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 .
Specification
The disclosure is objected to because of the following informalities:
Paragraph [0011] discloses “angulation determination algorithms”; examiner suggests adding further detail to this.
Appropriate correction is required.
Claim Objections
Claims 1, 3, and 7-8 are objected to because of the following informalities:
Claim 1 recites the limitation(s): “based on the anatomical dental features” on PG(s) 1, Line(s) 1-2; examiner suggests amending this to “based on anatomical dental features”;
Claim 1 recites the limitation(s): “images of the teeth” on PG(s) 1, Line(s) 3; examiner suggests amending this to “images of teeth”;
Claim 3 recites the limitation(s): “sending the information” on PG(s) 1, Line(s) 16-17; examiner suggests amending this to “sending information”;
Claim 7 recites the limitation(s): “regarding the x-ray quality” on PG(s) 2, Line(s) 12; examiner suggests amending this to “regarding an x-ray quality”; and
Claim 8 recites the limitation(s): “improving the angulation determination algorithms” on PG(s) 3, Line(s) 3; examiner suggests amending this to “improving angulation determination algorithms”.Appropriate correction is required.
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 1-4 and 7-8 are rejected under 35 U.S.C. 103 as being unpatentable over Subramanyan et al. (US 20220151576 A1), hereinafter referenced as Subramanyan, in view of Li et al. (US 20240122463 A1), hereinafter referenced as Li.
Regarding Claim 1, Subramanyan discloses a method of determining precise dental x-ray angulation based on the anatomical dental features of a patient (Subramanyan, [0067]: teaches a method that describes "an x-ray source 10 directs radiant energy through a subject tooth 14 or other feature <read on anatomical dental features of patient> toward an intraoral detector 20, over a range of angles <read on determining precise dental x-ray angulation>"), comprising:
capturing one or more images of the teeth of the patient (Subramanyan, [0121]: teaches an alignment apparatus being provided "to assist in capturing a series of images of the same tooth or other structure <read on teeth of patient>, taken in quick succession and each at a slightly different angle, for forming a limited-angle volume image");
[[sending the images to a server;]]
customizing one or more x-ray angles based on algorithmic analysis of the images (Subramanyan, [0101]: teaches an operator console display 28 on a computer display monitor indicates alignment information for the operator, where it recommends the needed adjustment settings <read on customizing x-ray angles>; [0101]: further teaches "a control logic processor 26 employing "conventional trigonometric calculations based on the received signals from, or other detectable features of, detectable elements 30 and the known position of sensor 24 with relation to x-ray source 10"; [0102]: teaches an alignment apparatus projecting "an image onto the cheek or other portion of the dental patient as a guide for proper alignment of the x-ray tube with respect to the position and angle of the detector," where "control logic processor 26 obtains alignment information <read on algorithmic analysis of images>);
displaying a tooth model of the patient on a display screen (Subramanyan, [0124]: teaches the system obtaining updated position and angle data that correspond to each imaging position in the series of images that are obtained, where "this data then provides the needed reference geometry for reconstruction of the 3-D volume image <read on displaying tooth model of patient> from a series of 2-D image captures"; Note: it should be noted that although not expressly stated, it is common in the art to display a reconstructed 3D volume image onto a screen <read on display screen> for viewing);
representing, on the display screen, the teeth in an initial color (Subramanyan, [0115]: teaches the system using color "to help indicate the relative amount of alignment offset in various ways," such as displaying the indicia 12 and position 42 in different colors A <read on representing teeth in initial color> on a display <read on display screen> to "help to guide the technician in adjusting the angle of the x-ray tube until both aim indicia 12 and position 42 display in the same color"); and
updating the display to turn the corresponding teeth a final color to indicate completion as an x-ray angulation device achieves the customized angles (Subramanyan, [0115]: teaches the system <read on x-ray angulation device> using color "to help indicate the relative amount of alignment offset in various ways," such as displaying the indicia 12 and position 42 in different colors on a display <read on display screen> to "help to guide the technician in adjusting <read on updating display to turn corresponding teeth a final color> the angle of the x-ray tube until both aim indicia 12 and position 42 display in the same color <read on indicate completion as x-ray angulation device achieves customized angles>").
However, Subramanyan does not expressly disclose
sending the images to a server.
Li discloses
sending the images to a server (Li, [0420]: teaches image data being "uploaded <read on sending images to server> from a patient's device to another computing device, such as a server or other computer (e.g., virtual dental care system 106 and/or dental professional system 150) for further processing").
Li is analogous art with respect to Subramanyan because they are from the same field of endeavor, namely analyzing scanned teeth. Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to implement a machine-learning model to analyze the quality of scanned images as taught by Li into the teaching of Subramanyan. The suggestion for doing so would allow the system to generate more accurate 3D scans based on trained inference to fill in potential gaps in the 3D model, thereby reducing computational workload and improving efficiency. Therefore, it would have been obvious to combine Li with Subramanyan.
