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 .
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The information disclosure statement (IDS) submitted on 04/03/2025, 01/30/2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
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Claims 1-7 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-3, 7 of U.S. Patent No. 12288291 as described in the table below. Although the claims at issue are not identical, they are not patentably distinct from each other because claims 1-7 of current application are obvious variations of claims 1-3, 7 of U.S. Patent No. 12288291.
Current application 19037703
U.S. Patent No. 12288291
1. A computer implemented method for automatically generating, by one or more computer processors, a 3-dimensional model for use in a virtual extraction of a targeted extraction object of a patient, the targeted extraction object comprising an object in a patient’s anatomy, the method based on each of a surface scan of an anatomical region of the patient’s oral cavity and a volumetric density scan of the anatomical region, the anatomical region including at least the targeted extraction object, the method comprising: receiving a first dataset of labeled surface scan segments, each surface scan segment comprising a 3-dimensional (3D) surface model of a corresponding object recognized and segmented from surface scan data of the surface scan, and each surface scan segment having an associated label identifying the surface scan segment; receiving a second dataset of labeled volumetric density scan segments, each volumetric density scan segment comprising a 3-dimensional (3D) volumetric density model of a boundary surface of a corresponding object recognized and segmented from volumetric density scan data of the volumetric density scan, and each volumetric density scan segment having an associated label identifying the volumetric density scan segment; cross-mounting in a common 3D coordinate system, labeled surface scan segments from the first dataset to labeled volumetric density scan segments from the second dataset; receiving identification of the targeted extraction object; identifying the 3D volumetric density model associated with the volumetric density scan segment label which corresponds to the identified targeted extraction object; identifying the 3D surface model associated with the surface scan segment label which corresponds to the identified targeted extraction object; generating a third dataset comprising a model comprising a 3D model of a socket being an equivalent of the identified 3D volumetric density model less portions of the identified 3D volumetric density model co-represented in the identified 3D surface model.
1. (Previously Presented) A computer implemented method for automatically generating, by one or more computer processors, a 3-dimensional model for use in a virtual extraction of a targeted extraction object of a patient, the targeted extraction object comprising an object in a patient’s anatomy, the method based on each of a surface scan of an anatomical region of the patient’s oral cavity and a volumetric density scan of the anatomical region, the anatomical region including at least the targeted extraction object, the method comprising: receiving a first dataset of labeled surface scan segments, each surface scan segment comprising a 3-dimensional (3D) surface model of a corresponding object recognized and segmented from surface scan data of the surface scan, and each surface scan segment having an associated label identifying the surface scan segment; receiving a second dataset of labeled volumetric density scan segments, each volumetric density scan segment comprising a 3-dimensional (3D) volumetric density model of a boundary surface of a corresponding object recognized and segmented from volumetric density scan data of the volumetric density scan, and each volumetric density scan segment having an associated label identifying the volumetric density scan segment; cross-mounting in a common 3D coordinate system, labeled surface scan segments from the first dataset to labeled volumetric density scan segments from the second dataset; receiving identification of the targeted extraction object; identifying the 3D volumetric density model associated with the volumetric density scan segment label which corresponds to the identified targeted extraction object; identifying the 3D surface model associated with the surface scan segment label which corresponds to the identified targeted extraction object; generating a third dataset comprising a model comprising: a 3D model of a socket being an equivalent of the identified 3D volumetric density model less portions of the identified 3D volumetric density model co-represented in the identified 3D surface model; at least a portion of the identified 3D volumetric density model co-represented in the identified 3D surface model and/or at least a portion of the identified 3D surface model co-represented in the identified 3D volumetric density model; at least a portion of the identified 3D volumetric density model less portions of the identified 3D volumetric density model co-represented in the identified 3D surface model; and/or at least a subset of the first dataset less portions of the identified 3D surface model co-represented in the identified 3D volumetric density model.
