For a low-field MRI system, the inverse calculation of the encoding
matrix is time consuming and moreover, there is a blurry area at the center of
the reconstructed image. To solve this problem, three strategies are proposed.
Firstly, QR decomposition is applied to inverse the matrix to eliminate the
blurry area. Secondly, the encoding matrix is separated so that the results of the matrix inverse can be
reused. Last, the size of encoding matrix is reduced by optimizing sample points. One
example is given, the calculation time is reduced, and the imaging quality is improved.
The proposed approach increases the imaging capability of a low-field MRI
system.
