Systems and methods for dental treatment and verification

1. A system for dental treatment and verification, the system comprising:

a laser configured to generate a laser beam as a function of at least a laser parameter;

a beam delivery system configured to deliver the laser beam from the laser, the beam delivery system comprising a beam scanner configured to scan a position of the laser beam on dental tissue as a function of at least a scan parameter;

a hand piece configured to accept the laser beam from the beam delivery system and direct the laser beam to the dental tissue;

at least a sensor configured to detect at least a treatment parameter as a function of at least a treatment phenomenon, during the dental treatment, wherein the at least a sensor comprises:

at least a camera configured to detect at least a treatment parameter comprising an image of at least a portion of the dental tissue concurrently with the dental treatment of the dental tissue, wherein the image includes an existing dental restoration; and

a computing device, in communication with the laser, the beam scanner, and the at least a sensor, configured to:

control the laser using the at least a laser parameter;

control the beam scanner using the at least a scan parameter;

controlling each of the at least a laser parameter and the at least a scan parameter to effect the dental treatment, wherein the dental treatment comprises dental laser cleaning;

receive the treatment parameter from the at least a sensor;

automatically determine aggregated treated surfaces as a function of the at least a treatment parameter and the at least a laser parameter;

generate a 3D representation of the aggregated treated surfaces as a function of the aggregated treated surfaces, the at least a treatment parameter, and the at least a laser parameter; and

display the 3D representation of the aggregated treated surfaces to a user of the system during the dental laser cleaning.

2. The system of claim 1 , wherein:

the at least a sensor comprises a position sensor, comprising a rotary encoder configured to detect rotary position of a component of the beam delivery system; and

the at least a treatment parameter represents a treated location derived from the rotary position of the component of the beam delivery system.

3. The system of claim 1 , wherein the computing device is further configured to:

generate a treatment metric as a function of one or more of the at least a treatment parameter and the aggregated treated surfaces; and

communicate the treatment metric to a remote device.

4. The system of claim 3 , wherein generating the treatment metric comprises:

inputting one or more of the at least a treatment parameter and a representation of the aggregated treated surfaces into a treatment metric machine learning model; and

outputting the treatment metric as a function of the treatment metric machine learning model and one or more of the at least a treatment parameter and the representation of the aggregated treated surfaces.

5. The system of claim 4 wherein generating the treatment metric further comprises:

training the treatment metric machine learning model by:

inputting a treatment metric training set into a machine learning algorithm, wherein the treatment metric training set correlates treatment metrics to one or more of the at least a treatment parameter and the representation of the aggregated treated surfaces; and

training the treatment metric machine learning model as a function of the treatment metric training set and the machine learning algorithm.

6. The system of claim 3 wherein the treatment metric is related to the laser treatment.

7. A method of dental treatment and verification, the method comprising:

generating, using a laser, a laser beam as a function of at least a laser parameter;

delivering, using a beam delivery system comprising a beam scanner, the laser beam from the laser;

scanning, using the beam scanner of the beam delivery system, a position of the laser beam on dental tissue as a function of at least a scan parameter;

accepting, using a hand piece, the laser beam from the beam delivery system

directing, using the hand piece, the laser beam to the dental tissue;

detecting, using at least a sensor comprising a camera, at least a treatment parameter as a function of at least a treatment phenomenon, during the dental laser treatment;

detecting, using the at least a camera, the at least a treatment parameter comprising an image of at least a portion of the dental tissue concurrently with the dental laser treatment of the dental tissue, wherein the image includes an existing dental restoration;

controlling, using a computing device in communication with the laser, the beam scanner, and the at least a sensor, the laser using the at least a laser parameter;

controlling, using the computing device, the beam scanning using the at least a scan parameter;

controlling, using the computing device, each of the at least a laser parameter and the at least a scan parameter to effect the dental treatment, wherein the dental treatment includes dental laser cleaning;

receiving, using the computing device, the treatment parameter from the at least a sensor;

automatically determining, using the computing device, aggregated treated surfaces as a function of the at least a treatment parameter and the at least a laser parameter;

generating, using the computing device, a 3D representation of the aggregated treated surfaces as a function of the aggregated treated surfaces, the at least a treatment parameter, and the at least a laser parameter; and

displaying, using the computing device, the 3D representation of the aggregated treated surfaces to a user of the system during the dental laser cleaning.

8. The method of claim 7 , wherein:

the at least a sensor comprises a position sensor, comprising a rotary encoder configured to detect rotary position of a component of the beam delivery system; and;

the at least a treatment parameter represents a treated location derived from the rotary position of the component of the beam delivery system.

9. The method of claim 7 , further comprising:

generating, using the computing device, a treatment metric as a function of one or more of the at least a treatment parameter and the aggregated treated surfaces; and

communicating, using the computing device, the treatment metric to a remote device.

10. The method of claim 9 , wherein generating the treatment metric comprises:

inputting one or more of the at least a treatment parameter and a representation of the aggregated treated surfaces into a treatment metric machine learning model; and

outputting the treatment metric as a function of the treatment metric machine learning model and one or more of the at least a treatment parameter and the representation of the aggregated treated surfaces.

11. The method of claim 10 wherein generating the treatment metric further comprises:

training the treatment metric machine learning model by:

inputting a treatment metric training set into a machine learning algorithm, wherein the treatment metric training set correlates treatment metrics to one or more of the at least a treatment parameter and the representation of the aggregated treated surfaces; and

training the treatment metric machine learning model as a function of the treatment metric training set and the machine learning algorithm.

12. The method of claim 9 wherein, the treatment metric is related to the dental treatment.

13. The system of claim 1 , wherein the computing device is further configured to automatically chart a size, location, and surface of the existing dental restoration, and automatically charting includes classifying the at least a treatment parameter comprising the image of the existing dental restoration to a type of restoration.

14. The system of claim 13 , wherein classifying the at least a treatment parameter comprising the image of the existing dental restoration to the type of restoration comprises:

inputting the at least a treatment parameter comprising the image of the existing dental restoration into a classifier comprising a machine learning model; and

classifying the type of restoration as a function of the at least a treatment parameter comprising the image of the existing dental restoration and the classifier comprising the machine learning model.

15. The method of claim 7 , further comprising automatically charting, using the computing device, a size, location, and surface of the existing dental restoration, wherein automatically charting includes classifying the at least a treatment parameter comprising the image of the existing dental restoration to a type of restoration.

16. The method of claim 15 , wherein classifying the at least a treatment parameter comprising the image of the existing dental restoration to the type of restoration comprises:

inputting the at least a treatment parameter comprising the image of the existing dental restoration into a classifier comprising a machine learning model; and

classifying the type of restoration as a function of the at least a treatment parameter comprising the image of the existing dental restoration and the classifier comprising the machine learning model.

17. The system of claim 1 , wherein the computing device is further configured to differentiate between treated surfaces and untreated surfaces on the 3D representation of the aggregated treated surfaces as a function of the aggregated treated surfaces, the at least a treatment parameter, and the at least a laser parameter.

18. The system of claim 1 , wherein the dental laser cleaning treatment is a prophylactic treatment configured to retreat a patient periodically at least once a year.

19. The method of claim 7 , further comprising differentiating, using the computing device, between treated surfaces and untreated surfaces on the 3D representation of the aggregated treated surfaces as a function of the aggregated treated surfaces, the at least a treatment parameter, and the at least a laser parameter.

20. The method of claim 7 , wherein the dental laser cleaning treatment is a prophylactic treatment configured to retreat a patient periodically at least once a year.