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 .
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed on 7 October, 2024.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 7 October, 2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Objections
Claim 5 is objected to because of the following informalities:
Claim 5 states “wherein method further comprises”, this should say “wherein the method further comprises”.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
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.
Claims 2 – 13 and 15 - 20 are 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.
Claim 2 recites the limitation "the step of calculating a curved path" in lines 1 – 2 and “the patient’s teeth”. There is insufficient antecedent basis for this limitation in the claim.
Claim 3 recites the limitation "the step of detecting" in line 2, “the center” in line 2, and “the left and/or right condyle” in line 2. There is insufficient antecedent basis for this limitation in the claim.
Claim 4 recites the limitation "the arch form" in line 2. There is insufficient antecedent basis for this limitation in the claim.
Claim 5 recites the limitation "the step of analyzing" in line 2. There is insufficient antecedent basis for this limitation in the claim.
Claim 6 recites the limitation "the step of tracking" in lines 2 – 3 and “the step of calculating” in line 5. There is insufficient antecedent basis for this limitation in the claim.
Claim 7 recites the limitation "the orientation" in line 2, “the curved path” in line 2, and “the dental arch” in line 3. There is insufficient antecedent basis for this limitation in the claim.
Claim 8 recites the limitation "the plane" in line 3. There is insufficient antecedent basis for this limitation in the claim.
Claim 9 recites the limitation "the tooth axis" in line 3 and 4, “the position” in line 3 and 5. There is insufficient antecedent basis for this limitation in the claim.
Claim 10 recites the limitation "the three components" in lines 2 – 3. There is insufficient antecedent basis for this limitation in the claim.
Claim 11 recites the limitation "the relative positions" in line 4. There is insufficient antecedent basis for this limitation in the claim.
Claim 12 recites the limitation "the step of deriving" in line 1. There is insufficient antecedent basis for this limitation in the claim.
Claim 13 recites the limitation "the step of generating and displaying" in line 1. There is insufficient antecedent basis for this limitation in the claim.
Claim 15 recites the limitation "the steps" in line 2, “the at least one missing tooth” in line 3, and “the direction of a tooth axis” in line 6. There is insufficient antecedent basis for this limitation in the claim.
Claim 16 recites the limitation "the curve of the path" in line 3. There is insufficient antecedent basis for this limitation in the claim.
Claim 17 recites the limitation "the step of generating and displaying a reslice image of a reslice plane" in line 3. There is insufficient antecedent basis for this limitation in the claim.
Claim 18 recites the limitation "the tooth axis” in line 3. There is insufficient antecedent basis for this limitation in the claim.
Claim 19 recites the limitation "the center” in lines 17 and 18, “the left and/or right” in lines 17 and 18 – 19, and “the arch form” in line 21. There is insufficient antecedent basis for this limitation in the claim.
Claim 20 recites the limitation "the plane” in line 22, “the position of one of the teeth” in lines 25 – 26 and line 27. There is insufficient antecedent basis for this limitation in the claim.
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.
Claims 1 – 5, 7 – 11, 19 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Ezhov et al (U.S. Patent Publication No. 2021/0217170 A1, hereinafter “Ezhov”) in view of Tong et al (Hongsheng Tong "A new method to measure mesiodistal angulation and faciolingual inclination of each whole tooth with volumetric cone-beam computed tomography images”, American Journal of Orthodontics and Dentofacial Orthopedics, Volume 142, Issue 1, 2012,Pages 133-143, ISSN 0889-5406, hereinafter “Tong”).
Regarding claim 1, Ezhov teaches a computer implemented method for automatically generating and displaying, derived from 3D image data (¶ 0035: In another embodiment, the input data is 3-Dimensional (3D) image data.), a 2D image of a portion of a patient's maxillofacial anatomy (¶ 0008: Further embodiments disclosed include a method and system for constructing a panorama with elements of interest (EoI) emphasized of a teeth arch or any point of interest in an oral-maxillofacial complex.), said method comprising the steps:
receiving 3D image data comprising a voxel image volume representing the maxillofacial anatomy of the patient (¶ 0035: In another embodiment, the input data is 3-Dimensional (3D) image data. The volumetric image processor 103a is configured to receive the volumetric image data from the radio-image gathering source.), the voxel image volume including teeth of the patient and each voxel of the voxel image volume being associated with a radiation intensity value (¶ 0036: Initially, the volumetric image data is pre-processed, which involves conversion of 3-D pixel array into an array of Hounsfield Unit (HU) radio intensity measurements.; ¶ 0050: At step 304, a tooth or anatomical structure inside the pre-processed and parsed i/v.i is localized and identified by tooth number.),
detecting one or more anatomical landmarks in said voxel image volume using a first artificial neural network (¶ 0036: The processor 103 is further configured to localize anatomical structures residing in the single image frame field of view by assigning at least one of each a pixel or voxel (p/v) a distinct anatomical structure by the voxel parsing engine 104… In one embodiment, localization is achieved using any one of fully convolutional network or plain classification convolutional neural network (FCN/CNN), such as a V-Net-based fully convolutional neural network. In one embodiment, the V-Net is a 3D generalization of UN et.),
using a second artificial neural network for determining (¶ 0011: The processor is configured to detect or classify the conditions for each defined anatomical structure within the cropped image by a detection module or classification layer. In one embodiment, the classification is achieved using any one of a fully convolutional network or plain classification convolutional neural network (FCN/CNN).; ¶ 0037: The processor 103 is further configured to select all p/v belonging to the localized anatomical structure by finding a minimal bounding rectangle around the p/v and the surrounding region for cropping as a defined anatomical structure by the localization layer.), and
generating the 2D image as a reslice image from the voxel image volume (¶ 0050: At step 308, a visual report is reconstructed with localized and defined anatomical structure. In some embodiments, the visual reports include, but not limited to, an endodontic report (with focus on tooth's root/canal system and its treatment state), an implantation report (with focus on the area where the tooth is missing), and a dystopic tooth report for tooth extraction (with focus on the area of dystopic/ impacted teeth). ¶ 0052: At step 320, a visual report is reconstructed with defined and localized anatomical structure. At step 322, conditions for each defined anatomical structure is classified within the cropped image by the classification layer.; Including ¶ 0072 and 0075).
Ezhov does not explicitly teach determining a crown center position; and generating the 2D image as a reslice image based on at least one crown center position.
