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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).
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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
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).
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