This is a MATLAB-based tutorial on iterative, non-Cartesian image reconstruction applied to a Compressed Sensing problem, all done in plain MATLAB with no external dependencies. The purpose of this worked example is to clearly demonstrate the steps involved in defining the linear transforms associated with non-Cartesian Fourier sampling and finite differences for TV-regularisation, and optimising cost functions by computing gradients. The tutorial can be accessed from the link above, or downloaded directly below as a MATLAB live script or plain script.
For an html-rendered version of the tutorial, please click here