Illustrations on MRI Techniques Using Matlab - Digital Signal Processing for Medical Imaging Using Matlab - page 69

Gx1=Gx/(10ˆ3);%This is to indicate that B0 is high compared with x-gradient
for x=0:1:siz-1
for y=0:1:siz-1
%The magnetic moments after applying y-gradient for the duration of
%0.0000000009
temp1=temp1+M(x+1,y+1)*exp(-j*((B0*gamma+gamma*y*d2*Gy1)*0.0000000009+K));
%The magnetic moments after applying negative x-gradient for the duration of
%0.0000000009 after applying the y-gradient for the duration of
%0.0000000009
temp2=temp2+M(x+1,y+1)*exp(-j*((B0*gamma+d2*gamma*y*Gy1)*0.0000000009+K))...
*exp(-j*((B0*gamma-gamma*d1*x*Gx1)*0.0000000009));
%The magnetic moments after applying x-gradient for the duration of
%0.0000000018 after applying the y-gradient for the duration of
%0.0000000009 and negative x-gradient for the duration of 0.0000000009
temp3=temp3+M(x+1,y+1)*exp(-j*((B0*gamma+gamma*d2*y*Gy1)*0.0000000009+K))...
*exp(-j*((B0*gamma-gamma*d1*x*Gx1)*0.0000000009))*...
exp(-j*((B0*gamma+gamma*d1*x*Gx1)*0.0000000018));
end
end
KSPACE(Gx+6,Gy+6)=temp3;
temp1=0;
temp2=0;
temp3=0;
end
end
KSPACEREARRANGED=KSPACE(6:1:11,6:1:11);
KSPACEREARRANGED=[KSPACEREARRANGED KSPACE(6:1:11,1:1:5)];
KSPACEREARRANGED=[KSPACEREARRANGED; KSPACE(1:1:5,6:1:11) KSPACE(1:1:5,1:1:5) ];
RECONSTRUCTED=ifft2(KSPACEREARRANGED)
figure
subplot(1,3,1)
colormap(gray)
imagesc(M)
subplot(1,3,2)
colormap(gray)
imagesc(log(abs(KSPACEREARRANGED)))
subplot(1,3,3)
colormap(gray)
imagesc(abs(RECONSTRUCTED))