However, Tong does teach determining a crown center position (Page 135, Col. 2, ¶ 3: Parallel movements of the sagittal, coronal, and axial planes were made so that each would pass through the center of the white stainless steel marker representing either the crown or the root point of each tooth (Figs 2 and 3).); and generating the 2D image as a reslice image based on at least one crown center position (Figure 2; Figure 2: Locating the maxillary right central incisor crown point before digitization: parallel movements of the sagittal (red), coronal (green), and axial (blue) planes were made to intersect at the center of the stainless steel ball representing the tooth's crown point.).
Tong is considered to be analogous art as it pertains to dental imaging. Therefore, it would have been obvious to one of ordinary skill in the art to combine the system for classifying a tooth condition based on landmarked anthropomorphic measurements (as taught by Ezhov) and the method to measure mesiodistal angulation and faciolingual inclination of each whole tooth (as taught by Tong) before the effective filing date of the claimed invention. The motivation for this combination of references would be Tong teaches measuring the location of the root when measuring the tooth’s mesiodistal angulation and faciolingual inclination which can help with long term stability and best orthodontal treatment outcome (See page 139, Col. 1 - 2).
This motivation for the combination of Ezhov and Tong 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 2, the Ezhov and Tong combination teaches the method according to claim 1.
Additionally, Ezhov teaches further comprising the step of calculating a curved path following a dental arch of the patient's teeth using said one or more anatomical landmarks and/or by fitting a curve to the determined crown center positions and using the curved path as a reference for generating the reslice image (¶ 0067: The first step concludes in voxel coordinates operations, such as extracting teeth arch and unfolding a study image into 3D panoramic ribbon (curved sub-volume that passes along the teeth arch). Teeth arch is extracted using segmentations of teeth and anatomy, mandible and mandibular canals in particular.).
Regarding claim 3, the Ezhov and Tong combination teaches the method according to claim 2.
Additionally, Ezhov teaches the method further comprising the step of detecting the center of the left and/or right condyle head using the first artificial neural network (¶ 0086: As a part of mandible/maxilla, TMJ parts: Condyle and temporal bone (this step is optional, landmarks could be detected) may be segmented. Then, several landmarks on condyle and temporal bone may be detected and distances between them measured.), wherein the curved path following the dental arch is calculated using the center of the left and/or right condyle head as endpoints (Figure 9, ¶ 0068: In general, two types of panoramas may be constructed using the above mentioned method: (1) a general panorama; and (2) a split panorama. A general panorama includes Rol for all the teeth present, a whole mandible with TMJs (emphasis added), and a lower part of maxilla with sinuses cropped to the middle.).
Regarding claim 4, the Ezhov and Tong combination teaches the method according to claim 2.
Additionally, Ezhov teaches wherein the reslice image is a panoramic image generated based on said curved path following the arch form of the patient's teeth (¶ 0067: The first step concludes in voxel coordinates operations, such as extracting teeth arch and unfolding a study image into 3D panoramic ribbon (curved sub-volume that passes along the teeth arch). Teeth arch is extracted using segmentations of teeth and anatomy, mandible and mandibular canals in particular… Then, construct a transformation grid that allows the arch to unfold in straight line, resulting in a panoramic ribbon.).
Regarding claim 5, the Ezhov and Tong combination teaches the method according to claim 1.
Additionally, Tong teaches wherein method further comprises the step of analyzing the 3D image data within at least an image region surrounding the determined crown center position of one of the teeth to derive a tooth axis, wherein the tooth axis intersects a coronal crown surface of the tooth, extends from this intersection towards an apical end of the tooth, and comprises the crown center position determined for the tooth (Figure 1, 2, and 4; Page 134, Col. 2, Section “Materials and Methods”: Stainless steel balls (Small Parts, Miramar, Fla), 1.58 mm in diameter, were placed at the approximate mesiodistal and faciolingual centers of the occlusal surfaces, and at the approximate centers of the root apices for single rooted teeth or the centers of the bifurcation or trifurcation at the level of the root apices for multi-rooted teeth. A line connecting the 2 centers on each tooth represented its long axis.; Page 135, Col 2. ¶ 3: The digitization of each tooth's long axis was done in all 3 plane views, each perpendicular to the other 2 views.; Page 137, Col. 1, ¶ 1: If the root center was distal to the crown center, the measurement would be positive; otherwise, it would be negative.).
Tong is considered to be analogous art as it pertains to dental imaging. Therefore, it would have been obvious to one of ordinary skill in the art to combine the system for classifying a tooth condition based on landmarked anthropomorphic measurements (as taught by Ezhov) and the method to measure mesiodistal angulation and faciolingual inclination of each whole tooth (as taught by Tong) before the effective filing date of the claimed invention. The motivation for this combination of references would be Tong teaches measuring the location of the root when measuring the tooth’s mesiodistal angulation and faciolingual inclination which can help with long term stability and best orthodontal treatment outcome (See page 139, Col. 1 - 2).
Regarding claim 7, the Ezhov and Tong combination teaches the method according to claim 5.
Additionally, Tong teaches wherein the orientation of the derived tooth axis is calculated relative to the curved path following the dental arch (Figure 2, 4; Page 136, Col. 1, ¶ 1: The order of digitization was from the maxillary right second molar to the maxillary left second molar, and from the mandibular left second molar to the mandibular right second molar. Figure 4 shows all the white stainless steel markers replaced by the red digitization points. The green lines represented the long axes of the teeth after the digitization was completed in both arches.).
Tong is considered to be analogous art as it pertains to dental imaging. Therefore, it would have been obvious to one of ordinary skill in the art to combine the system for classifying a tooth condition based on landmarked anthropomorphic measurements (as taught by Ezhov) and the method to measure mesiodistal angulation and faciolingual inclination of each whole tooth (as taught by Tong) before the effective filing date of the claimed invention. The motivation for this combination of references would be Tong teaches measuring the location of the root when measuring the tooth’s mesiodistal angulation and faciolingual inclination which can help with long term stability and best orthodontal treatment outcome (See page 139, Col. 1 - 2).
Regarding claim 8, the Ezhov and Tong combination teaches the method according to claim 5.
Additionally, Ezhov and Tong teach wherein the reslice image is generated and displayed as a cross-sectional reslice image comprising said crown center, the plane of the cross-sectional reslice image being perpendicular to the tooth axis of the tooth (Ezhov Figure 9; Tong Figures 1 – 4).
