clear
% folder containing images
folder = 'pics\Cropped Feature Test Pics\';
celltype = {'neutrophil'
'monocyte'
'lymphocyte'
'eosinophil'
'basophil'};
for j = 1:5
for i = 1:5
% filename of relevant pictures
pic = strcat(folder, celltype{j}, '_', num2str(i), '.tif');
picf = imread(pic);
[AAfilnuc Afin] = trial3(picf,1);
figure(10+j)
subplot(2,3,i)
%figure(10*j+i)
%clf
% saves matrix containing picture values to text file
%dlmwrite(strcat(folder, celltype{j},num2str(i), '_nucleus', 'bw'),AAfilnuc)
% saves image; change AAfilnuc (crop) to Afin (composite)
imwrite(AAfilnuc,strcat(folder, celltype{j},num2str(i), '_nucleus', 'crop.bmp'))
imshow(Afin)
[AAfilcell Afin] = trial3(picf,4);
figure(15+j)
subplot(2,3,i)
%figure(10*j+i+5)
%clf
% saves matrix containing picture values to text file
%dlmwrite(strcat(folder, celltype{j},num2str(i), '_cell', 'bw'),AAfilcell)
% saves image; change AAfilnuc (crop) to Afin (composite)
imwrite(AAfilcell,strcat(folder, celltype{j},num2str(i), '_cell', 'crop.bmp'))
imshow(Afin)
%figure(20+j)
%subplot(2,3,i)
%AAfilcomp =times(AAfilcell,AAfilnuc);
%Afin =times(AAfilcomp,picf(:,:,2));
%imshow(Afin)
end
end
figure(1)
close
figure(2)
close
figure(3)
close
figure(4)
close
figure(5)
close
figure(6)
close
function [AAfil Afin] = trial3(pic,cellnuc)
A = pic;
A1=A(:,:,1);%red,not very informative
A2=A(:,:,2);%green, the channel that we're using
A3=A(:,:,3);%blue, not very informative
figure(1)
imshow(A2)
h = uint8(ones(2,2));
%imshow(A1)%red, not using
figure(2)
imshow(A2)%greenchannel
figure(3)
%imshow(A3)%blue,not using
thresh=multithresh(A2,5);%use autothresholding to get the threshold value.
thresh = thresh(cellnuc); %thresh(1) for nucleus; thresh(2) for cell
%separate red blood cell from the white blood cells
AA=A2<thresh;%get the WBC into bright, RBC into black
imshow(AA) %show the binary image
x = 50;
nm = size(A2);
SE=strel('disk',10,0);
B = regionprops(AA, 'Centroid','PixelIdxList');
for i = 1:length(B);
if B(i).Centroid(1)<x || B(i).Centroid(2)<x || B(i).Centroid(1)>nm(1) - x || B(i).Centroid(2)>nm(2) - x
AA(B(i).PixelIdxList)=0;
imshow(AA)
end
end
AAfill = imfill(AA, 'holes'); %fill the holes in the image
%function extra_jw
%figure(4), imshow(AAfill);
SE=strel('disk',10,0);%use disk to dilate the image. the radius should be
%modified to a smaller value so that no extra stuff is included out of the
figure(4)
clf
AAfil=bwareaopen(AAfill,2); %delete the pixel clusters that have less than 2
%pixels in the image
%replace B6 with AAfil to use picture instead of differential
Bfil=imclose(AAfil,SE);%use the same disk size to get closed image
if sum(sum(Bfil))<2000
Bfil = imclose(AAfill,SE);
end
% deletes objects with centroid within distance x from border
x = 50;
nm = size(A2);
%for i = 1:10 % erode and dilate to smoothen (for whole cell only)
Bfil = imerode(Bfil,SE);
B = regionprops(Bfil, 'Centroid','PixelIdxList');
for i = 1:length(B);
if B(i).Centroid(1)<x || B(i).Centroid(2)<x || B(i).Centroid(1)>nm(1) - x || B(i).Centroid(2)>nm(2) - x
Bfil(B(i).PixelIdxList)=0;
imshow(Bfil)
end
end
Bfil = imdilate(Bfil,SE);
%end
figure(5)
imshow(Bfil)
AAfil=uint8(Bfil);
Afin=times(AAfil,A2);%extract from original image
%Afin = AAfil*255;
figure(6)
imshow(Afin)
end