Coil mixing error matrix and deep learning for prospective motion assessment
AssigneesSiemens Healthcare GmbH, The General Hospital Corporation
InventorsDaniel Nicolas Splitthoff, Julian Hossbach, Daniel Polak, Stephen Farman Cauley, Bryan Clifford, Wei-Ching Lo
Life of this patent
Estimating the term…
Abstract
Systems and Methods that identify the effect of motion during a medical imaging procedure. A neural network is trained to translate motion induced deviations of a coil-mixing matrix relative to a reference acquisition into a motion score. This score can be used for the prospective detection of the most corrupted echo trains for removal or triggering a replacement by reacquisition.
Claims20
A method for prospective or retrospective motion identification during an acquisition of magnetic resonance (MR) images of a patient by an imaging system, the method comprising:
- acquiring a motion free reference;
- calculating, based on the motion free reference, a first coil mixing matrix representing a linear combination of coils of the imaging system;
- applying the first coil mixing matrix to the motion free reference to generate a linearly combined reference data;
- acquiring MR data for the patient from the imaging system and applying the first coil mixing matrix to the MR data to generate linearly combined motion data;
- determining a second coil mixing matrix for a respective subset of MR data based on the linearly combined motion data;
- inputting the second coil mixing matrix into a neural network trained to output a motion assessment for the acquired MR data;
- and
- providing the motion assessment generated by the neural network to an operator.
A method for prospective or retrospective motion identification during an acquisition of magnetic resonance (MR) images of a patient by an imaging system, the method comprising:
- acquiring a motion free reference;
- calculating, based on the motion free reference, a first coil mixing matrix representing a linear combination of coils of the imaging system;
- acquiring MR data for the patient from the imaging system and applying the first coil mixing matrix to the MR data to generate linearly combined motion data;
- calculating a second coil mixing matrix for a respective subset of MR data based on the linearly combined motion data;
- calculating a difference coil mixing error matrix for a respective subset of MR data based on the difference of the first coil mixing matrix and the second coil mixing matrix;
- inputting the difference coil mixing error matrix into a neural network trained to output a motion assessment for the acquired MR data;
- and
- providing the motion assessment generated by the neural network to an operator.
A system for prospective or retrospective motion identification during an acquisition of magnetic resonance data of a patient, the system comprising:
- a magnetic resonance imaging system configured to acquire motion free reference data and magnetic resonance data;
- a processor configured to calculate, based on the motion free reference data, a scout coil mixing matrix and to calculate, based on the scout coil mixing matrix and the magnetic resonance data, a coil mixing error matrix, a coil mixing matrix, or the coil mixing error matrix and the coil mixing matrix;
- a neural network configured to output a motion assessment when input the coil mixing error matrix, the coil mixing matrix, or the coil mixing error matrix and the coil mixing matrix;
- and
- an output device configured to output the motion assessment from the neural network during an imaging procedure for the acquisition of the magnetic resonance data.
Dependencies are inferred from the claim text.