Tong is considered to be analogous art as it pertains to dental imaging. Therefore, it would have been obvious to one of ordinary skill in the art to combine the system for classifying a tooth condition based on landmarked anthropomorphic measurements (as taught by Ezhov) and the method to measure mesiodistal angulation and faciolingual inclination of each whole tooth (as taught by Tong) before the effective filing date of the claimed invention. The motivation for this combination of references would be Tong teaches measuring the location of the root when measuring the tooth’s mesiodistal angulation and faciolingual inclination which can help with long term stability and best orthodontal treatment outcome (See page 139, Col. 1 - 2).
Tong is considered to be analogous art as it pertains to dental imaging. Therefore, it would have been obvious to one of ordinary skill in the art to combine the system for classifying a tooth condition based on landmarked anthropomorphic measurements (as taught by Ezhov) and the method to measure mesiodistal angulation and faciolingual inclination of each whole tooth (as taught by Tong) before the effective filing date of the claimed invention. The motivation for this combination of references would be Tong teaches measuring the location of the root when measuring the tooth’s mesiodistal angulation and faciolingual inclination which can help with long term stability and best orthodontal treatment outcome (See page 139, Col. 1 - 2).
Regarding claim 9, the Ezhov and Tong combination teaches the method according to claim 2.
Additionally, Tong teaches wherein the reslice image is generated and displayed as a mesial-distal reslice image that comprises the tooth axis and is essentially oriented parallel to the curved path at the position of one of the teeth or a buccal/labial-oral reslice image that comprises the tooth axis and is essentially oriented perpendicular to the curved path at the position of one of the teeth (Figure 1 – 3, 5, and 6; Page 134, Col. 2, Section “Material and Methods”: A mesiodistal plane was created for each tooth that was perpendicular to the horizontal (archwire) plane. This tooth-specific reference plane passed through the mesial and distal interproximal points marked on the archwires with crimpable stops.; Figure 6: A, Mesiodistal angulation was measured in the mesiodistal plane and defined as the angle formed by the projection of the tooth's long axis (green line) and the red line that represented the faciolingual plane and the mesiodistal plane intersection.).
Tong is considered to be analogous art as it pertains to dental imaging. Therefore, it would have been obvious to one of ordinary skill in the art to combine the system for classifying a tooth condition based on landmarked anthropomorphic measurements (as taught by Ezhov) and the method to measure mesiodistal angulation and faciolingual inclination of each whole tooth (as taught by Tong) before the effective filing date of the claimed invention. The motivation for this combination of references would be Tong teaches measuring the location of the root when measuring the tooth’s mesiodistal angulation and faciolingual inclination which can help with long term stability and best orthodontal treatment outcome (See page 139, Col. 1 - 2).
Regarding claim 10, the Ezhov and Tong combination teaches the method according to claim 1.
Additionally Ezhov teaches the second artificial neural network (¶ 0011: The processor is configured to detect or classify the conditions for each defined anatomical structure within the cropped image by a detection module or classification layer. In one embodiment, the classification is achieved using any one of a fully convolutional network or plain classification convolutional neural network (FCN/CNN).).
Additionally, Tong teaches (Figure 7; Page 140; Fig. 7: Diagram showing the 3-dimensional relationship: a, b, c, d, and g each at a corner of a cubic with each side 20 mm long. The center of the crown is placed at point c. cd points mesiodistally; cg points faciolingually, and points cb occlusogingivally; cb, 20mm appical; be, 5mm distal; bf, 10mm lingual; r, designated root point; and yellow arrow, presumed long axis of the tooth.; Examiner’s note: Figure 7 of Tong discloses 3 dimensional offsets from a tooth crown center. As the “offset vector” of claim 10 is with respect to “a position within said voxel image”, under broadest reasonable interpretation any 3-dimensional measurement from a crown center point to another point is understood to read on this claim.).
Tong is considered to be analogous art as it pertains to dental imaging. Therefore, it would have been obvious to one of ordinary skill in the art to combine the system for classifying a tooth condition based on landmarked anthropomorphic measurements (as taught by Ezhov) and the method to measure mesiodistal angulation and faciolingual inclination of each whole tooth (as taught by Tong) before the effective filing date of the claimed invention. The motivation for this combination of references would be Tong teaches measuring the location of the root when measuring the tooth’s mesiodistal angulation and faciolingual inclination which can help with long term stability and best orthodontal treatment outcome (See page 139, Col. 1 - 2).
Regarding claim 11, the Ezhov and Tong combination teaches the method according to claim 2.
Additionally, Ezhov teaches wherein determining the crown center positions further comprises assigning a tooth label (¶ 0041: In an alternative embodiment, the system provides 2-class segmentation, which includes labelling or classification, if the localization comprises tooth or not. The system additionally outputs assignment of each tooth p/v to a separate "tooth instance".; ¶ 0076: In parallel with the previous step, apply the third, 2D R-CNN style instance segmentation model, to the generated panorama image to acquire 2D tooth masks and labels.).
Additionally Tong teaches wherein determining the crown center positions further comprises assigning a tooth label for each determined crown center position using said detected anatomical landmarks and by analyzing the relative positions of said crown center positions (Figure 4; Page 134, Col. 2, Section “Material and Methods”: Stainless steel balls (Small Parts, Miramar, Fla), 1.58 mm in diameter, were placed at the approximate mesiodistal and faciolingual centers of the occlusal surfaces, and at the approximate centers of the root apices for single rooted teeth or the centers of the bifurcation or trifurcation at the level of the root apices for multi-rooted teeth. A line connecting the 2 centers on each tooth represented its long axis.; Page 136, Col 1, ¶ 1: The order of digitization was from the maxillary right second molar to the maxillary left second molar, and from the mandibular left second molar to the mandibular right second molar. Figure 4 shows all the white
stainless steel markers replaced by the red digitization points. The green lines represented the long axes of the teeth after the digitization was completed in both arches.).
