Self ensembling techniques for generating magnetic resonance images from spatial frequency data

A system for generating, from magnitude MR images, training data for training a neural network model to process data to be collected by a target MRI system, the training data comprising the magnitude MR images and synthetic spatial frequency data generated from the magnitude MR images in part by using characteristics of the target MRI system, the system comprising:

• at least one computer hardware processor configured to perform:
• (A) obtaining a reference MR volume comprising one or more magnitude MR images;
• (B) updating the reference MR volume, using a target field of view and/or target image resolution for the target MRI system, to obtain an updated MR volume;
• (C) generating synthetic phase and adding the generated synthetic phase to the updated MR volume to obtain a target MR volume;
• and
• (D) generating, from the target MR volume and using one or more of the characteristics of the target MRI system, multiple sets of spatial frequency data to be used as part of the training data for training the neural network model to process the data to be collected by the target MRI system.

At least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by at least one computer hardware processor, cause the at least one computer hardware processor to perform a method for generating, from magnitude MR images, training data for training a neural network model to process data to be collected by a target MRI system, the training data comprising the magnitude MR images and synthetic spatial frequency data generated from the magnitude MR images in part by using characteristics of the target MRI system, the method comprising:

• (A) obtaining a reference MR volume comprising one or more magnitude MR images;
• (B) updating the reference MR volume, using a target field of view and/or target image resolution for the target MRI system, to obtain an updated MR volume;
• (C) generating synthetic phase and adding the generated synthetic phase to the updated MR volume to obtain a target MR volume;
• and
• (D) generating, from the target MR volume and using one or more of the characteristics of the target MRI system, multiple sets of spatial frequency data to be used as part of the training data for training the neural network model to process the data to be collected by the target MRI system.