US 11,957,541 B2
Machine learning scoring system and methods for tooth position assessment
Guotu Li, Durham, NC (US); Christopher E. Cramer, Durham, NC (US); Chad Clayton Brown, Cary, NC (US); and Anton Spiridonov, Cary, NC (US)
Assigned to Align Technology, Inc., San Jose, CA (US)
Filed by Align Technology, Inc., San Jose, CA (US)
Filed on Dec. 23, 2022, as Appl. No. 18/146,327.
Application 18/146,327 is a continuation of application No. 16/569,345, filed on Sep. 12, 2019, granted, now 11,534,272.
Claims priority of provisional application 62/731,741, filed on Sep. 14, 2018.
Prior Publication US 2023/0129379 A1, Apr. 27, 2023
Int. Cl. A61C 9/00 (2006.01); A61B 5/00 (2006.01); A61C 7/00 (2006.01); A61C 13/20 (2006.01); A61C 13/34 (2006.01)
CPC A61C 9/0053 (2013.01) [A61B 5/0088 (2013.01); A61B 5/7264 (2013.01); A61C 7/002 (2013.01); A61C 13/20 (2013.01); A61C 13/34 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method, comprising:
acquiring, in one or more computing devices, a digital model of a patient's teeth;
extracting, with the one or more computing devices, raw features of the patient's teeth from the digital model of the patient's teeth;
creating, in the one or more computing devices, engineered features from the raw features of the patient's teeth;
applying the raw features and/or the engineered features to a trained classifier of the one or more computing devices, wherein the trained classifier generates a post-treatment tooth position score indicating how likely a post-treatment tooth position is to be accepted or rejected by a doctor; and
outputting from the one or more computing devices the post-treatment tooth position score.