Tong is considered to be analogous art as it pertains to dental imaging. Therefore, it would have been obvious to one of ordinary skill in the art to combine the system for classifying a tooth condition based on landmarked anthropomorphic measurements (as taught by Ezhov) and the method to measure mesiodistal angulation and faciolingual inclination of each whole tooth (as taught by Tong) before the effective filing date of the claimed invention. The motivation for this combination of references would be Tong teaches measuring the location of the root when measuring the tooth’s mesiodistal angulation and faciolingual inclination which can help with long term stability and best orthodontal treatment outcome (See page 139, Col. 1 - 2).
Regarding claim 19, Ezhov teaches a computer implemented method for automatically generating and displaying, derived from 3D image data (¶ 0035: In another embodiment, the input data is 3-Dimensional (3D) image data.), a 2D image of a portion of a patient's maxillofacial anatomy (¶ 0008: Further embodiments disclosed include a method and system for constructing a panorama with elements of interest (EoI) emphasized of a teeth arch or any point of interest in an oral-maxillofacial complex.), said method comprising the steps:
receiving 3D image data comprising a voxel image volume representing the maxillofacial anatomy of the patient (¶ 0035: In another embodiment, the input data is 3-Dimensional (3D) image data. The volumetric image processor 103a is configured to receive the volumetric image data from the radio-image gathering source.), the voxel image volume including teeth of the patient and each voxel of the voxel image volume being associated with a radiation intensity value (¶ 0036: Initially, the volumetric image data is pre-processed, which involves conversion of 3-D pixel array into an array of Hounsfield Unit (HU) radio intensity measurements.; ¶ 0050: At step 304, a tooth or anatomical structure inside the pre-processed and parsed i/v.i is localized and identified by tooth number.),
detecting one or more anatomical landmarks in said voxel image volume using a first artificial neural network (¶ 0036: The processor 103 is further configured to localize anatomical structures residing in the single image frame field of view by assigning at least one of each a pixel or voxel (p/v) a distinct anatomical structure by the voxel parsing engine 104… In one embodiment, localization is achieved using any one of fully convolutional network or plain classification convolutional neural network (FCN/CNN), such as a V-Net-based fully convolutional neural network. In one embodiment, the V-Net is a 3D generalization of UN et.),
using a second artificial neural network for determining (¶ 0011: The processor is configured to detect or classify the conditions for each defined anatomical structure within the cropped image by a detection module or classification layer. In one embodiment, the classification is achieved using any one of a fully convolutional network or plain classification convolutional neural network (FCN/CNN).; ¶ 0037: The processor 103 is further configured to select all p/v belonging to the localized anatomical structure by finding a minimal bounding rectangle around the p/v and the surrounding region for cropping as a defined anatomical structure by the localization layer.), and
generating the 2D image as a reslice image from the voxel image volume (¶ 0050: At step 308, a visual report is reconstructed with localized and defined anatomical structure. In some embodiments, the visual reports include, but not limited to, an endodontic report (with focus on tooth's root/canal system and its treatment state), an implantation report (with focus on the area where the tooth is missing), and a dystopic tooth report for tooth extraction (with focus on the area of dystopic/ impacted teeth). ¶ 0052: At step 320, a visual report is reconstructed with defined and localized anatomical structure. At step 322, conditions for each defined anatomical structure is classified within the cropped image by the classification layer.; Including ¶ 0072 and 0075).
detecting the center of the left and/or right condyle head using the first artificial neural network (¶ 0086: As a part of mandible/maxilla, TMJ parts: Condyle and temporal bone (this step is optional, landmarks could be detected) may be segmented. Then, several landmarks on condyle and temporal bone may be detected and distances between them measured.), wherein the curved path following the dental arch is calculated using the center of the left and/or right condyle head as endpoints (Figure 9, ¶ 0068: In general, two types of panoramas may be constructed using the above mentioned method: (1) a general panorama; and (2) a split panorama. A general panorama includes Rol for all the teeth present, a whole mandible with TMJs (emphasis added), and a lower part of maxilla with sinuses cropped to the middle.);
wherein the reslice image is a panoramic image generated based on said curved path following the arch form of the patient's teeth (¶ 0067: The first step concludes in voxel coordinates operations, such as extracting teeth arch and unfolding a study image into 3D panoramic ribbon (curved sub-volume that passes along the teeth arch). Teeth arch is extracted using segmentations of teeth and anatomy, mandible and mandibular canals in particular… Then, construct a transformation grid that allows the arch to unfold in straight line, resulting in a panoramic ribbon.).
Ezhov does not explicitly teach determining a crown center position; and generating the 2D image as a reslice image based on at least one crown center position.
However, Tong does teach determining a crown center position (Page 135, Col. 2, ¶ 3: Parallel movements of the sagittal, coronal, and axial planes were made so that each would pass through the center of the white stainless steel marker representing either the crown or the root point of each tooth (Figs 2 and 3).); and generating the 2D image as a reslice image based on at least one crown center position (Figure 2; Figure 2: Locating the maxillary right central incisor crown point before digitization: parallel movements of the sagittal (red), coronal (green), and axial (blue) planes were made to intersect at the center of the stainless steel ball representing the tooth's crown point.).
Tong is considered to be analogous art as it pertains to dental imaging. Therefore, it would have been obvious to one of ordinary skill in the art to combine the system for classifying a tooth condition based on landmarked anthropomorphic measurements (as taught by Ezhov) and the method to measure mesiodistal angulation and faciolingual inclination of each whole tooth (as taught by Tong) before the effective filing date of the claimed invention. The motivation for this combination of references would be Tong teaches measuring the location of the root when measuring the tooth’s mesiodistal angulation and faciolingual inclination which can help with long term stability and best orthodontal treatment outcome (See page 139, Col. 1 - 2).
