Invention Grant
- Patent Title: Quantitative mapping by data-driven signal-model learning
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Application No.: US16426486Application Date: 2019-05-30
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Publication No.: US11587675B2Publication Date: 2023-02-21
- Inventor: Tom Hilbert , Tobias Kober
- Applicant: SIEMENS HEALTHCARE GMBH
- Applicant Address: DE Erlangen
- Assignee: SIEMENS HEALTHCARE GMBH
- Current Assignee: SIEMENS HEALTHCARE GMBH
- Current Assignee Address: DE Erlangen
- Agent Laurence A. Greenberg; Werner H. Stemer; Ralph E. Locher
- Priority: EP18175213 20180530
- Main IPC: G16H50/20
- IPC: G16H50/20 ; G06N20/00 ; G06F16/28 ; G06F16/22 ; G06N3/08

Abstract:
A system and a method determine a value for a parameter. Reference values for the parameter are determined from a group of objects. A first technique is used by the system for determining for each object the reference value from a first set of data. A learning dataset is created by associating for each object of the group of objects a second set of data and the reference value. The second set of data is acquired by the system according to a second technique for determining values of the parameter and is configured for enabling a determination of the parameter. A machine learning technique trained on the learning dataset is used for determining a value of the parameter. The second set of data obtained for each of the objects is used as input in a machine learning algorithm and its associated reference value is used as output target.
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