公开(公告)号：US20220005222A1

公开(公告)日：2022-01-06

申请号：US17280698

申请日：2019-09-24

Applicant: OSAKA UNIVERSITY

Inventor： Chihiro TANIKAWA ,  Chonho LEE

IPC: G06T7/73 ,  A61B6/00 ,  A61C7/00 ,  G06N20/00

Abstract: A technique for automating the identifying of a measurement point in cephalometric image analysis is provided. An automatic measurement point recognition method includes a step of detecting, from a cephalometric image 14 acquired from a subject, a plurality of peripheral partial regions 31, 32, 33, 34 for recognizing a target feature point, a step of estimating a candidate position of the feature point in each of the peripheral partial regions 31, 32, 33, 34 by the application of a regression CNN model 10, and a step of determining the position of the feature point in the cephalometric image 14 based on the distribution of the candidate positions estimated. In the step of detecting, for example, the peripheral partial region 32, a classification CNN model 13 trained with a control image 52 is applied.

公开(公告)号：US20210275281A1

公开(公告)日：2021-09-09

申请号：US17315896

申请日：2021-05-10

Applicant: OSAKA UNIVERSITY

Inventor： Chihiro TANIKAWA ,  Kenji TAKADA

IPC: A61C7/00 ,  G16H30/40 ,  A61B34/10 ,  G16H50/50

Abstract: To have convenient and highly precise prediction of the shape of a human body after a treatment by calculation processing that includes extracting a feature vector Fnew from face data of a patient as an evaluation subject, selecting a plurality of case patients having feature vectors Fpre(i), extracted from the face data of a plurality of previous patients, obtaining pre-orthodontic facial shape models Hpre(i) and a post-orthodontic facial shape models Hpost(i) in which the faces of the selected previous case patients before and after a treatment have been normalized, obtaining a facial shape model Hnew, and obtaining a three-dimensional predicted facial shape model Hprd, by modifying the facial shape model Hnew of the patient as an evaluation subject, using a vector average difference AVEpost−AVEpre between the pre-treatment and post-treatment facial shape models.

公开(公告)号：US20180311013A1

公开(公告)日：2018-11-01

申请号：US15770461

申请日：2016-10-21

Applicant: OSAKA UNIVERSITY

Inventor： Chihiro TANIKAWA ,  Kenji TAKADA

IPC: A61C7/00 ,  G16H50/50 ,  A61B34/10

CPC classification number: A61C7/00

Abstract: To have convenient and highly precise prediction of the shape of a human body after a treatment by calculation processing.It includes a step of extracting a feature vector Fnew from face data of a patient as an evaluation subject, a step of selecting a plurality of case patients having feature vectors Fpre(i), extracted from the face data of a plurality of previous patients, that have a short distance from the feature vector Fnew, or a step of selecting a similar case class having a cluster center Gpre(l) that has a short distance from the feature vector Fnew, a step of obtaining pre-orthodontic facial shape models Hpre(i) and a post-orthodontic facial shape models Hpost(i) in which the faces of the selected previous case patients before and after a treatment have been normalized, a step of obtaining a facial shape model Hnew in which the face of the patient as an evaluation subject has been normalized, and a step of obtaining a three-dimensional predicted facial shape model Hprd as predicted after orthodontic treatment, by modifying the facial shape model Hnew of the patient as an evaluation subject, using a vector average difference AVEpost−AVEpre between the pre-treatment and post-treatment facial shape models of case patients having a facial shape similar to that of the patient as an evaluation subject.