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    PATIENT AND CONSUMER DATA DE-IDENTIFICATION
    3.
    发明公开
    PATIENT AND CONSUMER DATA DE-IDENTIFICATION 审中-公开

    公开(公告)号：US20230352150A1

    公开(公告)日：2023-11-02

    申请号：US18140196

    申请日：2023-04-27

    申请人： Align Technology, Inc.

    发明人： Eric P. Meyer ,  Christopher E. Cramer ,  Doruk Cetin ,  Niko Benjamin Huber ,  Chad Clayton Brown

    IPC分类号： G16H30/40 ,  G16H10/60

    CPC分类号： G16H30/40 ,  G16H10/60

    摘要： The present technology provides solutions for anonymizing patient data and in particular, for anonymizing potentially unique patient-identifying information while retaining clinically relevant information, for example, that can be used to illustrate the results or outcomes of a clinical intervention. In some aspects, a process of the disclosed technology can include steps for receiving patient data, wherein the patient data comprises a patient image corresponding with a patient, receiving treatment data, wherein the treatment data is based on a treatment goal for the patient, automatically determining, using one or more semantic controls, one or more anonymization parameters for the patient image; and generating, based on the one or more anonymization parameters, an anonymized patient image. Systems and machine-readable media are also provided.

    EXCESS MATERIAL REMOVAL USING MACHINE LEARNING
    6.
    发明申请
    EXCESS MATERIAL REMOVAL USING MACHINE LEARNING 审中-公开

    公开(公告)号：US20200349698A1

    公开(公告)日：2020-11-05

    申请号：US16865162

    申请日：2020-05-01

    申请人： Align Technology, Inc.

    发明人： Mikhail Minchenkov ,  Ran Katz ,  Pavel Agniashvili ,  Chad Clayton Brown ,  Jonathan Coslovsky

    IPC分类号： G06T7/00 ,  A61C13/34 ,  A61C9/00 ,  G06N3/08 ,  G06N3/04 ,  G06T17/00 ,  G06K9/62 ,  G06T19/20

    摘要： A method includes processing an input comprising data from an intraoral image using a trained machine learning model that has been trained to classify regions of dental sites, wherein the trained machine learning model outputs a probability map comprising, for each pixel in the intraoral image, a first probability that the pixel belongs to a first dental class and a second probability that the pixel belongs to a second dental class, wherein the first dental class represents excess material, the excess material comprising material other than teeth or gums. The method further includes determining, based on the probability map, one or more pixels in the intraoral image that are classified as excess material. The method further includes hiding or removing from the intraoral image data for the one or more pixels that are classified as excess material.