- Patent Title: Method and system for deep motion model learning in medical images
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Application No.: US16131465Application Date: 2018-09-14
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Publication No.: US10664979B2Publication Date: 2020-05-26
- Inventor: Julian Krebs , Tommaso Mansi
- Applicant: Siemens Healthcare GmbH
- Applicant Address: DE Erlangen
- Assignee: Siemens Healthcare GmbH
- Current Assignee: Siemens Healthcare GmbH
- Current Assignee Address: DE Erlangen
- Main IPC: G06T17/00
- IPC: G06T17/00 ; G06T7/20 ; G06T7/246 ; G06T7/00 ; A61B5/00

Abstract:
A method and system for computer-based motion estimation and modeling in a medical image sequence of a patient is disclosed. A medical image sequence of a patient is received. A plurality of frames of the medical image sequence are input to a trained deep neural network. Diffeomorphic deformation fields representing estimated motion between the frames of the medical image sequence input to the trained deep neural network are generated. Future motion, or motion between frames, is predicted from the medical image sequence and at least one predicted next frame is generated using the trained deep neural network. An encoding of the observed motion in the medical image sequence is also generated, which is used for motion classification (e.g., normal or abnormal) or motion synthesis to generate synthetic data.
Public/Granted literature
- US20200090345A1 Method and System for Deep Motion Model Learning in Medical Images Public/Granted day:2020-03-19
Information query
IPC分类:
G | 物理 |
G06 | 计算;推算或计数 |
G06T | 一般的图像数据处理或产生 |
G06T17/00 | 用于计算机制图的3D建模 |