2. A computer implemented method for automatically generating, by one or more computer processors, a 3-dimensional model for use in a virtual extraction of a targeted extraction object of a patient, the targeted extraction object comprising an object in a patient’s anatomy, the method based on each of a surface scan of an anatomical region of the patient’s oral cavity and a volumetric density scan of the anatomical region, the anatomical region including at least the targeted extraction object, the method comprising: receiving a first dataset of labeled surface scan segments, each surface scan segment comprising a 3-dimensional (3D) surface model of a corresponding object recognized and segmented from surface scan data of the surface scan, and each surface scan segment having an associated label identifying the surface scan segment; receiving a second dataset of labeled volumetric density scan segments, each volumetric density scan segment comprising a 3-dimensional (3D) volumetric density model of a boundary surface of a corresponding object recognized and segmented from volumetric density scan data of the volumetric density scan, and each volumetric density scan segment having an associated label identifying the volumetric density scan segment; cross-mounting in a common 3D coordinate system, labeled surface scan segments from the first dataset to labeled volumetric density scan segments from the second dataset; receiving identification of the targeted extraction object; identifying the 3D volumetric density model associated with the volumetric density scan segment label which corresponds to the identified targeted extraction object;identifying the 3D surface model associated with the surface scan segment label which corresponds to the identified targeted extraction object; generating a third dataset comprising a model comprising at least a portion of the identified 3D volumetric density model co-represented in the identified 3D surface model and/or at least a portion of the identified 3D surface model co-represented in the identified 3D volumetric density model.
1. (Previously Presented) A computer implemented method for automatically generating, by one or more computer processors, a 3-dimensional model for use in a virtual extraction of a targeted extraction object of a patient, the targeted extraction object comprising an object in a patient’s anatomy, the method based on each of a surface scan of an anatomical region of the patient’s oral cavity and a volumetric density scan of the anatomical region, the anatomical region including at least the targeted extraction object, the method comprising: receiving a first dataset of labeled surface scan segments, each surface scan segment comprising a 3-dimensional (3D) surface model of a corresponding object recognized and segmented from surface scan data of the surface scan, and each surface scan segment having an associated label identifying the surface scan segment; receiving a second dataset of labeled volumetric density scan segments, each volumetric density scan segment comprising a 3-dimensional (3D) volumetric density model of a boundary surface of a corresponding object recognized and segmented from volumetric density scan data of the volumetric density scan, and each volumetric density scan segment having an associated label identifying the volumetric density scan segment; cross-mounting in a common 3D coordinate system, labeled surface scan segments from the first dataset to labeled volumetric density scan segments from the second dataset; receiving identification of the targeted extraction object; identifying the 3D volumetric density model associated with the volumetric density scan segment label which corresponds to the identified targeted extraction object; identifying the 3D surface model associated with the surface scan segment label which corresponds to the identified targeted extraction object; generating a third dataset comprising a model comprising: a 3D model of a socket being an equivalent of the identified 3D volumetric density model less portions of the identified 3D volumetric density model co-represented in the identified 3D surface model; at least a portion of the identified 3D volumetric density model co-represented in the identified 3D surface model and/or at least a portion of the identified 3D surface model co-represented in the identified 3D volumetric density model; at least a portion of the identified 3D volumetric density model less portions of the identified 3D volumetric density model co-represented in the identified 3D surface model; and/or at least a subset of the first dataset less portions of the identified 3D surface model co-represented in the identified 3D volumetric density model.
3. A computer implemented method for automatically generating, by one or more computer processors, a 3-dimensional model for use in a virtual extraction of a targeted extraction object of a patient, the targeted extraction object comprising an object in a patient’s anatomy, the method based on each of a surface scan of an anatomical region of the patient’s oral cavity and a volumetric density scan of the anatomical region, the anatomical region including at least the targeted extraction object, the method comprising: receiving a first dataset of labeled surface scan segments, each surface scan segment comprising a 3-dimensional (3D) surface model of a corresponding object recognized and segmented from surface scan data of the surface scan, and each surface scan segment having an associated label identifying the surface scan segment; receiving a second dataset of labeled volumetric density scan segments, each volumetric density scan segment comprising a 3-dimensional (3D) volumetric density model of a boundary surface of a corresponding object recognized and segmented from volumetric density scan data of the volumetric density scan, and each volumetric density scan segment having an associated label identifying the volumetric density scan segment; cross-mounting in a common 3D coordinate system, labeled surface scan segments from the first dataset to labeled volumetric density scan segments from the second dataset; receiving identification of the targeted extraction object; identifying the 3D volumetric density model associated with the volumetric density scan segment label which corresponds to the identified targeted extraction object; identifying the 3D surface model associated with the surface scan segment label which corresponds to the identified targeted extraction object; generating a third dataset comprising a model comprising at least a portion of the identified 3D volumetric density model less portions of the identified 3D volumetric density model co-represented in the identified 3D surface model.