Regarding claim 20, Ezhov teaches a computer implemented method for automatically generating and displaying, derived from 3D image data (¶ 0035: In another embodiment, the input data is 3-Dimensional (3D) image data.), a 2D image of a portion of a patient's maxillofacial anatomy (¶ 0008: Further embodiments disclosed include a method and system for constructing a panorama with elements of interest (EoI) emphasized of a teeth arch or any point of interest in an oral-maxillofacial complex.), said method comprising the steps:
receiving 3D image data comprising a voxel image volume representing the maxillofacial anatomy of the patient (¶ 0035: In another embodiment, the input data is 3-Dimensional (3D) image data. The volumetric image processor 103a is configured to receive the volumetric image data from the radio-image gathering source.), the voxel image volume including teeth of the patient and each voxel of the voxel image volume being associated with a radiation intensity value (¶ 0036: Initially, the volumetric image data is pre-processed, which involves conversion of 3-D pixel array into an array of Hounsfield Unit (HU) radio intensity measurements.; ¶ 0050: At step 304, a tooth or anatomical structure inside the pre-processed and parsed i/v.i is localized and identified by tooth number.),
detecting one or more anatomical landmarks in said voxel image volume using a first artificial neural network (¶ 0036: The processor 103 is further configured to localize anatomical structures residing in the single image frame field of view by assigning at least one of each a pixel or voxel (p/v) a distinct anatomical structure by the voxel parsing engine 104… In one embodiment, localization is achieved using any one of fully convolutional network or plain classification convolutional neural network (FCN/CNN), such as a V-Net-based fully convolutional neural network. In one embodiment, the V-Net is a 3D generalization of UN et.),
using a second artificial neural network for determining (¶ 0011: The processor is configured to detect or classify the conditions for each defined anatomical structure within the cropped image by a detection module or classification layer. In one embodiment, the classification is achieved using any one of a fully convolutional network or plain classification convolutional neural network (FCN/CNN).; ¶ 0037: The processor 103 is further configured to select all p/v belonging to the localized anatomical structure by finding a minimal bounding rectangle around the p/v and the surrounding region for cropping as a defined anatomical structure by the localization layer.), and
generating the 2D image as a reslice image from the voxel image volume (¶ 0050: At step 308, a visual report is reconstructed with localized and defined anatomical structure. In some embodiments, the visual reports include, but not limited to, an endodontic report (with focus on tooth's root/canal system and its treatment state), an implantation report (with focus on the area where the tooth is missing), and a dystopic tooth report for tooth extraction (with focus on the area of dystopic/ impacted teeth). ¶ 0052: At step 320, a visual report is reconstructed with defined and localized anatomical structure. At step 322, conditions for each defined anatomical structure is classified within the cropped image by the classification layer.; Including ¶ 0072 and 0075).
calculating a curved path following a dental arch of the patient's teeth using said one or more anatomical landmarks and/or by fitting a curve to the determined crown center positions and using the curved path as a reference for generating the reslice image (¶ 0067: The first step concludes in voxel coordinates operations, such as extracting teeth arch and unfolding a study image into 3D panoramic ribbon (curved sub-volume that passes along the teeth arch). Teeth arch is extracted using segmentations of teeth and anatomy, mandible and mandibular canals in particular.).
wherein the reslice image is generated and displayed as a cross-sectional reslice image comprising said crown center, the plane of the cross-sectional reslice image being perpendicular to the tooth axis of the tooth (Figure 9)
Ezhov does not explicitly teach determining a crown center position; generating the 2D image as a reslice image based on at least one crown center position; analyzing the 3D image data within at least an image region surrounding the determined crown center position of one of the teeth to derive a tooth axis, wherein the tooth axis intersects a coronal crown surface of the tooth, extends from this intersection towards an apical end of the tooth, and comprises the crown center position determined for the tooth; and wherein the reslice image is generated and displayed as a mesial-distal reslice image that comprises the tooth axis and is essentially oriented parallel to the curved path at the position of one of the teeth or a buccal/labial-oral reslice image that comprises the tooth axis and is essentially oriented perpendicular to the curved path at the position of one of the teeth.
However, Tong does teach determining a crown center position (Page 135, Col. 2, ¶ 3: Parallel movements of the sagittal, coronal, and axial planes were made so that each would pass through the center of the white stainless steel marker representing either the crown or the root point of each tooth (Figs 2 and 3).); and generating the 2D image as a reslice image based on at least one crown center position (Figure 2; Figure 2: Locating the maxillary right central incisor crown point before digitization: parallel movements of the sagittal (red), coronal (green), and axial (blue) planes were made to intersect at the center of the stainless steel ball representing the tooth's crown point.);
analyzing the 3D image data within at least an image region surrounding the determined crown center position of one of the teeth to derive a tooth axis, wherein the tooth axis intersects a coronal crown surface of the tooth, extends from this intersection towards an apical end of the tooth, and comprises the crown center position determined for the tooth (Figure 1, 2, and 4; Page 134, Col. 2, Section “Materials and Methods”: Stainless steel balls (Small Parts, Miramar, Fla), 1.58 mm in diameter, were placed at the approximate mesiodistal and faciolingual centers of the occlusal surfaces, and at the approximate centers of the root apices for single rooted teeth or the centers of the bifurcation or trifurcation at the level of the root apices for multi-rooted teeth. A line connecting the 2 centers on each tooth represented its long axis.; Page 135, Col 2. ¶ 3: The digitization of each tooth's long axis was done in all 3 plane views, each perpendicular to the other 2 views.; Page 137, Col. 1, ¶ 1: If the root center was distal to the crown center, the measurement would be positive; otherwise, it would be negative.).
wherein the reslice image is generated and displayed as a cross-sectional reslice image comprising said crown center, the plane of the cross-sectional reslice image being perpendicular to the tooth axis of the tooth (Figures 1 - 4); and
wherein the reslice image is generated and displayed as a mesial-distal reslice image that comprises the tooth axis and is essentially oriented parallel to the curved path at the position of one of the teeth or a buccal/labial-oral reslice image that comprises the tooth axis and is essentially oriented perpendicular to the curved path at the position of one of the teeth (Figure 1 – 3, 5, and 6; Page 134, Col. 2, Section “Material and Methods”: A mesiodistal plane was created for each tooth that was perpendicular to the horizontal (archwire) plane. This tooth-specific reference plane passed through the mesial and distal interproximal points marked on the archwires with crimpable stops.; Figure 6: A, Mesiodistal angulation was measured in the mesiodistal plane and defined as the angle formed by the projection of the tooth's long axis (green line) and the red line that represented the faciolingual plane and the mesiodistal plane intersection.).
Tong is considered to be analogous art as it pertains to dental imaging. Therefore, it would have been obvious to one of ordinary skill in the art to combine the system for classifying a tooth condition based on landmarked anthropomorphic measurements (as taught by Ezhov) and the method to measure mesiodistal angulation and faciolingual inclination of each whole tooth (as taught by Tong) before the effective filing date of the claimed invention. The motivation for this combination of references would be Tong teaches measuring the location of the root when measuring the tooth’s mesiodistal angulation and faciolingual inclination which can help with long term stability and best orthodontal treatment outcome (See page 139, Col. 1 - 2).
