Data mining of dental images

• US 10,460,839 B1
• Filed: 11/29/2018
• Issued: 10/29/2019
• Est. Priority Date: 11/29/2018
• Status: Active Grant

• Current Assignee: Cube Click Incorporated
• Original Assignee: Richard Ricci
• Inventors: Ricci, Richard
• Primary Examiner(s): Burgess, Joseph D
• Application Number:
  US16/203,795
• Time in Patent Office: 334 Days
• CPC Class Codes: G06T 2207/20081 Training; Learning
• CPC Class Codes: G06T 2207/30036 Dental; Teeth
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06V 2201/03 Recognition of patterns in medical or anatomical images
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

Data mining of a dental image is described. In an example scenario, an aggregator service receives a dental image of a patient from a dental image provider. The dental image is processed with a machine learning (ML) anatomy dataset. An anatomy from the ML anatomy dataset is identified and matched to the dental image. The dental image is next matched and identified with a ML pathology and treatment dataset. A pathology and a treatment from the ML pathology and treatment dataset are matched to the dental image. Next, the dental image and the anatomy, the pathology, and the treatment associated with the dental image are inserted to a patient dataset associated with the patient. A cluster analysis of the patient dataset is performed with a cluster dataset to produce a correlated dental image information. The correlated dental image information is provided to a data mining entity and to compile a diagnostic aid for a user.

Claims

1. A system for providing data mining of a dental image, the system comprising:

an aggregator server, wherein the aggregator server is configured to;

receive a dental image of a patient from a dental image provider, wherein the dental image provider is an e-commerce service;

process the dental image with a machine learning (ML) anatomy dataset;

match and identify an anatomy from the ML anatomy dataset to the dental image;

match and identify the dental image with a ML pathology and treatment dataset;

match a pathology and a treatment from the machine leaning pathology and treatment dataset to the dental image;

insert the dental image and the anatomy, the pathology, and the treatment associated with the dental image to a patient dataset associated with the patient;

perform a cluster analysis of the patient dataset with a cluster dataset to produce a correlated dental image information;

provide the correlated dental image information to a data mining entity and to compile a diagnostic aid for a user;

format the correlated dental image information based on another dataset associated with the data mining entity;

merge the correlated dental image information into the data mining entity dataset; and

identify and correct a discrepancy between the correlated dental image information and the data mining entity dataset.

2. The aggregator server of claim 1, wherein the dental image is obtained from one or more of:

a digital image, a film based x-ray, a digitally scanned x-ray, a digitally captured x-ray, a scintillator technology based image, a trans-illumination image, a florescence technology based image, a blue florescence technology based image, a laser based technology based image, and a computed tomography (CT) scan based image.

3. The aggregator server of claim 1, wherein the dental image provider utilizes an image capture device or a data storage device.

4. The aggregator server of claim 3, wherein the capture image device includes one or more of:

an x-ray equipment, a scintillator counter, an indirect or direct flat panel detector (FPD), a charged couple device (CCD), a phosphor plate radiography device, a picture archiving and communication system (PACS), a photo-stimulable phosphor (PSP) device, a computer tomography (CT) device, a wireless complementary metal-oxide-semiconductor (CMOS), a cone beam computed tomography (CBCT) device.

5. The aggregator server of claim 1, wherein the aggregator server is further configured to:

change an orientation of the dental image based on the anatomy;

correlate one or more classifications from the dental image and the anatomy with at least one operation to;

identify teeth in the dental image;

identify a position for each of the teeth as adult or primary based on one or more of a universal number system, a palmer notation, or an international standards organization (ISO) system;

identify one or more of a maxillary, a mandible molar, or a canine relationship between the teeth based on an angle'"'"'s classification of malocclusion; and

insert the one or more classifications into the patient dataset in relation to the dental image.

6. The aggregator server of claim 1, wherein the aggregator server is further configured to:

determine the anatomy associated with the dental image by performing at least one operation to;

differentiate the dental image as a left or a right vertical bite wing image;

differentiate the dental image as a left or a right horizontal bite wing image;

differentiate the dental image as a left or a right maxillary periapical image;

differentiate the dental image as a left or a right mandibular periapical image;

differentiate the dental image as a maxillary or mandibular anterior image;

differentiate the dental image as a left or a right side of a panoramic image;

differentiate the dental image as including an absent tooth or a present tooth;

or

differentiate the dental image as including a cephalometric image with an over bite, an over jet, an angle'"'"'s classification of malocclusion, an airway space or a sleep apnea.

7. The aggregator server of claim 1, wherein the aggregator server is further configured to:

determine the anatomy associated with the dental image by performing at least one operation to;

differentiate the dental image as a maxillary image or a mandible image;

differentiate the dental image as a left or a right temporal mandibular joint image;

identify and measure one or more of;

a mandibular canal, an inferior alveolar nerve space, a mental foramen, a staphne'"'"'s cyst, a mandible foramen, a condylar process, a mandibular coronoid process, a sublingual fossa, a ramus, a alveolar crest, a mental protuberance, a mental tubercle, a mylohyoid grove, a mylohyoid line, a lingual, a pterygoid fossa, an incisive canal, a zygomatic bone, a maxillary sinus, a curve of spee, a diastomer, a tooth bud, a germination, a fused teeth, a full or partial septum, an open bite, a cross bite, an over jet, or an over bite associated with the dental image;

identify and measure one or more of a maxillary sinus size and volume, a bone thickness of a floor of a maxillary sinus, a bone thickness surrounding the maxillary sinus, a graft placed in the maxillary sinus, and a septum in the maxillary sinus;

identify a post-surgical maxillary sinus or mandibular alveolar ridge splitting procedure; and

identify a frontal sinus, a graft placed in the frontal sinus, and a bone thickness surrounding the frontal sinus.

