Published March 19, 2020
| Version v1
Patent
Method and System for Deep Motion Model Learning in Medical Images
Creators
Contributors
Others:
- Siemens Healthineers, Digital Services, Digital Technology and Innovation
- E-Patient : Images, données & mOdèles pour la médeciNe numériquE (EPIONE) ; Inria Sophia Antipolis - Méditerranée (CRISAM) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
Description
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.
Additional details
Identifiers
- URL
- https://hal.archives-ouvertes.fr/hal-02536459
- URN
- urn:oai:HAL:hal-02536459v1
Origin repository
- Origin repository
- UNICA