Regarding Claim 2, the combination of Subramanyan and Li discloses the method of Claim 1. Additionally, Subramanyan further discloses
saving the customized angles on a computer memory device for future visits (Subramanyan, [0127]: teaches using "positioning apparatus 194 for correlating detector 20 position to the secondary collimator 56 and relating these positions to the position of the x-ray source at any acquisition angle <read on saved customized angles> in a tomosynthesis sequence"; [0122]: teaches "radiation energy is directed to detector 20 and the corresponding image data from the digital detector obtained by control logic processor 26 and stored as a component or projection image 44, indexed according to the relative acquisition geometry for the image, such as by the exposure angle orientation," where "one component image 44 is obtained and stored <read on computer memory device> for each exposure angle").
Regarding Claim 3, the combination of Subramanyan and Li discloses the method of Claim 2. Additionally, Subramanyan further discloses
retrieving the saved customized angles (Subramanyan, [0128]: teaches the apparatus for dental tomosynthesis imaging generating and shaping an x-ray path, as well as providing geometric calibration information that might be detected in each acquired radiographic image, where by using one or more x-ray sources, "the enclosure also provides a translation apparatus with an actuator that translates the position of the x-ray source along a translation path in order to provide radiation over the range of angles <read on retrieve saved customized angles> needed for tomosynthesis imaging"),
displaying the tooth model on the screen (Subramanyan, [0124]: teaches the system obtaining updated position and angle data that correspond to each imaging position in the series of images that are obtained, where "this data then provides the needed reference geometry for reconstruction of the 3-D volume image <read on displaying tooth model> from a series of 2-D image captures"), and
sending the information to the x-ray angulation device (Subramanyan, [0102]: teaches control logic processor 26 of the system <read on x-ray angulation device> obtaining alignment information <read on sent information>).
Regarding Claim 4, the combination of Subramanyan and Li discloses the method of Claim 1. Additionally, Subramanyan further discloses wherein
the x-ray angulation is angulation for full-mouth (FMX) x-rays (Subramanyan, [0098]: teaches "for best imaging results, proper alignment with respect to angle, or angulation <read on x-ray angulation>, is also needed"; [0071]: teaches a reflectance imaging apparatus 96 being used to provide "more accurate positioning information for the detector 20 placed within the mouth of the patient"; [0073]: teaches "a full-mouth scanning apparatus <read on FMX x-rays> works in conjunction with the radiographic imaging system," which allows for the simultaneous acquisition of both radiographic and reflectance images, which can be fused together to show depth information with reference to highly accurate surface contour information).
Regarding Claim 7, the combination of Subramanyan and Li discloses the method of Claim 1. Subramanyan does not expressly disclose the limitations of Claim 7; however, Li discloses
sending feedback regarding the x-ray quality obtained from the x-ray image data captured using the customized angles to the server (Li, [0216]: teaches "execution of the neural network may enable the processing node 3110 to infer whether the dental image received in block 3502 includes sufficient quality as determined by the training data used to train the neural network"; [0217]: teaches the execution of the neural network being performed by a cloud-based processing node <read on server>; [0218]: teaches "the processing node 3110 may provide feedback <read on sending x-ray quality feedback> based on the determined quality of the dental image 3506").
Li is analogous art with respect to Subramanyan because they are from the same field of endeavor, namely analyzing scanned teeth. Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to implement a machine-learning model to analyze the quality of scanned images as taught by Li into the teaching of Subramanyan. The suggestion for doing so would allow the system to generate more accurate 3D scans based on trained inference to fill in potential gaps in the 3D model, thereby reducing computational workload and improving efficiency. Therefore, it would have been obvious to combine Li with Subramanyan.
Regarding Claim 8, the combination of Subramanyan and Li discloses the method of Claim 7. Subramanyan does not expressly disclose the limitations of Claim 8; however, Li discloses
developing and improving the angulation determination algorithms using the images sent to the server and feedback regarding the x-ray quality obtained from the x-ray image data captured using the customized angles (Li, [0208]: teaches calculating the loss function and using said loss function to train the neural network, where "the output of the loss function may be used to modify one or more of the convolutional filters or kernels <read on developing and improving angulation determination algorithms> so that the neural network may more accurately predict or identify a “quality” image"; [0216]: teaches "execution of the neural network may enable the processing node 3110 to infer whether the dental image received in block 3502 includes sufficient quality as determined by the training data used to train the neural network"; [0217]: teaches the execution of the neural network being performed by a cloud-based processing node <read on server>; [0218]: teaches "the processing node 3110 may provide feedback <read on sending x-ray quality feedback> based on the determined quality of the dental image 3506"; [0251]: teaches "the one or more images may include various perspectives and/or views of the dentition of the patient," where "the dental patient system 102 may send captured photos of the patient to the virtual dental care system 106 <read on send images to server>).