1. (Previously Presented) A computer implemented method for automatically generating, by one or more computer processors, a 3-dimensional model for use in a virtual extraction of a targeted extraction object of a patient, the targeted extraction object comprising an object in a patient’s anatomy, the method based on each of a surface scan of an anatomical region of the patient’s oral cavity and a volumetric density scan of the anatomical region, the anatomical region including at least the targeted extraction object, the method comprising: receiving a first dataset of labeled surface scan segments, each surface scan segment comprising a 3-dimensional (3D) surface model of a corresponding object recognized and segmented from surface scan data of the surface scan, and each surface scan segment having an associated label identifying the surface scan segment; receiving a second dataset of labeled volumetric density scan segments, each volumetric density scan segment comprising a 3-dimensional (3D) volumetric density model of a boundary surface of a corresponding object recognized and segmented from volumetric density scan data of the volumetric density scan, and each volumetric density scan segment having an associated label identifying the volumetric density scan segment; cross-mounting in a common 3D coordinate system, labeled surface scan segments from the first dataset to labeled volumetric density scan segments from the second dataset; receiving identification of the targeted extraction object; identifying the 3D volumetric density model associated with the volumetric density scan segment label which corresponds to the identified targeted extraction object; identifying the 3D surface model associated with the surface scan segment label which corresponds to the identified targeted extraction object; generating a third dataset comprising a model comprising: a 3D model of a socket being an equivalent of the identified 3D volumetric density model less portions of the identified 3D volumetric density model co-represented in the identified 3D surface model; at least a portion of the identified 3D volumetric density model co-represented in the identified 3D surface model and/or at least a portion of the identified 3D surface model co-represented in the identified 3D volumetric density model; at least a portion of the identified 3D volumetric density model less portions of the identified 3D volumetric density model co-represented in the identified 3D surface model; and/or at least a subset of the first dataset less portions of the identified 3D surface model co-represented in the identified 3D volumetric density model.
4. A computer implemented method for automatically generating, by one or more computer processors, a 3-dimensional model for use in a virtual extraction of a targeted extraction object of a patient, the targeted extraction object comprising an object in a patient’s anatomy, the method based on each of a surface scan of an anatomical region of the patient’s oral cavity and a volumetric density scan of the anatomical region, the anatomical region including at least the targeted extraction object, the method comprising: receiving a first dataset of labeled surface scan segments, each surface scan segment comprising a 3-dimensional (3D) surface model of a corresponding object recognized and segmented from surface scan data of the surface scan, and each surface scan segment having an associated label identifying the surface scan segment; receiving a second dataset of labeled volumetric density scan segments, each volumetric density scan segment comprising a 3-dimensional (3D) volumetric density model of a boundary surface of a corresponding object recognized and segmented from volumetric density scan data of the volumetric density scan, and each volumetric density scan segment having an associated label identifying the volumetric density scan segment; cross-mounting in a common 3D coordinate system, labeled surface scan segments from the first dataset to labeled volumetric density scan segments from the second dataset; receiving identification of the targeted extraction object; identifying the 3D volumetric density model associated with the volumetric density scan segment label which corresponds to the identified targeted extraction object; identifying the 3D surface model associated with the surface scan segment label which corresponds to the identified targeted extraction object; generating a third dataset comprising a model comprising at least a subset of the first dataset less portions of the identified 3D surface model co-represented in the identified 3D volumetric density model.
1. (Previously Presented) A computer implemented method for automatically generating, by one or more computer processors, a 3-dimensional model for use in a virtual extraction of a targeted extraction object of a patient, the targeted extraction object comprising an object in a patient’s anatomy, the method based on each of a surface scan of an anatomical region of the patient’s oral cavity and a volumetric density scan of the anatomical region, the anatomical region including at least the targeted extraction object, the method comprising: receiving a first dataset of labeled surface scan segments, each surface scan segment comprising a 3-dimensional (3D) surface model of a corresponding object recognized and segmented from surface scan data of the surface scan, and each surface scan segment having an associated label identifying the surface scan segment; receiving a second dataset of labeled volumetric density scan segments, each volumetric density scan segment comprising a 3-dimensional (3D) volumetric density model of a boundary surface of a corresponding object recognized and segmented from volumetric density scan data of the volumetric density scan, and each volumetric density scan segment having an associated label identifying the volumetric density scan segment; cross-mounting in a common 3D coordinate system, labeled surface scan segments from the first dataset to labeled volumetric density scan segments from the second dataset; receiving identification of the targeted extraction object; identifying the 3D volumetric density model associated with the volumetric density scan segment label which corresponds to the identified targeted extraction object; identifying the 3D surface model associated with the surface scan segment label which corresponds to the identified targeted extraction object; generating a third dataset comprising a model comprising: a 3D model of a socket being an equivalent of the identified 3D volumetric density model less portions of the identified 3D volumetric density model co-represented in the identified 3D surface model; at least a portion of the identified 3D volumetric density model co-represented in the identified 3D surface model and/or at least a portion of the identified 3D surface model co-represented in the identified 3D volumetric density model; at least a portion of the identified 3D volumetric density model less portions of the identified 3D volumetric density model co-represented in the identified 3D surface model; and/or at least a subset of the first dataset less portions of the identified 3D surface model co-represented in the identified 3D volumetric density model.
