Invention Grant
- Patent Title: Methods for estimating mechanical properties from magnetic resonance elastography data using artificial neural networks
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Application No.: US16764838Application Date: 2018-11-19
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Publication No.: US11543481B2Publication Date: 2023-01-03
- Inventor: Matthew C. Murphy , Richard L. Ehman , Kevin J. Glaser , Joshua D. Trzasko , Armando Manduca , John Huston, III , Jonathan M. Scott , Arvin Forghanian-Arani
- Applicant: Mayo Foundation for Medical Education and Research
- Applicant Address: US MN Rochester
- Assignee: Mayo Foundation for Medical Education and Research
- Current Assignee: Mayo Foundation for Medical Education and Research
- Current Assignee Address: US MN Rochester
- Agency: Quarles & Brady LLP
- International Application: PCT/US2018/061779 WO 20181119
- International Announcement: WO2019/099986 WO 20190523
- Main IPC: G01R33/563
- IPC: G01R33/563 ; A61B5/055 ; A61B5/00 ; G01R33/30 ; G01R33/56 ; G06N3/04 ; G06N3/08
Abstract:
Magnetic resonance elastography (“MRE”), or other imaging-based elastography techniques, generate estimates of the mechanical properties, such as stiffness and damping ratio, of tissues in a subject. A machine learning approach, such as an artificial neural network, is implemented to perform an inversion of displacement data in order to generate the estimates of the mechanical properties.
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