Dental Image Feature Detection

Abstract

A system includes a computing device that includes a memory configured to store instructions. The system also includes a processor to execute the instructions to perform operations that include receiving data representing one or more images of dental information associated with a patient. Operations include 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. Operations include 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.

What is claimed is: 
     
         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.