5. The method of any one of claims 1 to 4, the generation step comprising: determining portions of the identified 3D volumetric density model not co- represented in the identified 3D surface model; and, optionally, storing, in a computer-readable data storage component, the determined portions of the identified 3D volumetric density model as the 3D model of the socket.
2. (Currently Amended) The method of claim 1, the generation step comprising: determining portions of the identified 3D volumetric density model not co-represented in the identified 3D surface model; and storing, in a computer-readable data storage component, the determined portions of the identified 3D volumetric density-model as the 3D model of the socket.
6. The method of any one of claims 1 to 4, the generation step comprising: determining portions of the identified 3D volumetric density model co- represented in the identified 3D surface model; determining a difference between the determined co-represented portions and the identified 3D volumetric density model by removing the determined co-represented portions from the identified 3D volumetric density model; and, optionally, storing, in a computer-readable data storage component the determined difference as the 3D model of the socket.
3. (Currently Amended) The method of claim 1, the generation step comprising: determining portions of the identified 3D volumetric density model co-represented in the identified 3D surface model; determining a difference between the determined co-represented portions and the identified 3D volumetric density-model by removing the determined co-represented portions from the identified 3D volumetric density model; and storing, in a computer-readable data storage component the determined difference as the 3D model of the socket.
7. The method of any one of claims 1 to 4, comprising: determining a boundary of the identified 3D surface model and generating a cut- line therefrom; and projecting the cut-line onto the identified 3D volumetric density model.
7. (Previously Presented) The method of claim 1, comprising: determining a boundary of the identified 3D surface model and generating a cut-line therefrom; and projecting the cut-line onto the identified 3D volumetric density model.
Allowable Subject Matter
Claims 1-7 would be allowable if rewritten or amended to overcome the rejection(s) under Double Patenting, set forth in this Office action.
The following is a statement of reasons for the indication of allowable subject matter: no prior art teaches the italicized and bolded features.
Claim 1. A computer implemented method for automatically generating, by one or more computer processors, a 3-dimensional model for use in a virtual extraction of a targeted extraction object of a patient, the targeted extraction object comprising an object in a patient’s anatomy, the method based on each of a surface scan of an anatomical region of the patient’s oral cavity and a volumetric density scan of the anatomical region, the anatomical region including at least the targeted extraction object, the method comprising: receiving a first dataset of labeled surface scan segments, each surface scan segment comprising a 3-dimensional (3D) surface model of a corresponding object recognized and segmented from surface scan data of the surface scan, and each surface scan segment having an associated label identifying the surface scan segment; receiving a second dataset of labeled volumetric density scan segments, each volumetric density scan segment comprising a 3-dimensional (3D) volumetric density model of a boundary surface of a corresponding object recognized and segmented from volumetric density scan data of the volumetric density scan, and each volumetric density scan segment having an associated label identifying the volumetric density scan segment; cross-mounting in a common 3D coordinate system, labeled surface scan segments from the first dataset to labeled volumetric density scan segments from the second dataset; receiving identification of the targeted extraction object; identifying the 3D volumetric density model associated with the volumetric density scan segment label which corresponds to the identified targeted extraction object; identifying the 3D surface model associated with the surface scan segment label which corresponds to the identified targeted extraction object; generating a third dataset comprising a model comprising a 3D model of a socket being an equivalent of the identified 3D volumetric density model less portions of the identified 3D volumetric density model co-represented in the identified 3D surface model.Claim 2. A computer implemented method for automatically generating, by one or more computer processors, a 3-dimensional model for use in a virtual extraction of a targeted extraction object of a patient, the targeted extraction object comprising an object in a patient’s anatomy, the method based on each of a surface scan of an anatomical region of the patient’s oral cavity and a volumetric density scan of the anatomical region, the anatomical region including at least the targeted extraction object, the method comprising: receiving a first dataset of labeled surface scan segments, each surface scan segment comprising a 3-dimensional (3D) surface model of a corresponding object recognized and segmented from surface scan data of the surface scan, and each surface scan segment having an associated label identifying the surface scan segment; receiving a second dataset of labeled volumetric density scan segments, each volumetric density scan segment comprising a 3-dimensional (3D) volumetric density model of a boundary surface of a corresponding object recognized and segmented from volumetric density scan data of the volumetric density scan, and each volumetric density scan segment having an associated label identifying the volumetric density scan segment; cross-mounting in a common 3D coordinate