US 12,465,469 B2
Method, system and devices for instant automated design of a customized dental object
Jinho Lee, Belmont, MA (US); Chih-Yung Jesse Huang, Westford, MA (US); and Eric Bright, Fiskdale, MA (US)
Assigned to Dentsply Sirona Inc., York, PA (US)
Appl. No. 17/637,107
Filed by DENTSPLY SIRONA Inc., York, PA (US)
PCT Filed Sep. 3, 2020, PCT No. PCT/US2020/049093
§ 371(c)(1), (2) Date Feb. 22, 2022,
PCT Pub. No. WO2021/046147, PCT Pub. Date Mar. 11, 2021.
Claims priority of provisional application 62/896,043, filed on Sep. 5, 2019.
Prior Publication US 2022/0296344 A1, Sep. 22, 2022
Int. Cl. A61C 13/00 (2006.01); A61C 5/77 (2017.01); G06N 3/02 (2006.01); G16H 30/40 (2018.01)
CPC A61C 13/0004 (2013.01) [A61C 5/77 (2017.02); G06N 3/02 (2013.01); G16H 30/40 (2018.01)] 13 Claims
OG exemplary drawing
 
1. A computer-implemented method for providing a representation of a 3D shape of a restorative dental object for a patient, the method comprising:
training, by one or more computing devices and using a plurality of preexisting treatment 3D data sets, a trained machine learning system in an end-to-end manner, wherein the plurality of preexisting treatment 3D data sets comprises 3D images of patients' dentitions and 3D shapes of representations of patients' restorative dental objects and the trained machine learning system includes a convolutional neural network,
inputting a representation of a 3D scan of at least one portion of a patient's dentition to the trained machine learning system, the representation of a 3D scan defining at least one implant position of an implant, the trained machine learning system being installed on one or more computing devices,
accessing a set of parameters used to generate a parametric model, each parameter of the set of parameters having a corresponding range, and each corresponding range having a set of bins having a limited resolution, wherein the set of parameters relate to a characteristic of a tooth surface anatomy, a tooth dentition, or a restoration type,
estimating, by the convolutional neural network, a correct bin of the set of bins for each corresponding range of each parameter of the set of parameters, to obtain optimized parameters for a restorative dental object to correspond with the 3D scan of the at least one portion of the patient's dentition, and
identifying, using the trained machine learning system and based on the optimized parameters of the parametric model, the representation of the 3D shape of the restorative dental object for the implant in an end-to-end manner.