SYSTEMS AND METHODS FOR GENERATING AN IMAGE REPRESENTATIVE OF ORAL TISSUE CONCURRENTLY WITH DENTAL PREVENTATIVE LASER TREATMENT

1 . A system for generating an image representative of oral tissue concurrently with dental preventative laser treatment, the system comprising:

a laser configured to generate a laser beam as a function of a laser parameter, wherein the laser beam performs a non-ablative treatment of dental hard tissue, as a function of the laser parameter;

a beam delivery system configured to deliver the laser beam from the laser;

a hand piece configured to accept the laser beam from the beam delivery system and direct the laser beam, using a laser beam output configured to be positioned within an oral cavity, to the dental hard tissue;

a sensor, positioned outside of the hand piece and in sensed communication with oral tissue including the treated dental hard tissue and untreated dental soft tissue, configured to detect a plurality of 3D oral images as a function of oral phenomena associated with the treated dental hard tissue and the untreated dental soft tissue, concurrently with delivery of the non-ablative laser beam to the dental tissue; and

a computing device configured to:

receive the plurality of 3D oral images from the sensor; and

aggregate an aggregated 3D oral image representing the treated dental hard tissue of multiple teeth and the untreated soft tissue as a function of the plurality of 3D oral images.

2 . (canceled)

3 . The system of claim 2 , wherein the computing device is further configured to associate the aggregated 3D oral image with the laser parameter.

4 . The system of claim 1 , wherein aggregating the aggregated 3D oral image further comprises:

identifying at least a common feature in a first 3D oral image and a second 3D oral image of the plurality of 3D oral images; and

transforming one or more of the first 3D oral image and the second 3D oral image as a function of the at least a common feature.

5 . The system of claim 4 , wherein aggregating the aggregated 3D oral image further comprises blending a demarcation between the first 3D oral image and the second 3D oral image.

6 . The system of claim 5 , wherein blending the demarcation comprises:

comparing pixel values between overlapping pixels in the first 3D oral image and the second 3D oral image; and

altering the demarcation as a function of the comparison.

7 . The system of claim 6 , wherein altering the demarcation comprises minimizing a difference in value between overlapping pixels between the first 3D oral image and the second 3D oral image along the demarcation.

8 . The system of claim 2 wherein the aggregated 3D oral image has a resolution which is finer than one or more of 500, 250, 150, 100, 50, or 25 micrometers.

9 . The system of claim 1 wherein aggregating the aggregated 3D oral image comprises:

inputting the plurality of 3D oral images into an image aggregation machine learning model; and

outputting the aggregated 3D oral image as a function of the plurality of 3D oral images and the image aggregation machine learning model.

10 . The system of claim 9 wherein aggregating the aggregated 3D oral image further comprises:

training the image aggregation machine learning model by:

inputting an image aggregation training set into a machine learning process, wherein the image aggregation training set correlates aggregated 3D oral images to pluralities of 3D oral images; and

training the image aggregation machine learning model as a function of the image aggregation training set and the machine learning process.

11 . A method of generating an image representative of oral tissue concurrently with preventative dental laser treatment, the system comprising:

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

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

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

directing, using the hand piece, the laser beam to dental tissue, wherein the laser beam performs a non-ablative treatment of the dental tissue, as a function of the laser parameter;

detect, using a sensor, a plurality of oral images as a function of oral phenomena concurrently with delivery of the laser beam to the dental tissue;

receiving, using a computing device, the plurality of oral images from the sensor; and

aggregating, using the computing device, an aggregated oral image as a function of the plurality of oral images.

12 . The method of claim 11 , wherein the aggregated oral image comprises a three-dimensional representation of oral tissue.

13 . The method of claim 12 , further comprising associating, using the computing device, the aggregated oral image with the laser parameter.

14 . The method of claim 11 , wherein aggregating the aggregated oral image further comprises:

identifying at least a common feature in a first oral image and a second oral image of the plurality of oral images; and

transforming one or more of the first oral image and the second oral image as a function of the at least a common feature.

15 . The method of claim 14 , wherein aggregating the aggregated oral image further comprises blending a demarcation between the first oral image and the second oral image.

16 . The method of claim 15 , wherein blending the demarcation comprises:

comparing pixel values between overlapping pixels in the first oral image and the second oral image; and

altering the demarcation as a function of the comparison.

17 . The method of claim 16 , wherein altering the demarcation comprises minimizing a difference in value between overlapping pixels between the first oral image and the second oral image along the demarcation.

18 . The method of claim 11 , wherein the aggregated oral image has a resolution which is finer than one or more of 500, 250, 150, 100, 50, or 25 micrometers.

19 . The method of claim 11 , wherein aggregating the aggregated oral image comprises:

inputting the plurality of oral images into an image aggregation machine learning model; and

outputting the aggregated oral image as a function of the plurality of oral images and the image aggregation machine learning model.

20 . The method of claim 19 , wherein aggregating the aggregated oral image further comprises:

training the image aggregation machine learning model by:

inputting an image aggregation training set into a machine learning process, wherein the image aggregation training set correlates aggregated oral images to pluralities of oral images; and

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

21 . The system of claim 1 , wherein the laser parameter is selected to generate the non-ablative laser beam to remove plaque from the treated dental hard tissue.

22 . The system of claim 1 , wherein the camera, including the image sensor, is located at an opposite end of-the hand piece from the laser beam output and configured not to be positioned within the oral cavity, and the hand piece is further configured to facilitate an optical path between the oral tissue and the camera.