Li is analogous art with respect to Subramanyan because they are from the same field of endeavor, namely analyzing scanned teeth. Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to implement a machine-learning model to analyze the quality of scanned images as taught by Li into the teaching of Subramanyan. The suggestion for doing so would allow the system to generate more accurate 3D scans based on trained inference to fill in potential gaps in the 3D model, thereby reducing computational workload and improving efficiency. Therefore, it would have been obvious to combine Li with Subramanyan.
Claims 5-6 are rejected under 35 U.S.C. 103 as being unpatentable over Subramanyan et al. (US 20220151576 A1), hereinafter referenced as Subramanyan, in view of Li et al. (US 20240122463 A1), hereinafter referenced as Li as applied to Claim 1 above respectively, and further in view of Abraham et al. (US 20230149128 A1), hereinafter referenced as Abraham.
Regarding Claim 5, the combination of Subramanyan and Li discloses the method of Claim 1. The combination of Subramanyan and Li does not expressly disclose the limitations of Claim 5; however, Abraham discloses wherein
the x-ray angulation is angulation for bitewing (BW) x-rays (Abraham, [0088]: teaches 2D x-ray dental image data being bitewing x-rays; [0067]: teaches determining the relative orientation difference between segmented crown images by comparing two angles between the two segmented crowns <read on angulation for bitewing x-rays> as shown in FIG. 10; Note: it should be noted that although the primary prior art does not expressly teach this, it is common knowledge in the art that a full-mouth x-ray image comprises a bitewing x-ray scan(s) AND a periapical x-ray scan(s)).
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Abraham is analogous art with respect to Subramanyan, in view of Li because they are from the same field of endeavor, namely x-ray dental scans of teeth. Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to implement a neural network that automatically segments x-ray dental image data into separate categories, such as x-ray roots and x-ray crowns as taught by Abraham into the teaching of Subramanyan, in view of Li. The suggestion for doing so would allow the system to generate a full-mouth x-ray image using inference to determine regions of interest of the reconstructed 3D model, thereby reducing computation resources. Therefore, it would have been obvious to combine Abraham with Subramanyan, in view of Li.
Regarding Claim 6, the combination of Subramanyan and Li discloses the method of Claim 1. The combination of Subramanyan and Li does not expressly disclose the limitations of Claim 5; however, Abraham discloses wherein
the x-ray angulation is angulation for periapical (PA) x-rays (Abraham, [0088]: teaches 2D x-ray dental image data being periapical x-rays; [0053]: teaches determining the relative orientation difference between segmented 3D x-ray roots by comparing two angles between the two segmented 3D x-ray roots <read on angulation for periapical x-rays> as shown in FIG. 6; Note: it should be noted that although the primary prior art does not expressly teach this, it is common knowledge in the art that a full-mouth x-ray image comprises a bitewing x-ray scan(s) AND a periapical x-ray scan(s)).
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Abraham is analogous art with respect to Subramanyan, in view of Li because they are from the same field of endeavor, namely x-ray dental scans of teeth. Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to implement a neural network that automatically segments x-ray dental image data into separate categories, such as x-ray roots and x-ray crowns as taught by Abraham into the teaching of Subramanyan, in view of Li. The suggestion for doing so would allow the system to generate a full-mouth x-ray image using inference to determine regions of interest of the reconstructed 3D model, thereby reducing computation resources. Therefore, it would have been obvious to combine Abraham with Subramanyan, in view of Li.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Cramer et al. (US 20240185420 A1) discloses an apparatus for assessing a dental x-ray image and determining whether a patient is a candidate for dental treatment using neural networks;
Silva (US 20160284241 A1) discloses a system for simulating an x-ray dental image;
Derzapf et al. (US 20240398521 A1) discloses an intelligent restoration proposal that includes using an input resource to segment a 3D jaw model to obtain a segmented missing or unhealthy teeth and omitting the segmented missing or unhealthy teeth from the 3D jaw model to obtain a modified 3D jaw model;
Hirsch et al. (US 20240058099 A1) discloses a system that creates a virtual model that represents the individual visible teeth parts and gingiva of a dentition of a patient in segmented form; and
Cano (US 20190274643 A1) discloses an apparatus for aiming an X-ray camera that captures images of a physiology of a patient.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KARL TRUONG whose telephone number is (703)756-5915. The examiner can normally be reached 7:30 AM - 5:00 PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kent Chang can be reached at (571) 272-7667. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/K.D.T./Examiner, Art Unit 2614
/KENT W CHANG/Supervisory Patent Examiner, Art Unit 2614