Deep learning techniques for alignment of magnetic resonance images

At least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by at least one processor, cause the at least one processor to perform a method for generating magnetic resonance (MR) images of a subject from MR data obtained by a magnetic resonance imaging (MRI) system, the method comprising:

• obtaining first input MR data obtained by imaging the subject using the MRI system;
• obtaining second input MR data obtained by imaging the subject using the MRI system;
• generating a first set of one or more MR images from the first input MR data;
• generating a second set of one or more MR images from the second input MR data;
• aligning the first set of MR images and the second set of MR images using a neural network model to obtain aligned first and second sets of MR images, the neural network model comprising a first neural network and a second neural network, the aligning comprising:
• estimating, using the first neural network, a first transformation between the first set of MR images and the second set of MR images;
• generating a first updated set of MR images from the second set of MR images using the first transformation;
• estimating, using the second neural network, a second transformation between the first set of MR images and the first updated set of MR images;
• and
• aligning the first set of MR images and the second set of MR images at least in part by using the first transformation and the second transformation;
• combining the aligned first and second sets of MR images to obtain a combined set of one or more MR images;
• and
• outputting the combined set of one or more MR images.

A magnetic resonance imaging (MRI) system, comprising:

• a magnetics system having a plurality of magnetics components to produce magnetic fields for performing MRI;
• and
• at least one processor configured to perform:
• obtaining first input MR data by imaging the subject using the MRI system;
• obtaining second input MR data by imaging the subject using the MRI system;
• generating a first set of one or more MR images from the first input MR data;
• generating a second set of one or more MR images from the second input MR data;
• aligning the first set of MR images and the second set of MR images using a neural network model to obtain aligned first and second sets of MR images, the neural network model comprising a first neural network and a second neural network, the aligning comprising:
• estimating, using the first neural network, a first transformation between the first set of MR images and the second set of MR images;
• generating a first updated set of MR images from the second set of MR images using the first transformation;
• estimating, using the second neural network, a second transformation between the first set of MR images and the first updated set of MR images;
• and
• aligning the first set of MR images and the second set of MR images at least in part by using the first transformation and the second transformation;
• combining the aligned first and second sets of MR images to obtain a combined set of one or more MR images;
• and
• outputting the combined set of one or more MR images.