SYSTEMS AND METHODS FOR CONSTRUCTING A THREE-DIMENSIONAL MODEL FROM TWO-DIMENSIONAL IMAGES

1 . A method comprising:

receiving, by a model generation engine, one or more images of a dental arch of a user;

generating, by the model generation engine, a point cloud based on data from the one or more images of the dental arch of the user, wherein generating the point cloud comprises:

identifying, based on the one or more images, a plurality of features included in the one or more images;

computing a probability for each feature; and

generating the point cloud based on the plurality of features using the probabilities;

generating, by the model generation engine, a three-dimensional (3D) model of the dental arch of the user based on the point cloud.

2 . The method of claim 1 , further comprising manufacturing, based on the 3D model of the dental arch of the user, a dental aligner specific to the user and configured to reposition one or more teeth of the user.

3 . The method of claim 1 , wherein the one or more images are received by the model generation engine from a mobile device corresponding to the user.

4 . The method of claim 1 , wherein identifying the plurality of features in the one or more images comprises generating an image feature map including the plurality of features included in the one or more images.

5 . The method of claim 4 , wherein the image feature map includes a plurality of portions, and wherein each portion of the plurality of portions is classified based on a respective feature within the portion of the one or more images to be represented in the point cloud.

6 . The method of claim 1 , further comprising:

identifying, by a point cloud feature extractor, a plurality of features of the point cloud;

determining, by a decoder, a difference between the plurality of features identified by the point cloud feature extractor and corresponding features identified in the one or more images; and

training, by an encoder, one or more weights for computing the probability of features being included in the one or more images based on the determined difference.

7 . The method of claim 1 , wherein the 3D model is a first 3D model, and wherein the method further comprises generating a merged model by merging the first 3D model with a second 3D model of the dental arch of the user.

8 . The method of claim 1 , wherein the 3D model is a first 3D model, the method further comprising comparing the first 3D model with a second 3D model.

9 . The method of claim 8 , wherein the second 3D model is generated based on a dental impression of the dental arch of the user.

10 . A method comprising:

identifying, by an image detector based on one or more images of a dental arch of a user, one or more features represented in a respective portion of a plurality of portions of the one or more images;

generating, by a model generation engine, a point cloud using the one or more features identified in the one or more images and a respective probability of the one or more features; and

generating, by the model generation engine based on the generated point cloud, a three-dimensional (3D) model of the dental arch of the user, the 3D model corresponding to the one or more images.

11 . The method of claim 10 , further comprising manufacturing, based on the 3D model of the dental arch of the user, a dental aligner specific to the user and configured to reposition one or more teeth of the user.

12 . The method of claim 10 , wherein the one or more images are received from a mobile device corresponding to the user.

13 . The method of claim 10 , wherein identifying the one or more features in the one or more images comprises generating an image feature map including the one or more features included in the one or more images.

14 . The method of claim 13 , wherein the image feature map is formed based on the plurality of portions, and wherein each portion of the plurality of portions is classified based on a respective feature within the portion of the one or more images to be represented in the point cloud.

15 . The method of claim 10 , further comprising:

identifying, by a point cloud feature extractor, a plurality of features of the point cloud;

determining, by a decoder, a difference between the plurality of features identified by the point cloud feature extractor and corresponding features identified in the one or more images; and

training, by an encoder, one or more weights for computing a probability of features being included in the one or more images based on the determined difference.

16 . The method of claim 10 , wherein the 3D model is a first 3D model, and wherein the method further comprises generating a merged model by merging the first 3D model with a second 3D model of the dental arch of the user.

17 . The method of claim 10 , wherein the 3D model is a first 3D model, the method further comprising comparing the first 3D model with a second 3D model.

18 . The method of claim 17 , wherein the second 3D model is generated based on a dental impression of the dental arch of the user.

19 . A system comprising:

a processing circuit comprising a processor communicably coupled to a non-transitory computer readable medium, wherein the processor is configured to execute instructions stored on the non-transitory computer readable medium to:

identify, based on one or more images of a dental arch of a user, a plurality of features represented in the one or more images;

generate a point cloud using the one or more images and the plurality of features; and

generate a three-dimensional (3D) model of the dental arch of the user based on the point cloud, wherein the 3D model corresponds to the one or more images.

20 . The system of claim 19 , wherein the 3D model is a first 3D model, and wherein the processor is further configured to compare the first 3D model with a second 3D model generated based on a dental impression of the dental arch of the user.