Image based dentition record digitization

1 . A method for generating a 3D model of an object using one or more cameras, comprising:

calibrating each camera;

establishing a coordinate system and environment for the one or more cameras;

registering one or more fiducials on the object; and

capturing one or more images and constructing a 3D model from images.

2 . The method of claim 1 , wherein the model is used for one of the following:

measurement of 3 D geometry for teeth/gingival/face/jaw; measurement of position, orientation and size of teeth/gingival/face/jaw; determination of the type of malocclusion for treatment; recognition of tooth features; recognition of gingiva feature; extraction of teeth from jaw scans; registration with marks or sparkles to identify features of interest; facial profile analysis; filling in gaps in 3 D models from photogrammetry using preacquired models based on prior information about teeth/jaw/face, and creating a facial/orthodontic model.

3 . The method of claim 1 , comprising:

a. receiving an initial 3D model for the patient;

b. determining a target 3D model; and

c. generating one or more intermediate 3D models.

4 . The method of claim 1 , comprising extracting environment information from the model.

5 . The method of claim 1 , comprising rendering one or more images of the model.

6 . The method of claim 1 , wherein the model is represented using one of:

polyhedrons and voxels.

7 . The method of claim 1 , wherein the model is a patient model

8 . The method of claim 7 , comprising generating a virtual treatment for the patient and generating a post-treatment 3D model.

9 . The method of claim 1 , comprising geometry subdividing and tessellating the model.

10 . The method of claim 1 , comprising:

identifying one or more common features on the tooth model;

detecting the position of the common features on the tooth model at the first position;

detecting the position of the common features on the tooth model at the second position; and

determining a difference between the position of each common feature at the first and second positions.

11 . A system for generating a 3D model of an object, comprising:

one or more calibrated cameras;

means for establishing a coordinate system and environment for the one or more cameras;

means for registering one or more fiducials on the object; and

means for capturing one or more images and constructing a 3D model from images.

12 . The system of claim 11 , wherein the model is used for one of the following:

measurement of 3 D geometry for teeth/gingival/face/jaw; measurement of position, orientation and size of teeth/gingival/face/jaw; determination of the type of malocclusion for treatment; recognition of tooth features; recognition of gingiva feature; extraction of teeth from jaw scans; registration with marks or sparkles to identify features of interest; facial profile analysis; filling in gaps in 3 D models from photogrammetry using preacquired models based on prior information about teeth/jaw/face, and creating a facial/orthodontic model.

13 . The system of claim 11 , comprising means for:

a. receiving an initial 3D model for the patient;

b. determining a target 3D model; and

c. generating one or more intermediate 3D models.

14 . The system of claim 11 , comprising means for extracting environment information from the model.

15 . The system of claim 11 , comprising means for rendering one or more images of the model.

16 . The system of claim 11 , wherein the model is represented using one of:

polyhedrons and voxels.

17 . The system of claim 11 , wherein the model is a patient model

18 . The system of claim 17 , comprising means for generating a virtual treatment for the patient and generating a post-treatment 3D model.

19 . The system of claim 11 , comprising means for geometry subdividing and tessellating the model.

20 . The system of claim 11 , comprising means for:

identifying one or more common features on the tooth model;

detecting the position of the common features on the tooth model at the first position;

detecting the position of the common features on the tooth model at the second position; and

determining a difference between the position of each common feature at the first and second positions.