diff --git a/src/MATLAB/ssf_vs_cn/goFigure3-C.m b/src/MATLAB/ssf_vs_cn/goFigure3C.m
similarity index 73%
rename from src/MATLAB/ssf_vs_cn/goFigure3-C.m
rename to src/MATLAB/ssf_vs_cn/goFigure3C.m
index 7fb9db14f7c002214f291ba2937837f7c828f10c..e44eb3b545e2e00da09716f154096fbbbd6434ea 100644
--- a/src/MATLAB/ssf_vs_cn/goFigure3-C.m
+++ b/src/MATLAB/ssf_vs_cn/goFigure3C.m
@@ -1,5 +1,6 @@
 
 cnRatios = zeros(9,100);
+ccnRatios = zeros(9,100);
 ssfVals = zeros(9,100);
 
 % i = 9;
@@ -8,11 +9,11 @@ for i = 1:10
     for j = 1:100
         
 %         [cnRatio,ssfVal] = ssfPhantom(i/10);
-        [cnRatio,ssfVal] = ssfPhantom((i-1)/10);
+        [cnRatio,ccnRatio, ssfVal] = ssfPhantom((i-1)/10);
         
         cnRatios(i,j) = cnRatio;
         ssfVals(i,j) = ssfVal;
-        
+        ccnRatios(i,j) = ccnRatio;
     end
 end
 
@@ -25,6 +26,9 @@ sc = std(cnRatios,0,2);
 ms = mean(ssfVals,2);
 ss = std(ssfVals,0,2);
 
+mccn = mean(ccnRatios,2);
+sccn = std(ccnRatios,0,2);
+
 msNorm = mean(ssfVals,2)./ssfRefVal;
 ssNorm = std(ssfVals./ssfRefVal,0,2);
 
@@ -33,7 +37,8 @@ figure;
 
 plot([1:-.1:.1],'color','y','LineWidth',4,'linestyle','-'); hold on;
 errorbar(mc,sc/(2*sqrt(size(ssfVals,2))),'color','r')
-errorbar(ms,ss/(2*sqrt(size(ssfVals,2))),'color',[0.4660 0.6740 0.1880])
+errorbar(mccn,sccn/(2*sqrt(size(ssfVals,2))),'color',[0.4660 0.6740 0.1880])
+errorbar(ms,ss/(2*sqrt(size(ssfVals,2))),'color','m')
 % errorbar(msNorm,ssNorm/(2*sqrt(size(ssfVals,2))),'-ro','color','k','markersize',8,'markerfacecolor','r');
 errorbar(msNorm,ssNorm/(2*sqrt(size(ssfVals,2))),'color','k');
 
@@ -49,7 +54,8 @@ ylabel('Cell signal activation')
 % set(gca, 'YScale', 'log')
 
 % legend('GT','Nuclear/Cyto Ratio','LoG','SSF')
-legend('GT','CN_{ratio}','LoG','SSF')
+% legend('GT','CN_{ratio}','LoG','SSF','\frac{C}{C+N}')
+legend('GT','$\frac{C}{N}$','$\frac{C}{C+N}$','LoG','SSF','Interpreter','latex')
 set(gcf,'color','white')
 ylim([0 5])
 
@@ -57,7 +63,7 @@ f = getframe(gcf);
 
 cap = frame2im(f);
 outName = 'phantomLinear.tif';
-outRoot = 'F:\leverjs\agne\images\ssfFigures';
+outRoot = './';
 
 outFile = fullfile(outRoot,outName);
 imwrite(cap,outFile);
diff --git a/src/MATLAB/ssf_vs_cn/phantomLinear.tif b/src/MATLAB/ssf_vs_cn/phantomLinear.tif
new file mode 100644
index 0000000000000000000000000000000000000000..e53eae496b03a35d5f5daf4f62c6e3505acb5285
Binary files /dev/null and b/src/MATLAB/ssf_vs_cn/phantomLinear.tif differ
diff --git a/src/MATLAB/phantomSSF/ssfPhantom.m b/src/MATLAB/ssf_vs_cn/ssfPhantom.m
similarity index 86%
rename from src/MATLAB/phantomSSF/ssfPhantom.m
rename to src/MATLAB/ssf_vs_cn/ssfPhantom.m
index 41232694da699b5ef33b20b98abd941d1f3e0e29..fbddbe8c8d7f0f1dc001393b30a8779167a4ad67 100644
--- a/src/MATLAB/phantomSSF/ssfPhantom.m
+++ b/src/MATLAB/ssf_vs_cn/ssfPhantom.m
@@ -1,4 +1,4 @@
-function [cnRatio,ssfValue] = ssfPhantom(density)
+function [cnRatio,ccnRatio, ssfValue] = ssfPhantom(density)
 
 % set width/length of the image
 wl = 200;
@@ -45,6 +45,7 @@ imNoiseLoG = HIP.LoG(imNoise(:,:,1),logRadius,targetDevice);
 
 % cnRatio = mean(imNoise(idxNuclear))/mean(imNoise(idxCyto));
 cnRatio = mean(imNoise(idxCyto))/mean(imNoise(idxNuclear));
+ccnRatio = mean(imNoise(idxCyto)) / (mean(imNoise(idxCyto))+mean(imNoise(idxNuclear)));
 ssfValue = max(imNoiseLoG(:));
 
 end
\ No newline at end of file