# MRI image reconstruction - reduced scan pecentage

I have an MRI kspace from a siemens 1.5 T scanner with reduced scan percentage ( sampled truncation by not acquiring the most peripheral lines in kspace). The kspace plot in matlab look like below.

I can do zero filling in this kspace to the required resolution and reconstruct images.

Other than zero filling, is there another method which can estimate missing lines and reconstruction images.

I would say no, there isn't. This is unmeasured information and you cannot compute it without additional information (ie some additionally sampled data, and maybe some compressed sensing algorithm). However, truncating an image like that in order to save measurement time is quite unusual. You would be better off to sample one side full and skip twice the number of lines on one side of $$k$$-space. You could then use additional information (in this case: the object is real and should be shimmed well, ie you know that the image data should be real). The $$k$$-space of a real image is Hermitian, and you could use the sampled information of the one side outer part to use the Hermitian symmetry to fill the missing lines. Different algorithms for this exist.