SENSE is simple! % load up data (coil maps in s1 & s2; images in im1 & im2) load sense_data.mat; %im is output matrix [Nx Ny]=size(im1); im=zeros(2*Nx,Ny); % SENSE (neglecting noise covariance) for x=1:Nx, dx=mod((x-1+Nx/2),Nx)+1; for y=1:Ny, S=[s1(x,y) s1(x+Nx,y); s2(x,y) s2(x+Nx,y)]; d=[im1(dx,y); im2(dx,y)]; % SENSE inversion step m=pinv(S)*d; im(x,y)=m(1); im(x+Nx,y)=m(2); end;

Basic SENSE x x x x Coil 1 Coil 2 SENSE reconstructed x x x x Image 1

Image Artifacts SENSE GRAPPA

Reduced Distortion EPI, 128x256 Non-Accelerated GRAPPA, R=3