CPC G06V 10/82 (2022.01) [G06F 18/24143 (2023.01); G06T 7/0012 (2013.01); G06T 7/13 (2017.01); G06V 10/44 (2022.01); G06V 30/19173 (2022.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20132 (2013.01); G06T 2207/30004 (2013.01); G06V 2201/033 (2022.01)] | 20 Claims |
1. A method comprising:
receiving a two-dimensional (2D) image of a face of a patient, the 2D image including a depiction of teeth of the patient;
processing the 2D image of the face using one or more trained machine learning model, wherein the one or more trained machine learning model outputs a pixel-level classification of pixels in the 2D image, the pixel-level classification comprising a first set of pixels classified as being inside of a first bounding shape that bounds a first plurality of teeth of the teeth depicted in the 2D image of the face of the patient and a second set of pixels classified as being outside of the first bounding shape;
performing a classification comprising at least one of:
a) classifying, by the one or more trained machine learning model, the 2D image as depicting one of an anterior view, a side view or an occlusal view; or
b) classifying, by the one or more trained machine learning model, the 2D image as appropriate for further processing or as not appropriate for further processing;
cropping the 2D image of the face of the patient to leave a first region comprising the first set of pixels classified as being inside of the first bounding shape and to remove a second region comprising the second set of pixels classified as being outside of the first bounding shape, wherein the cropped 2D image comprises depictions of the first plurality of teeth; and
performing one or more operations on the cropped 2D image of the face of the patient.
|