8. The aggregator server of claim 1, wherein the pathology and the treatment dataset includes one or more pathology annotations and one or more treatment annotations designated to one or more model dental images associated with a dental field including one or more of:

endodontics, periodontics, orthodontics, prosthodontics, oral surgery, oral pathology, pediatrics, temporal mandibular joint dentistry, and radiology.

9. An aggregator server for providing data mining of a dental image, the aggregator server comprising:

a computer vision component configured to analyze the dental image,

a memory configured to store instructions associated with an aggregator service,

a processor coupled to the computer vision component and the memory, the processor executing the instructions associated with the aggregator service, wherein the aggregator service includes;

an image processing engine configured to;

receive a dental image of a patient from a dental image provider, wherein the dental image provider is an e-commerce service;

process the dental image with a machine learning (ML) anatomy dataset;

match and identify an anatomy from the ML anatomy dataset to the dental image;

match and identify the dental image with a ML pathology and treatment dataset;

match a pathology and a treatment from the ML pathology and treatment dataset to the dental image;

query and receive a patient dataset of the patient associated with the dental image from a patient data provider;

insert the dental image and the anatomy, the pathology, and the treatment associated with the dental image to the patient dataset;

perform a cluster analysis of the patient dataset with a cluster dataset to produce a correlated dental image information;

provide the correlated dental image information to a data mining entity and to compile a diagnostic aid for a user;

format the correlated dental image information based on another dataset associated with the data mining entity;

merge the correlated dental image information into the data mining entity dataset; and

identify and correct a discrepancy between the correlated dental image information and the data mining entity dataset.

10. The aggregator server of claim 9, wherein the dental image is processed with the ML anatomy dataset upon a process to:

verify an authorization by the patient to analyze the dental image.

11. The aggregator server of claim 10, wherein the correlated dental image information is provided to a data mining entity upon a process to:

verify a compliance of the dental image and the correlated dental image information with a regulatory policy.

12. The aggregator server of claim 11, wherein the regulatory policy includes health insurance portability and accountability act (HIPAA).

13. The aggregator server of claim 9, wherein the dental image is not processed with the ML anatomy dataset in response to a failure to determine an authorization by the patient to analyze the dental image.

14. The aggregator server of claim 9, wherein the patient dataset includes one or more of an age, a first name, a gender, a middle initial, a last name, a date of birth, a zip code, an address, a cell phone number, a land line number, a current medication, a previous medication, a social security number, a material status, an insurance, a patient'"'"'s insurance identification number, a patient'"'"'s email address, a change of insurance, a change of employment, a change of zip code, a change of the previous medication, a change of the marital status, and a change of the gender associated with the patient.

15. The aggregator server of claim 9, wherein the data mining entity includes a dental insurance data mining service, and wherein the dental insurance data mining provides an insurance dataset including one or more of an American dental association (ADA) code, a date, a claim identifier, a claim number, a duplicate claim associated with the claim identifier, a national provider identification number for a provider associated with a patient, and a provider'"'"'s state license number to further analyze and integrate the correlated dental image information.

16. The aggregator server of claim 9, wherein the data mining entity includes a bioinformatics data mining service, and wherein the bioinformatics data mining service provides a bioinformatics dataset including one or more of a gene identifier, a gene sequence, a single nucleotide polymorphism, a nucleic acid sequence, a protein sequence, an annotating genome, a shotgun sequence, a periodontal disease, a caries susceptibility, an impacted tooth, a tooth loss, an angle'"'"'s classification of malocclusion, and a diabetes diagnosis to further analyze and integrate the correlated dental image information.

17. A method of providing data mining of a dental image, the method comprising:

receiving a dental image of a patient from a dental image provider;

processing the dental image with a machine learning (ML) anatomy dataset;

matching and identifying an anatomy from the ML anatomy dataset to the dental image;

matching and identifying the dental image with a ML pathology and treatment dataset;

matching a pathology and a treatment from the ML pathology and treatment dataset to the dental image;

querying and receive a patient dataset of the patient associated with the dental image from a patient data provider;

inserting the dental image and the anatomy, the pathology, and the treatment associated with the dental image to the patient dataset;

performing a cluster analysis of the patient dataset with a cluster dataset to produce a correlated dental image information;

providing the correlated dental image information to a data mining entity and to compile a diagnostic aid for a user;

formatting the correlated dental image information based on another dataset associated with the data mining entity;

merging the correlated dental image information into the data mining entity dataset; and

identifying and correcting a discrepancy between the correlated dental image information and the data mining entity dataset.