Gradient non-linearity compensation in moving table MRI

A method of correcting gradient non-linearities in moving table MR imaging comprising the steps of:

• translating a patient on a movable table within a magnet;
• acquiring MR data in a presence of gradient non-linearity;
• reconstructing a portion of the MR data into an image;
• correcting any warping in the portion of the MR data that is acquired in the presence of gradient non-linearity while in an image domain;
• and
• shifting the MR data acquired and reconstructed to compensate for table motion.

An MR apparatus having gradient non-linearity compensation for moving objects comprising:

• a magnetic resonance imaging system having a plurality of gradient coils positioned about a bore of a magnet to impress a polarizing magnetic field and an RF transceiver system and an RF switch controlled by a pulse module to transmit RF signals to an RF coil assembly to acquire MR images;
• a movable table to translate an imaging object about the magnet;
• and
• a computer programmed to:
• translate the moving table through the bore of the magnet;
• acquire MR data of an imaging object positioned on the moving table as the movable table is translated through the bore of the magnet;
• process the MR data acquired by one of point-by-point and line-by-line;
• perform a 1-D FT on the MR data in a direction of table motion;
• perform at least one additional FT on the MR data;
• apply a GradWrap function on the MR data;
• and
• fill an image space with the MR data.

A computer program for compensating for gradient non-linearities in moving table MR imaging, the computer program comprising a set of instructions to cause a computer to:

• move a patient table with respect to a gradient coil;
• acquire a plurality of MR data points;
• place at least one MR data point into a matrix sized based on a desired image dimension sought wherein a remainder of the matrix has zeros therein;
• perform an FFT, a type of which is based on the desired image dimension sought, to each MR data point;
• apply a GradWrap function to the MR data points;
• correct each MR data point for patient table motion;
• and
• add each MR data point to build up an image.