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Ezhov et al (U.S. Patent Publication No. 2021/0217170 A1, hereinafter “Ezhov”) in view of Tong et al (Hongsheng Tong "A new method to measure mesiodistal angulation and faciolingual inclination of each whole tooth with volumetric cone-beam computed tomography images”, American Journal of Orthodontics and Dentofacial Orthopedics, Volume 142, Issue 1, 2012,Pages 133-143, ISSN 0889-5406, hereinafter “Tong”) and further in view of Anassari Moin et al (U.S. Patent Publication No. 2020/0320685 A1, hereinafter “Anassari”).
Regarding claim 6, the Ezhov and Tong combination teaches the method according to claim 5.
Ezhov does not explicitly teach wherein deriving the tooth axis comprises, starting from a cross-section of the tooth including the estimated crown center position, the step of tracking a corresponding position in a next adjacent cross-section and proceeding with tracking corresponding positions in adjacent cross-sections along the tooth, in particular in a direction towards the apical side of the tooth, and the step of calculating the tooth axis based on these corresponding positions.
However, Anassari teach wherein deriving the tooth axis comprises, starting from a cross-section of the tooth including the estimated crown center position, the step of tracking a corresponding position in a next adjacent cross-section and proceeding with tracking corresponding positions in adjacent cross-sections along the tooth, in particular in a direction towards the apical side of the tooth, and the step of calculating the tooth axis based on these corresponding positions (¶ 0105: In yet another embodiment, the 3D tooth structure may be sliced at a pre-determined point of the longitudinal axis of the tooth structure. For example, in 438 the tooth structure may be sliced at a point on the longitudinal axis which is at a predetermined distance from the bottom side of the tooth structure. This way a 2D slice of data may be determined. In this 2D slice the two points with the greatest distance from each other may be determined. The line between these points may be referred to as the lateral axis of the tooth structure.).
Anassari is considered to be analogous art as it pertains to dental image processing. Therefore, it would have been obvious to one of ordinary skill in the art to combine the system for classifying a tooth condition based on landmarked anthropomorphic measurements (as taught by Ezhov) and the automated classification and taxonomy of 3D teeth data (as taught by Anassari) before the effective filing date of the claimed invention. The motivation for this combination of references would be the system of Anassari provides positional features to allow a deep neural network to efficiently and accurately classify voxels of a 3D image data stack to reduce the risk of overfitting (See ¶ 0150).
This motivation for the combination of Ezhov, Tong, and Anassari 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).
Claims 12, 14, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Ezhov et al (U.S. Patent Publication No. 2021/0217170 A1, hereinafter “Ezhov”) in view of Tong et al (Hongsheng Tong "A new method to measure mesiodistal angulation and faciolingual inclination of each whole tooth with volumetric cone-beam computed tomography images”, American Journal of Orthodontics and Dentofacial Orthopedics, Volume 142, Issue 1, 2012,Pages 133-143, ISSN 0889-5406, hereinafter “Tong”) and further in view of Keustermans et al (U.S. Patent Publication No. 2019/0147666 A1, hereinafter “Keustermans”).
Regarding claim 12, the Ezhov and Tong combination teaches the method according to claim 11.
Additionally, Ezhov teaches further comprising the step of deriving (¶ 0050: In some embodiments, the visual reports include, but not limited to, an endodontic report (with focus on tooth's root/canal system and its treatment state), an implantation report (with focus on the area where the tooth is missing) (emphasis added), and a dystopic tooth report for tooth extraction (with focus on the area of dystopic/ impacted teeth).; ¶ 0059: In the case where a tooth is missing from ground truth and the model predicted any positive p/v (i.e. the ground truth bounding box is not defined), localization IoU is set to 0.).
Ezhov does not explicitly teach deriving a virtual crown center position for any tooth missing in the 3D image data of the patient.
However, Keustermans does teach deriving a virtual crown center position for any tooth missing in the 3D image data of the patient (¶ 0016: The shape, position and/or orientation of a tooth or teeth to be included in a dental restoration can subsequently be estimated based on the shape, position and/or orientation of the tooth or teeth in said adapted virtual teeth setup, which correspond to the patient's missing teeth.; ¶ 0047: In order to enable such matching of landmarks it is preferred that a user indicates such one or more landmarks on one or more teeth of the digitized surface mesh wherein said land marks correspond with predefined landmarks on the virtual teeth setup. In a particular embodiment said one landmark is the midpoint of the upper crown surface.).
Keustermans is considered to be analogous art as it pertains to dental image processing. Therefore, it would have been obvious to one of ordinary skill in the art to combine the system for classifying a tooth condition based on landmarked anthropomorphic measurements (as taught by Ezhov) and the method for estimating at least one of shape, position, and orientation of a dental restoration (as taught by Keustermans) before the effective filing date of the claimed invention. The motivation for this combination of references would be the system of Keustermans represents virtual teeth by a translation vector, a rotation matrix, and a polygonal surface mesh representing the shape of the teeth in relation to a surface representation of the patient’s intraoral situation, allowing for improved flexibility and adaptability of the represented tooth and allowing the user to modify the position, orientation, or shape of the tooth to introduce minor modifications to the proposed solution (See ¶ 0026).
This motivation for the combination of Ezhov, Tong, and Keustermans 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 14, the Ezhov, Tong, and Keustermans combination teaches the method according to claim 12.
Additionally, Tong teaches wherein the method further comprises displaying the 3D image data and displaying a marker at the position of each determined crown center position and/or each virtual crown center position (Figure 1 - 4; Page 134, Col. 2, Section “Material and Methods”: Stainless steel balls (Small Parts, Miramar, Fla), 1.58 mm in diameter, were placed at the approximate mesiodistal and faciolingual centers of the occlusal surfaces, and at the approximate centers of the root apices for single rooted teeth or the centers of the bifurcation or trifurcation at the level of the root apices for multi-rooted teeth. A line connecting the 2 centers on each tooth represented its long axis.;).
