1. 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;

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

3. Image Artifacts
SENSE
GRAPPA

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