Predicting the likelihood of contrast enhanced imaging findings from non-contrast imaging
AssigneeSiemens Healthineers AG
InventorsTeodora Marina Chitiboi, Andreea Bianca Popescu
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Abstract
Systems and methods for determining a likelihood of contrast-enhanced imaging findings of a patient are provided. One or more non-contrast medical images of a patient are received. A likelihood of contrast-enhanced imaging findings of the patient is determined based on the one or more non-contrast medical images using a machine learning based system. The likelihood of contrast-enhanced imaging findings is output.
Claims20
A computer-implemented method comprising:
- receiving one or more non-contrast medical images of a patient;
- determining a likelihood of contrast-enhanced imaging findings of the patient based on the one or more non-contrast medical images using a machine learning based system;
- and
- outputting the likelihood of contrast-enhanced imaging findings.
An apparatus comprising:
- means for receiving one or more non-contrast medical images of a patient;
- means for determining a likelihood of contrast-enhanced imaging findings of the patient based on the one or more non-contrast medical images using a machine learning based system;
- and
- means for outputting the likelihood of contrast-enhanced imaging findings.
A non-transitory computer-readable storage medium comprising instructions which, when executed by a computer, cause the computer to carry out operations comprising:
- receiving one or more non-contrast medical images of a patient;
- determining a likelihood of contrast-enhanced imaging findings of the patient based on the one or more non-contrast medical images using a machine learning based system;
- and
- outputting the likelihood of contrast-enhanced imaging findings.
Dependencies are inferred from the claim text.