Tong is considered to be analogous art as it pertains to dental imaging. Therefore, it would have been obvious to one of ordinary skill in the art to combine the system for classifying a tooth condition based on landmarked anthropomorphic measurements (as taught by Ezhov) and the method to measure mesiodistal angulation and faciolingual inclination of each whole tooth (as taught by Tong) before the effective filing date of the claimed invention. The motivation for this combination of references would be Tong teaches measuring the location of the root when measuring the tooth’s mesiodistal angulation and faciolingual inclination which can help with long term stability and best orthodontal treatment outcome (See page 139, Col. 1 - 2).
Regarding claim 16, the Ezhov, Tong, and Keustermans combination teaches the method according to claim 12.
Additionally, Tong teaches wherein calculating the curved path following the dental arch of the patient's teeth comprises fitting the curve of the path to both the determined crown center positions of the teeth represented in the 3D image data and each virtual crown center position (Figure 1 – 5; Page 135, Col 2, ¶ 3: The digitization of each tooth's long axis was done in all 3 plane views, each perpendicular to the other 2 views. Parallel movements of the sagittal, coronal, and axial planes were made so that each would pass through the center of the white stainless steel marker representing either the crown or the root point of each tooth (Figs 2 and 3).; Figure 5: The maxillary arch on the right side was digitized based on 4 points along the archwire relative to the following tooth positions: midincisor, right canine, right second premolar, and right second molar (dots). The left yellow side half arch was the mirror image of the right side half. The tooth-specific coordinate system was based on the arch form and the crown point of each tooth:).
Tong is considered to be analogous art as it pertains to dental imaging. Therefore, it would have been obvious to one of ordinary skill in the art to combine the system for classifying a tooth condition based on landmarked anthropomorphic measurements (as taught by Ezhov) and the method to measure mesiodistal angulation and faciolingual inclination of each whole tooth (as taught by Tong) before the effective filing date of the claimed invention. The motivation for this combination of references would be Tong teaches measuring the location of the root when measuring the tooth’s mesiodistal angulation and faciolingual inclination which can help with long term stability and best orthodontal treatment outcome (See page 139, Col. 1 - 2).
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Ezhov et al (U.S. Patent Publication No. 2021/0217170 A1, hereinafter “Ezhov”) in view of Tong et al (Hongsheng Tong "A new method to measure mesiodistal angulation and faciolingual inclination of each whole tooth with volumetric cone-beam computed tomography images”, American Journal of Orthodontics and Dentofacial Orthopedics, Volume 142, Issue 1, 2012,Pages 133-143, ISSN 0889-5406, hereinafter “Tong”) and further in view of Keustermans et al (U.S. Patent Publication No. 2019/0147666 A1, hereinafter “Keustermans”) and Lee et al (U.S. Patent Publication No. 2024/0177440 A1, hereinafter “Lee”).
Regarding claim 13, the Ezhov, Tong, and Keustermans combination teaches the method according to claim 12.
Ezhov does not explicitly teach the step of generating and displaying a tooth chart comprising selectable icons denoting teeth represented in the 3D image data and/or any tooth missing in the 3D image data, wherein upon selection of one of the icons a 2D image of the tooth of the selected icon is displayed and includes at least the reslice image.
However, Lee teaches further comprising the step of generating and displaying a tooth chart comprising selectable icons denoting teeth represented in the 3D image data and/or any tooth missing in the 3D image data (Figure 7; ¶ 0140: FIG. 7 illustrates an example of a graphical user interface provided by a data processing device in relation to a missing tooth, according to one embodiment.; ¶0143: In this way, an input for changing a corresponding missing tooth to a planned prosthetic tooth state as illustrated in FIG. 6 and an input enabling the corresponding missing tooth to be recognized as an existing tooth state as in the example of FIG. 7 may coexist with each other for the missing tooth.), wherein upon selection of one of the icons a 2D image of the tooth of the selected icon is displayed and includes at least the reslice image. (Figure 6 – 9; Ref. No. 630; ¶ 0142: Actually, a tooth 630 is placed between a scanned tooth of the tooth number 23 and a scanned tooth of the tooth number 26 in the first region 610, and accordingly, the tooth 630 may be a tooth of the tooth number 24 or the tooth number 25.; ¶ 0145: Referring to FIG. 8, when a user input for selecting a tooth number 24 displayed as a missing tooth state from an image 621 of a second region 620 is received by a user, the data processing device 100 may output a menu 800 in response to the user input. The menu 800 may include a first icon 810 for receiving a user input designating a missing tooth as a planned prosthetic tooth, and a second icon 820 for receiving a user input for recognizing a tooth corresponding to a tooth number of the missing tooth among scanned teeth displayed in a first region 610 to assign a tooth number to the recognized tooth.; Examiner’s note: Figure’s 6 – 8 show a 2D prosthetic tooth being placed in a 2D reslice image of the patients mouth after being selected by the user as a “missing tooth”.)
Lee is considered to be analogous art as it pertains to dental image processing. Therefore, it would have been obvious to one of ordinary skill in the art to combine the system for classifying a tooth condition based on landmarked anthropomorphic measurements (as taught by Ezhov) and the three-dimensional intraoral model processing device (as taught by Lee) before the effective filing date of the claimed invention. The motivation for this combination of references would be the system of Lee utilizes an iterative closest point algorithm to reconstruct 2D or 3D surfaces from scan data, the algorithm reducing an error metric representing a difference from a source to a reference. (See ¶ 0125).
This motivation for the combination of Ezhov, Tong, Keustermans, and Lee 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).
Claims 15, 17, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Ezhov et al (U.S. Patent Publication No. 2021/0217170 A1, hereinafter “Ezhov”) in view of Tong et al (Hongsheng Tong "A new method to measure mesiodistal angulation and faciolingual inclination of each whole tooth with volumetric cone-beam computed tomography images”, American Journal of Orthodontics and Dentofacial Orthopedics, Volume 142, Issue 1, 2012,Pages 133-143, ISSN 0889-5406, hereinafter “Tong”) and further in view of Keustermans et al (U.S. Patent Publication No. 2019/0147666 A1, hereinafter “Keustermans”) and Bradenburg et al (Brandenburg LS, Berger L, Schwarz SJ, Meine H, Weingart JV, Steybe D, Spies BC, Burkhardt F, Schlager S, Metzger MC. Reconstruction of dental roots for implant planning purposes: a feasibility study. Int J Comput Assist Radiol Surg. 2022 Oct;17(10):1957-1968., hereinafter “Bradenburg”)
Regarding claim 15, the Ezhov, Tong, and Keustermans combination teaches the method according to claim 12.
