aiAreaOpen

matlab/+Segment/aiAreaOpen.m

+function bw=aiAreaOpen(bw,min_radius_pixels)
+
+if ~is3D(bw)
+    % 2d - use pi*r^2 approximation
+    radius=min_radius_pixels(1);
+    area = radius^2 * pi;
+    bw=bwareaopen(bw,area);
+    return;
+end
+
+maskRadius=0.5*min_radius_pixels;
+maskRadius=max(maskRadius,[1,1,1]);
+ee=HIP.MakeEllipsoidMask(maskRadius);
+bwSeeds=imerode(bw,ee);
+bw=imreconstruct(bwSeeds,bw);   

matlab/+Segment/frameSegment.m

@@ -88,7 +88,7 @@ end
 % of those pixels will be discarded in resolving the underlying cells.
 % allocateShake (below) assigns each discarded pixel to it's closest
 % touching segmentation using a morphological region fill
-bw=bwareaopen(bw,min_area_pixels);
+bw=Segment.aiAreaOpen(bw,min_radius_pixels);
 bw2=bw;
 bPhaseReduce=segParams.isPhase || segParams.bCytoplasmic;
 % if prod(size(im))>1e9

matlab/+Segment/segReduce.m

@@ -6,7 +6,6 @@ if bPhaseReduce
     return;
 end
 
-minKernelArea=ceil(0.25*min_area_pixels); %
 if is3D(bw)
     se=strel('sphere',1);
 else
@@ -14,11 +13,11 @@ else
 end
 %
 bwOut=bw;
-
 nIter=100; %10*max(min_radius_pixels);
 for nDilate=1:nIter
     bwKernels=bwOut&~bwLog;
-    bwKernels=bwareaopen(bwKernels,minKernelArea);    
+    bwKernels=Segment.aiAreaOpen(bwKernels,0.5*min_radius_pixels);  
+  
     L=bwlabeln(bwKernels);
     CC=bwconncomp(bwOut);
     workingL=double(labelmatrix(CC));

matlab/+Segment/thresholdImages.m

@@ -14,10 +14,10 @@ end
 if sensitivity>1 && round(sensitivity)==sensitivity
     lm=multithresh(imLog,sensitivity)
     bwLog=logical(imLog>lm(end));
-    bwLog=bwareaopen(bwLog,4*min_area_pixels);
+    bwLog=Segment.aiAreaOpen(bwLog,2*min_radius_pixels);
     lm=multithresh(im,sensitivity)
     bw=logical(im>lm(end));
-    bw=bwareaopen(bw,min_area_pixels);
+    bw=Segment.aiAreaOpen(bw,min_radius_pixels);
     return;
 end
 
@@ -25,12 +25,12 @@ if is3D(im)
     nsz=2*floor(size(im)/16)+1;
     T=adaptthresh(imLog,0.5,'NeighborhoodSize',nsz,'statistic','gaussian');
     bwLog=imbinarize(imLog,T);
-    bwLog=bwareaopen(bwLog,4*min_area_pixels);
+    bwLog=Segment.aiAreaOpen(bwLog,2*min_radius_pixels);
 
     nsz=4*floor(size(im)/16)+1;
     T=adaptthresh(im,sensitivity,'NeighborhoodSize',nsz,'statistic','gaussian');
     bw=imbinarize(im,T);
-    bw=bwareaopen(bw,min_area_pixels);
+    bw=Segment.aiAreaOpen(bw,min_radius_pixels);
     return;
 end
 
@@ -38,7 +38,7 @@ end
 nsz=4*floor(size(im)/16)+1;
 T=adaptthresh(imLog,0.5,'NeighborhoodSize',nsz,'statistic','gaussian');
 bwLog=imbinarize(imLog,T);
-bwLog=bwareaopen(bwLog,4*min_area_pixels);
+bwLog=Segment.aiAreaOpen(bwLog,2*min_radius_pixels);
 
 if segParams.isPhase
     [bw,bwLog]=phaseThreshold(im,bwLog,min_radius_pixels,segParams,...
@@ -49,7 +49,7 @@ else
     T=adaptthresh(im,sensitivity,'NeighborhoodSize',4*floor(size(im)/16)+1,'statistic','gaussian');
     bw=imbinarize(im,T);
 end
-bw=bwareaopen(bw,min_area_pixels);
+bw=Segment.aiAreaOpen(bw,min_radius_pixels);
 4;
 
 function [bw,bwLog]=phaseThreshold(im,bwLog,min_radius_pixels,segParams,...