Multimodal data fusion for coronary heart disease diagnostics and prognostics from non-invasive imaging

A system, comprising:

• one or more processors;
• and
• memory storing instructions that, when executed by the one or more processors, cause the system to perform operations comprising:
• receiving data associated with two or more imaging modalities, at least one of the imaging modalities comprising an inference imaging modality and at least one of the imaging modalities comprising a training-only imaging modality;
• determining annotations in the data associated with the training-only imaging modality;
• registering data associated with the inference imaging modality and data associated with the training-only imaging modality;
• and
• training at least one statistical model to predict features in the inference imaging modality based on the data associated with the training-only imaging modality, the data associated with the inference imaging modality, and the annotations in the data associated with the training-only imaging modality.

A non-transitory computer-readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:

• receiving data associated with two or more imaging modalities, at least one of the imaging modalities comprising an inference imaging modality and at least one of the imaging modalities comprising a training-only imaging modality;
• determining annotations in the data associated with the training-only imaging modality;
• registering data associated with the inference imaging modality and data associated with the training-only imaging modality;
• and
• training at least one statistical model to predict features in the inference imaging modality based on the data associated with the training-only imaging modality, the data associated with the inference imaging modality, and the annotations in the data associated with the training-only imaging modality.