公开(公告)号：US11657600B2

公开(公告)日：2023-05-23

申请号：US17765795

申请日：2020-10-01

Applicant: Adent ApS

Inventor： Richard Bundsgaard ,  Thøger Bundsgaard

IPC: G06V10/776 ,  G16H50/30 ,  G16H30/40 ,  G06V10/56 ,  G06V10/77 ,  G06V10/778 ,  G06V10/82 ,  G06V10/764 ,  G06T7/00

CPC classification number: G06V10/776 ,  G06T7/0012 ,  G06V10/56 ,  G06V10/764 ,  G06V10/7715 ,  G06V10/7796 ,  G06V10/82 ,  G16H30/40 ,  G16H50/30 ,  G06T2207/30036 ,  G06V2201/033

Abstract: A method for remotely assessing oral health of a user of a mobile device by obtaining, using the mobile device (40), at least one digital image (1) of said user's (30) oral cavity (31) and additional non-image data (2) comprising anamnestic information about the user (30). The digital image (1) is processed both using a statistical object detection algorithm (20) to extract at least one local visual feature (3) corresponding to a medical finding related to a sub-region of said user's oral cavity (31); and also using a statistical image recognition algorithm (21) to extract at least one global classification label (4) corresponding to a medical finding related to said user's oral cavity (31) as a whole. An assessment (10) of the oral health of said user (30) is determined based on the local visual feature(s) (3), the global classification label(s) (4) and the non-image data (2).

公开(公告)号：US11826176B2

公开(公告)日：2023-11-28

申请号：US17908724

申请日：2021-02-26

Applicant: Adent ApS

Inventor： Richard Bundsgaard ,  Thøger Bundsgaard

IPC: A61B5/00 ,  G06T7/10 ,  G06V40/10 ,  A61B1/24 ,  A61C13/34

CPC classification number: A61B5/7275 ,  A61B1/24 ,  A61B5/0022 ,  A61B5/0088 ,  A61B5/4547 ,  A61B5/4552 ,  A61B5/6898 ,  A61B5/7267 ,  A61B5/743 ,  A61B5/7475 ,  A61C13/34 ,  G06T7/10 ,  G06V40/10 ,  G06T2207/10024 ,  G06T2207/20081 ,  G06T2207/30036

Abstract: A computer program and computer-based system for remotely assessing oral health of a person by obtaining at least one digital image (1) of the person's oral cavity and additional non-image data (2) comprising anamnestic information about the person (30). The digital images (1) are segmented using statistical image segmentation algorithms (101,102) to extract visible segments (3), which are further processed to predict any invisible segments (6). The resulting segments are processed by a statistical object detection algorithm (104) using the non-image data (2) as further input to identify dental features (7), which are filtered to select only risk-related dental features (8) using a risk database (9) and mapped to respective tooth regions (11) or oral cavity regions (12) in an Oral Risk Atlas (10).