Self-supervised machine learning for medical image reconstruction
AssigneeSiemens Healthcare GmbH
InventorsSimon Arberet, Mariappan S. Nadar, Mahmoud Mostapha, Dorin Comaniciu
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Abstract
For reconstruction in medical imaging, self-consistency using data augmentation is improved by including data consistency. Artificial intelligence is trained based on self-consistency and data consistency, allowing training without supervision. Fully sampled data and/or ground truth is not needed but may be used. The machine-trained model is less likely to reconstruct images with motion artifacts, and/or the training data may be more easily gathered by not requiring full sampling.
Claims20
A method of machine training for magnetic resonance (MR) reconstruction in medical imaging, the method comprising:
- acquiring MR training data;
- generating augmentation data from the MR training data;
- machine training a neural network for the MR reconstruction using the training data and the augmentation data, wherein the machine training uses (1) a self-consistency loss between pairs of MR training data and/or augmentation data and (2) a data-consistency loss and/or data-consistency constraint;
- and
- storing the neural network as machine trained.
A method for reconstruction of a medical image in a medical imaging system, the method comprising:
- scanning, by the medical imaging system, a patient, the scanning resulting in measurements;
- reconstructing, by an image processor applying a machine-learned model, the medical image from the measurements, the machine-learned model having been trained with both self-consistency and data consistency;
- and
- displaying the medical image.
A system for reconstruction in medical imaging, the system comprising:
- a medical scanner configured to scan a patient;
- an image processor configured to reconstruct a representation of the patient, the image processor configured to reconstruct by application of a machine-learned model having been trained for the reconstruction based on self-supervised learning from augmentation with data consistency;
- and
- a display configured to display an image of the patient, the image formed from the representation.
Dependencies are inferred from the claim text.