Additionally, Keustermans teaches further comprising the steps:
(¶ 0260: For the case of a patient missing multiple anterior teeth illustrated in FIG. 13, the estimated teeth are positioned too far to the front and do not follow the anatomical dental arch (FIG. 13A). Following this observation, the user needs to input an anatomically more desirable position of only one missing tooth, in this example the right central incisor (FIG. 13B), to generate an updated estimate for all missing teeth.; ¶ 0261: Thereafter, the virtual teeth setup algorithm constrained by these inputted modifications is used to calculate an updated estimate for the position, shape and orientation of all missing teeth.).
Keustermans is considered to be analogous art as it pertains to dental image processing. Therefore, it would have been obvious to one of ordinary skill in the art to combine the system for classifying a tooth condition based on landmarked anthropomorphic measurements (as taught by Ezhov) and the method for estimating at least one of shape, position, and orientation of a dental restoration (as taught by Keustermans) before the effective filing date of the claimed invention. The motivation for this combination of references would be the system of Keustermans represents virtual teeth by a translation vector, a rotation matrix, and a polygonal surface mesh representing the shape of the teeth in relation to a surface representation of the patient’s intraoral situation, allowing for improved flexibility and adaptability of the represented tooth and allowing the user to modify the position, orientation, or shape of the tooth to introduce minor modifications to the proposed solution (See ¶ 0026).
Ezhov does not explicitly teach extrapolating a virtual tooth axis for the at least one missing tooth, wherein the virtual tooth axis comprises the virtual crown center position of the missing tooth.
However, Bradenburg does teach extrapolating a virtual tooth axis for the at least one missing tooth, wherein the virtual tooth axis comprises the virtual crown center position of the missing tooth (Figure 9 and 10; Page 1958, Col. 1, ¶ 4: In the context of implant planning, statistical shape modeling (SSM) might predict the tooth axis of missing teeth, based on the tooth crown morphology of remaining teeth)
Bradenburg is considered to be analogous art as it pertains to dental image processing. Therefore, it would have been obvious to one of ordinary skill in the art to combine the system for classifying a tooth condition based on landmarked anthropomorphic measurements (as taught by Ezhov) and the reconstruction of dental roots for implanting purposes (as taught by Bradenburg) before the effective filing date of the claimed invention. The motivation for this combination of references would be the system of Bradenburg is able to effectively reconstruct the arches of upper and lower teeth when missing teeth are present. (See Page 1957 “Results”).
This motivation for the combination of Ezhov, Tong, Keustermans, and Bradenburg 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 17, the Ezhov, Tong, Keustermans, and Bradenburg combination teaches the method according to claim 15.
Additionally, Tong teaches further comprising the step of generating and displaying a reslice image of a reslice plane comprising the (Figure 5; page 136, Col. 2, ¶ 1: Once the arch form was digitized, the custom USC root vector analysis program would automatically construct another 3-plane coordinate system consisting of multiple coordinates, each specific for only 1 tooth for its mesiodistal angulation and faciolingual inclination measurements).
Tong is considered to be analogous art as it pertains to dental imaging. Therefore, it would have been obvious to one of ordinary skill in the art to combine the system for classifying a tooth condition based on landmarked anthropomorphic measurements (as taught by Ezhov) and the method to measure mesiodistal angulation and faciolingual inclination of each whole tooth (as taught by Tong) before the effective filing date of the claimed invention. The motivation for this combination of references would be Tong teaches measuring the location of the root when measuring the tooth’s mesiodistal angulation and faciolingual inclination which can help with long term stability and best orthodontal treatment outcome (See page 139, Col. 1 - 2).
Additionally, Bradenburg teaches virtual tooth axes (Figure 9 and 10; Page 1958, Col. 1, ¶ 4: In the context of implant planning, statistical shape modeling (SSM) might predict the tooth axis of missing teeth, based on the tooth crown morphology of remaining teeth)
Bradenburg is considered to be analogous art as it pertains to dental image processing. Therefore, it would have been obvious to one of ordinary skill in the art to combine the system for classifying a tooth condition based on landmarked anthropomorphic measurements (as taught by Ezhov) and the reconstruction of dental roots for implanting purposes (as taught by Bradenburg) before the effective filing date of the claimed invention. The motivation for this combination of references would be the system of Bradenburg is able to effectively reconstruct the arches of upper and lower teeth when missing teeth are present. (See Page 1957 “Results”).
Regarding claim 18, the Ezhov, Tong, Keustermans, and Bradenburg combination teaches the method according to claim 15.
Additionally, Tong teaches wherein the method further comprises displaying the 3D image data (Figure 1 - 4) and displaying for each crown center position a line corresponding to the tooth axis and/or for each virtual crown center position a line corresponding to the virtual tooth axis (Tong Figure 5).
Tong is considered to be analogous art as it pertains to dental imaging. Therefore, it would have been obvious to one of ordinary skill in the art to combine the system for classifying a tooth condition based on landmarked anthropomorphic measurements (as taught by Ezhov) and the method to measure mesiodistal angulation and faciolingual inclination of each whole tooth (as taught by Tong) before the effective filing date of the claimed invention. The motivation for this combination of references would be Tong teaches measuring the location of the root when measuring the tooth’s mesiodistal angulation and faciolingual inclination which can help with long term stability and best orthodontal treatment outcome (See page 139, Col. 1 - 2).
Additionally, Bradenburg teaches for each virtual crown center position a line corresponding to the virtual tooth axis (Figure 9 and 10: Paramedian cut of the CBCT-scan superimposed with a dental wax-up and the SSM-based tooth axis reconstruction (both in yellow).)
Bradenburg is considered to be analogous art as it pertains to dental image processing. Therefore, it would have been obvious to one of ordinary skill in the art to combine the system for classifying a tooth condition based on landmarked anthropomorphic measurements (as taught by Ezhov) and the reconstruction of dental roots for implanting purposes (as taught by Bradenburg) before the effective filing date of the claimed invention. The motivation for this combination of references would be the system of Bradenburg is able to effectively reconstruct the arches of upper and lower teeth when missing teeth are present. (See Page 1957 “Results”).
Conclusion
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/ANDREW B. JONES/Examiner, Art Unit 2667 /MATTHEW C BELLA/Supervisory Patent Examiner, Art Unit 2667
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