mode is defined by a second gain-value, wherein the first gain-value is controlled via a pin to the image sensor.
However, Elbaz discloses multiple processors controlling different functions in the wand (“The intraoral scanner 101 may also include one or more processors, including linked processors or remote processors, for both controlling the wand 103 operation, including coordinating the scanning and in reviewing and processing the scanning and generation of the 3D model including surface and internal features.” [0232])
It would have been obvious to an ordinary skilled person in the art before the effective filing
date of the claimed invention to modify the system of Elbaz as outlined above with an acquisition-controller, because it would allow for the coordination of the scan to generate a 3D model that includes surface and internal features [0232].
Elbaz does not specifically disclose that the first acquisition mode is defined by a first gain-value and said second acquisition-mode is defined by a second gain-value, wherein the first gain-value is controlled via a pin to the image sensor.
However, in a similar field of endeavor, Deane teaches methods and systems for improved detection of localized gingival inflammation using an oral care device via automatic brightness and/or gain control [0001].
Deane also teaches that the first acquisition mode is defined by a first gain-value and said second acquisition-mode is defined by a second gain-value (“the device determines which of the locations comprise gingiva, and the device then automatically adjusts the intensity of the one or more light emitters illuminating the gingiva, and/or automatically adjusts the gain of the photodetectors corresponding to the gingiva.” [0006], “the adjustment module 410 is configured to adjust the intensity and/or gain in order to keep reflectance signals for each location in an optimum dynamic range of the ADC used to digitize the samples while minimizing noise.” [0057])
wherein the first gain-value is controlled via a pin to the image sensor (“Examples of controller components that may be employed in various embodiments of the present disclosure include, but are not limited to, conventional microprocessors, application specific integrated circuits (ASICs), and field-programmable gate arrays (FPGAs).” [0018], in Applicants Spec [0065], an example pin is a FPGA)
It would have been obvious to an ordinary skilled person in the art before the effective filing
date of the claimed invention to modify the system of Elbaz as outlined above with the first acquisition mode is defined by a first gain-value and said second acquisition-mode is defined by a second gain-value, wherein the first gain-value is controlled via a pin to the image sensor as taught by Deane, because there is a continued need in the art for oral care methods and devices that minimize noise while keeping the returned light signals for each region in an optimum dynamic range [0005].
Regarding Claim 2, Elbaz discloses that the determination of the health- condition or the probability thereof is independent of one or more dataset(s) of the intraoral object that is/are formed 24 hours or more before the first dataset and second dataset being formed (“Thus, a method of generating a model of a subject's teeth may include: using a hand-held intraoral scanner to scan a portion of a subject's tooth using a first modality to capture three-dimensional (3D) surface model data of the tooth; using the hand-held intraoral scanner to scan the portion of the subject's tooth using a second modality to image into the tooth using a penetrative wavelength to capture internal data of the tooth; cycling between the first modality and the second modality using a scanning scheme wherein cycling rapidly switches between the first modality and the second modality so that the internal data uses the same coordinate system as the 3D surface model data captured in the first modality; and adjusting the scanning scheme based on the captured 3D surface model data, the internal data, or both the 3D surface model data and the internal data.” [0029], Elbaz does not disclose combining previously acquired datasets thus there is an inherent independence between scans conducted at different times)
Regarding Claim 3, Elbaz discloses that the data processor is further configured to correlate at least a part of the 2D-image to at least a corresponding 3D-point on or inside the 3D-model, whereby the at least part of the 2D-image and the health-condition or the probability thereof is related to a 3D-location of the 3D-point on or inside the 3D-model (“Features may be marked, including coloring, labeling or the like. Feature may be marked directly in the 3D model, on the penetration image, or in a data structure that references (e.g., shares a coordinate system with) the 3D model of the tooth formed by the methods and apparatuses described herein.” [0024])
Regarding Claim 4, Elbaz discloses that the data processor is further configured to correlate at least a part of the 2D-image to at least a corresponding 3D-point on or inside the 3D-model, whereby the at least part of the 2D-image and the health-condition and/or the probability thereof is related to a 3D-location of the 3D-point on or inside the 3D-model (“using a first coordinate system; generate a three-dimensional (3D) surface model of at least a portion of a subject's tooth using the surface information; take a plurality of images in the second spectral range, wherein the images reference the first coordinate system; and generate a 3D model of the subject's tooth including internal structures based on the 3D surface model and the a plurality of images.” [0026])
Regarding Claim 5, Elbaz discloses that the health-condition or the probability thereof is displayed with a 3D-diagnosis indicator between the health-condition or the probability thereof and the 3D-model to show how the health-condition or the probability thereof correlates to the 3D-location of the 3D- point on or inside the 3D-model (“using a first coordinate system; generate a three-dimensional (3D) surface model of at least a portion of a subject's tooth using the surface information; take a plurality of images in the second spectral range, wherein the images reference the first coordinate system; and generate a 3D model of the subject's tooth including internal structures based on the 3D surface model and the a plurality of images.” [0026], “Features may be marked, including coloring, labeling or the like. Feature may be marked directly in the 3D model, on the penetration image, or in a data structure that references (e.g., shares a coordinate system with) the 3D model of the tooth formed by the methods and apparatuses described herein.” [0024]).
