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US 11,107,211 B2Granted
Medical imaging method and system and non-transitory computer-readable storage medium
AssigneeGE Precision Healthcare LLC
InventorsDan Wu, Kun Wang, Weinan Tang, Longqing Wang
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Abstract
The present application provides a medical imaging method and system and a non-transitory computer-readable storage medium. The medical imaging method comprises identifying an image quality type of a medical image based on a trained learning network, and generating, based on the identified image quality type, a corresponding control signal for controlling a medical imaging system.
Claims17
A medical imaging method, comprising:
- identifying an image quality type of a medical image based on a trained learning network;
- generating, based on the identified image quality type, a corresponding control signal for controlling a medical imaging system;
- wherein the image quality type comprises one or a plurality of artifact types;
- and
- wherein when the medical image is identified as an acceleration artifact in a magnetic resonance image, a first control signal is generated to control the medical imaging system to send a warning signal for adjusting an acceleration factor.
2 more elements
A medical imaging system, comprising:
- an identification module, configured to identify, based on a trained learning network, an image quality type of a medical image generated by the medical imaging system;
- a control module, configured to generate, based on the identified image quality type, a corresponding control signal for controlling the medical imaging system;
- wherein the image quality type comprises one or a plurality of artifact types;
- and
- wherein the control module comprises a first control unit configured to generate a first control signal based on an acceleration artifact type in a magnetic resonance image outputted by the identification module, so as to control the medical imaging system to send a warning signal for adjusting an acceleration factor.
2 more elements
The medical imaging method, comprising:
- identifying an image quality type of a medical image based on a trained learning network;
- generating, based on the identified image quality type, a corresponding control signal for controlling a medical imaging system;
- wherein the image quality type comprises one or a plurality of artifact types;
- and
- wherein the medical image is identified as a Nyquist artifact in a magnetic resonance image, a second control signal is generated to control the medical imaging system to start a calibration mode.
2 more elements
Dependencies are inferred from the claim text.