Dental Image Feature Detection

1 . A computing device implemented method comprising:

receiving data representing one or more images of dental information associated with a patient;

adjusting the data representing the one or more images of dental information into a predefined format, wherein adjusting the data includes adjusting one or more visual parameters associated with the one or more images of dental information;

using a machine learning system to determine a confidence score for one or more portions of the one or more images of dental information; and

producing a representation of the determined confidence scores to identify one or more detected features present in the one or more images of dental information.

2 . The computing device implemented method of claim 1 , further comprising: transferring data representative of the one or more images of dental information associated with the patient to one or more networked computing devices for statistical analysis.

3 . The computing device implemented method of claim 1 , wherein the machine learning system employs a convolution neural network.

4 . The computing device implemented method of claim 1 , wherein the machine learning is trained with dental imagery and associated annotations.

5 . The computing device implemented method of claim 1 , wherein one or more annotations are produced for each of the images of dental information.

6 . The computing device implemented method of claim 1 , wherein the one or more detected features include a radiolucent lesion or an opaque lesion.

7 . The computing device implemented method of claim 1 , wherein the produced representation includes a graphical representation that is presentable on a user interface of the computing device.

8 . The computing device implemented method of claim 1 , wherein the produced representation is used for a diagnosis and treatment plan.

9 . The computing device implemented method of claim 8 , wherein an alert or recommendation is produced by using the produced representation for the diagnosis and treatment plan.

10 . A system comprising:

a computing device comprising:

a memory configured to store instructions; and

a processor to execute the instructions to perform operations comprising:

receiving data representing one or more images of dental information associated with a patient;

adjusting the data representing the one or more images of dental information into a predefined format, wherein adjusting the data includes adjusting one or more visual parameters associated with the one or more images of dental information;

using a machine learning system to determine a confidence score for one or more portions of the one or more images of dental information; and

producing a representation of the determined confidence scores to identify one or more detected features present in the one or more images of dental information.

11 . The system of claim 10 , further comprising: transferring data representative of the one or more images of dental information associated with the patient to one or more networked computing devices for statistical analysis.

12 . The system of claim 10 , wherein the machine learning system employs a convolution neural network.

13 . The system of claim 10 , wherein the machine learning is trained with dental imagery and associated annotations.

14 . The system of claim 10 , wherein one or more annotations are produced for each of the images of dental information.

15 . The system of claim 10 , wherein the one or more detected features include a radiolucent lesion or an opaque lesion.

16 . The system of claim 10 , wherein the produced representation includes a graphical representation that is presentable on a user interface of the computing device.

17 . The system of claim 10 , wherein the produced representation is used for a diagnosis and treatment plan.

18 . The system of claim 17 , wherein an alert or recommendation is produced by using the produced representation for the diagnosis and treatment plan.

19 . One or more computer readable media storing instructions that are executable by a processing device, and upon such execution cause the processing device to perform operations comprising:

receiving data representing one or more images of dental information associated with a patient;

adjusting the data representing the one or more images of dental information into a predefined format, wherein adjusting the data includes adjusting one or more visual parameters associated with the one or more images of dental information;

using a machine learning system to determine a confidence score for one or more portions of the one or more images of dental information; and

producing a representation of the determined confidence scores to identify one or more detected features present in the one or more images of dental information.

20 . The computer readable media of claim 19 , further comprising: transferring data representative of the one or more images of dental information associated with the patient to one or more networked computing devices for statistical analysis.

21 . The computer readable media of claim 19 , wherein the machine learning system employs a convolution neural network.

22 . The computer readable media of claim 19 , wherein the machine learning is trained with dental imagery and associated annotations.

23 . The computer readable media of claim 19 , wherein one or more annotations are produced for each of the images of dental information.

24 . The computer readable media of claim 19 , wherein the one or more detected features include a radiolucent lesion or an opaque lesion.

25 . The computer readable media of claim 19 , wherein the produced representation includes a graphical representation that is presentable on a user interface of the computing device.

26 . The computer readable media of claim 19 , wherein the produced representation is used for a diagnosis and treatment plan.

27 . The computer readable media of claim 27 , wherein an alert or recommendation is produced by using the produced representation for the diagnosis and treatment plan.