Regarding Claim 6, Elbaz discloses that the health-condition or the probability thereof is displayed with a 2D-diagnosis indicator between the health-condition or the probability thereof and the 2D-image or the at least part of the 2D-image to show how the health-condition or the probability thereof correlates to the diagnostic feature (“using a first coordinate system; generate a three-dimensional (3D) surface model of at least a portion of a subject's tooth using the surface information; take a plurality of images in the second spectral range, wherein the images reference the first coordinate system; and generate a 3D model of the subject's tooth including internal structures based on the 3D surface model and the a plurality of images.” [0026], “Features may be marked, including coloring, labeling or the like. Feature may be marked directly in the 3D model, on the penetration image, or in a data structure that references (e.g., shares a coordinate system with) the 3D model of the tooth formed by the methods and apparatuses described herein.” [0024])
Regarding Claim 7, Elbaz discloses that the diagnostic algorithm is based on artificial intelligence or is based on pattern recognition (“In any of the methods and apparatuses configured to perform these methods described herein, the data may be analyzed automatically or manually by the system. In particular, the method and apparatuses described herein may include examining internal features and/or identifying features of interest, including crack and caries. Features may be recognized based on feature-recognition criterion (e.g., dark or light regions in the penetration images), pattern-recognition, machine learning, or the like.” [0024]).
Regarding Claim 9, Elbaz discloses that the scanning device further comprises: a controller configured to operate the illumination-unit in a first illumination-mode (“The intraoral scanner 101 may also include one or more processors, including linked processors or remote processors, for both controlling the wand 103 operation, including coordinating the scanning and in reviewing and processing the scanning and generation of the 3D model including surface and internal features.” [0232], “the system may alternate (switch) between scanning a portion of the tooth using a first modality 705 (e.g., surface scanning, using emitting light in an appropriate wavelength of range of wavelengths)” [0262], “a first light source 109 configured to emit light in a first spectral range for detection of surface features (e.g., visible light, monochromatic visible light, etc.; this light does not have to be visible light)” [0230]),
and configured to operate the illumination unit in a second illumination-mode (“After an appropriate duration in the first modality, the method and apparatus may briefly switch to a second modality (e.g., a penetrative wavelength or range of wavelengths)” [0262], “and a third light source 111 configured to emit light in a second spectral range for detection of internal features within the tooth (e.g., by trans-illumination, small-angle penetration imaging” [0230]),
wherein the scanning device is configured to change between the first illumination-mode and the second illumination-mode (“after positioning the scanner adjacent to the target intraoral structure to be modeled 701, the wand may be moved over the target while the apparatus automatically scans 703 the target for both surface data and internal data. As part of this method, the system may alternate (switch) between scanning a portion of the tooth using a first modality 705 (e.g., surface scanning, using emitting light in an appropriate wavelength of range of wavelengths) to collect surface data such as 3D surface model data and scanning with a second modality 707 (e.g. a penetrative wavelength).” [0262]),
the first illumination-mode is defined by a first period of illumination-time and said second illumination-mode is defined by a second period of illumination-time (“Any of the methods described herein may include automatically adjusting the duration of time spent scanning in first modality, the duration of time spent in the second modality, or the duration of time spent in the first and the second modality when cycling between the first modality and the second modality.” [0029], “In FIG. 1B, three light sources are shown: a first light source 109 configured to emit light in a first spectral range for detection of surface features (e.g., visible light, monochromatic visible light, etc.; this light does not have to be visible light), a second color light source (e.g., white light between 400-700 nm, e.g., approximately 400-600 nm), and a third light source 111 configured to emit light in a second spectral range for detection of internal features within the tooth (e.g., by trans-illumination, small-angle penetration imaging, laser florescence, etc., which may generically be referred to as penetration imaging, e.g., in the near-IR). Although separate illumination sources are shown in FIG. 1B, in some variations a selectable light source may be used.” [0230])
Elbaz does not specifically disclose an illumination-controller.
However, Elbaz discloses multiple processors controlling different functions in the wand (“The intraoral scanner 101 may also include one or more processors, including linked processors or remote processors, for both controlling the wand 103 operation, including coordinating the scanning and in reviewing and processing the scanning and generation of the 3D model including surface and internal features.” [0232])
It would have been obvious to an ordinary skilled person in the art before the effective filing
date of the claimed invention to modify the system of Elbaz as outlined above with an illumination-controller, because it would allow for the coordination of the scan to generate a 3D model that includes surface and internal features [0232].
Regarding Claim 10, Elbaz discloses that said first acquisition-mode is defined by a first period of acquisition-time and said second acquisition-mode is defined by a second period of acquisition-time. (“Any of the methods described herein may include automatically adjusting the duration of time spent scanning in first modality, the duration of time spent in the second modality, or the duration of time spent in the first and the second modality when cycling between the first modality and the second modality.” [0029], “In FIG. 1B, three light sources are shown: a first light source 109 configured to emit light in a first spectral range for detection of surface features (e.g., visible light, monochromatic visible light, etc.; this light does not have to be visible light), a second color light source (e.g., white light between 400-700 nm, e.g., approximately 400-600 nm), and a third light source 111 configured to emit light in a second spectral range for detection of internal features within the tooth (e.g., by trans-illumination, small-angle penetration imaging, laser florescence, etc., which may generically be referred to as penetration imaging, e.g., in the near-IR). Although separate illumination sources are shown in FIG. 1B, in some variations a selectable light source may be used.” [0230])
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-7, and 9-10 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
Applicant's submission of an information disclosure statement under 37 CFR 1.97(c) with the timing fee set forth in 37 CFR 1.17(p) on 07/01/2025 prompted the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 609.04(b). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to STEVEN MALDONADO whose telephone number is 703-756-1421. The examiner can normally be reached 8:00 am-4:00 pm PST M-Th Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at
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/Steven Maldonado/
Patent Examiner, Art Unit 3797
/CHRISTOPHER KOHARSKI/Supervisory Patent Examiner, Art Unit 3797
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