Methods and systems for multiplanar reformation with machine learning based image enhancement

A method for training an image enhancement network, comprising:

• selecting a training data pair comprising input data and a ground truth image sequence, wherein the input data comprises:
• a landmark plane;
• a reformatted image sequence;
• and
• a native image sequence comprising a first plurality of images parallel to a first plane;
• and
• mapping the input data to a predicted resolution enhanced image sequence using the image enhancement network;
• determining a loss based on a difference between the predicted resolution enhanced image sequence and the ground truth image sequence;
• and
• updating parameters of the image enhancement network based on the loss to produce a trained image enhancement network.

An imaging system, comprising:

• an imaging device;
• a display device;
• and
• an image processing system configured with a processor, and executable instructions stored in non-transitory memory, wherein, when executing the instructions, the processor causes the imaging system to:
• determine a landmark plane intersecting a volume;
• acquire an image sequence of the volume based on the landmark plane;
• reformat the image sequence along the landmark plane to produce a first reformatted image sequence;
• map the first reformatted image sequence, the image sequence, and the landmark plane, to a resolution enhanced image sequence, using a trained image enhancement network;
• and
• display the resolution enhanced image sequence via the display device.