system, labeled surface scan segments from the first dataset to labeled volumetric density scan segments from the second dataset; receiving identification of the targeted extraction object; identifying the 3D volumetric density model associated with the volumetric density scan segment label which corresponds to the identified targeted extraction object; identifying the 3D surface model associated with the surface scan segment label which corresponds to the identified targeted extraction object; generating a third dataset comprising a model comprising at least a portion of the identified 3D volumetric density model co-represented in the identified 3D surface model and/or at least a portion of the identified 3D surface model co-represented in the identified 3D volumetric density model.Claim 3. A computer implemented method for automatically generating, by one or more computer processors, a 3-dimensional model for use in a virtual extraction of a targeted extraction object of a patient, the targeted extraction object comprising an object in a patient’s anatomy, the method based on each of a surface scan of an anatomical region of the patient’s oral cavity and a volumetric density scan of the anatomical region, the anatomical region including at least the targeted extraction object, the method comprising: receiving a first dataset of labeled surface scan segments, each surface scan segment comprising a 3-dimensional (3D) surface model of a corresponding object recognized and segmented from surface scan data of the surface scan, and each surface scan segment having an associated label identifying the surface scan segment; receiving a second dataset of labeled volumetric density scan segments, each volumetric density scan segment comprising a 3-dimensional (3D) volumetric density model of a boundary surface of a corresponding object recognized and segmented from volumetric density scan data of the volumetric density scan, and each volumetric density scan segment having an associated label identifying the volumetric density scan segment; cross-mounting in a common 3D coordinate system, labeled surface scan segments from the first dataset to labeled volumetric density scan segments from the second dataset; receiving identification of the targeted extraction object; identifying the 3D volumetric density model associated with the volumetric density scan segment label which corresponds to the identified targeted extraction object; identifying the 3D surface model associated with the surface scan segment label which corresponds to the identified targeted extraction object; generating a third dataset comprising a model comprising at least a portion of the identified 3D volumetric density model less portions of the identified 3D volumetric density model co-represented in the identified 3D surface model.Claim 4. A computer implemented method for automatically generating, by one or more computer processors, a 3-dimensional model for use in a virtual extraction of a targeted extraction object of a patient, the targeted extraction object comprising an object in a patient’s anatomy, the method based on each of a surface scan of an anatomical region of the patient’s oral cavity and a volumetric density scan of the anatomical region, the anatomical region including at least the targeted extraction object, the method comprising: receiving a first dataset of labeled surface scan segments, each surface scan segment comprising a 3-dimensional (3D) surface model of a corresponding object recognized and segmented from surface scan data of the surface scan, and each surface scan segment having an associated label identifying the surface scan segment; receiving a second dataset of labeled volumetric density scan segments, each volumetric density scan segment comprising a 3-dimensional (3D) volumetric density model of a boundary surface of a corresponding object recognized and segmented from volumetric density scan data of the volumetric density scan, and each volumetric density scan segment having an associated label identifying the volumetric density scan segment; cross-mounting in a common 3D coordinate system, labeled surface scan segments from the first dataset to labeled volumetric density scan segments from the second dataset; receiving identification of the targeted extraction object; identifying the 3D volumetric density model associated with the volumetric density scan segment label which corresponds to the identified targeted extraction object; identifying the 3D surface model associated with the surface scan segment label which corresponds to the identified targeted extraction object; generating a third dataset comprising a model comprising at least a subset of the first dataset less portions of the identified 3D surface model co-represented in the identified 3D volumetric density model.Claims 3-7 depend on anyone of allowable claims 1-4 and are therefore allowable for the same reasons as anyone of allowable claims 1-4.
Claim 8 is 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.
The following is a statement of reasons for the indication of allowable subject matter:
Claim 8 depend on anyone of allowable claims 1-4 and are therefore allowable for the same reasons as anyone of allowable claims 1-4.
Relevant prior art:US 20180028065 Al Methods and apparatuses for generating a model of a subject's teeth. Described herein are intraoral scanning methods and apparatuses for generating a three - dimensional model of a subject's intraoral region (e.g., teeth) including both surface features and internal features. These methods and apparatuses may be used for identifying and evaluating lesions, caries and cracks in the teeth. Any of these methods and apparatuses may use minimum scattering coefficients and/or segmentation to form a volumetric model of the teeth.
Conclusion
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/MARTIN MUSHAMBO/Primary Examiner, Art Unit 2615 11/30/2025