Artificial intelligence-based magnetic resonance sequence
AssigneeSiemens Healthineers AG
InventorsSimon Arberet, Dorin Comaniciu
Life of this patent
Estimating the term…
Abstract
For artificial Intelligence-based optimization of a MR sequence, an agent machine trained with reinforcement learning generates the MR pulse sequence for a patient. The agent may generate values for multiple or all the parameters defining the MR pulse sequence. The agent was trained using the end goal or task (e.g., MR map or segmentation) as the reward function, so the MR pulse sequence generated by the agent provides good quality MR imaging. The agent generates the MR pulse sequence quickly and without requiring multiple sequences to be used on the patient.
Claims20
A method of establishing a magnetic resonance (MR) pulse sequence for a MR scanner, the method comprising:
- receiving indications of an environment for MR scanning of a patient;
- establishing the MR pulse sequence for the environment by reinforcement learned artificial intelligence based on input of the environment and a digital twin of the patient, establishing comprising optimization by the reinforcement learned artificial intelligence of the MR pulse sequence in the environment for the digital twin of the patient;
- configuring the MR scanner with the MR pulse sequence;
- and
- imaging the patient by the MR scanner as configured with the MR pulse sequence.
A method for reinforcement machine learning to establish a magnetic resonance (MR) pulse sequence, the method comprising:
- defining a state space representing the MR pulse sequence, a MR scanner, and a virtual object to be scanned;
- parameterizing an action space of the MR pulse sequence with a plurality of objects corresponding to actions changing a characteristic of the MR pulse sequence;
- reinforcement learning, by a processor, an agent, the reinforcement learning simulating different MR pulse sequences, different MR scanners, and different virtual objects of the state space in different combinations where each combination is optimized in the action space;
- and
- storing the agent.
A magnetic resonance (MR) system comprising:
- a MR scanner configured by settings of controls to scan a region of a patient, the scan providing scan data;
- a processor configured by a machine-learned agent to configure the MR scanner, the machine-learned agent using simulation of MR scanning by the MR scanner with different values of the settings through a sequence of simulated actions, the different values optimized by the machine-learned agent where the optimized values are used for the settings of the configuration of the MR scanner.
Dependencies are inferred from the claim text.