Digital-Pathology---Image-Processing-and-Analysis/registration_performance_PAS_IF.m at main · Leema-Krishna-Murali/Digital-Pathology---Image-Processing-and-Analysis · GitHub

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for i = 1:size(registrated1,1)
    for j = 1:size(registrated1,2)
    if registrated1(i,j, 1) == 0 && registrated1(i,j, 2) == 0 && registrated1(i,j, 3) == 00
      % Change from white to our gray level
      registrated1 (i,j,1) = 240;
      registrated1 (i,j,2) = 240;
      registrated1 (i,j,3) = 240;
    end
    end
end
figure();imshow(registrated1);
registrated1_gray = rgb2gray(registrated1);
figure();imshow(registrated1_gray);
fixed_2_gray = rgb2gray(fixed_rotate);
figure();imshow(fixed_2_gray);
%%%%%%%%%%%
M = zeros(256,1,'uint8'); % Store mapping - Cast to uint8 to respect data type
hist1 = imhist(registrated1_gray);        % Compute histograms
hist2 = imhist(fixed_2_gray);
cdf1 = cumsum(hist1) / numel(registrated1_gray);  %Compute CDFs
cdf2 = cumsum(hist2) / numel(fixed_2_gray);
% Compute the mapping
for idx = 1 : 256
    [~,ind] = min(abs(cdf1(idx) - cdf2));
    M(idx) = ind-1;
end
%Now apply the mapping to get first image to make
%the image look like the distribution of the second image
out = M(double(registrated1_gray)+1);

%%%%%%%%%%%%
b = histeq(registrated1_gray,imhist(fixed_2_gray));


[r1,c1] = size(b);
registrated1_1 = zeros(r1,c1);
registrated1_1 = uint8(registrated1_1*0);
for i = 1:size(b,1)
    for j = 1:size(b,2)
    if b(i,j, 1) >= 150
      % Change from white to our gray level
      registrated1_1 (i,j) = 0;
      registrated1_1 (i,j) = 0;
      registrated1_1 (i,j) = 0;
    else
      registrated1_1 (i,j) = 255;
      registrated1_1 (i,j) = 255;
      registrated1_1 (i,j) = 255;
    end
    end
end
%registrated1_1 = imfill(registrated1_1,'holes');
%mask of registrated image
BW2 = bwareaopen(registrated1_1, 120);
figure();imshow(BW2);
figure();imshow(registrated1_1);

%mask of hist(reference) image
[r2,c2] = size(fixed_2_gray);
mask_hist = zeros(r2,c2);
mask_hist = uint8(mask_hist*0);

for i = 1:size(fixed_2_gray,1)
    for j = 1:size(fixed_2_gray,2)
    if fixed_2_gray(i,j) >= 170
      % Change from white to our gray level
      mask_hist (i,j) = 0;
      mask_hist (i,j) = 0;
      mask_hist (i,j) = 0;
    else
      mask_hist (i,j) = 255;
      mask_hist (i,j) = 255;
      mask_hist (i,j) = 255;
    end
    end
end
%mask_hist = imfill(mask_hist,'holes');
BW_hist = bwareaopen(mask_hist, 2000);
figure();imshow(BW_hist);
figure();imshow(mask_hist);
BW_hist(8369:23100,65:5219) = 0;

%overlapped pixels(TP)
%BW2_X = ~(BW2);
TP = BW_hist.*BW2;
figure();imshow(TP);
TP_idx=TP==1;
TP_idx=sum(TP_idx(:))

%non-overlapping pixels - region of PAS image(FN)
FN = BW_hist - TP;
figure();imshow(FN);
FN_idx=FN==1;
FN_idx=sum(FN_idx(:))

%non-overlapping pixels - region of IF image(FP)
FP = BW2 - BW_hist;
figure();imshow(FP);
FP_idx=FP==1;
FP_idx=sum(FP_idx(:))

%common background - TN
TN = BW_hist + BW2;
figure();imshow(TN);
TN_idx=TN==0;
TN_idx_1=sum(TN_idx(:))

Sensitivity = TP_idx/(TP_idx+FN_idx)
Specificity = TN_idx_1/(FP_idx+TN_idx_1)
PPV = TP_idx/(TP_idx+FP_idx)
NPV = TN_idx_1/(TN_idx_1+FN_idx)

% for i = 1:size(registrated1,1)
%     for j = 1:size(registrated1,2)
%     if registrated1(i,j, 1) <= 60 && registrated1(i,j, 2) <= 60 && registrated1(i,j, 3) <= 60
%       % Change from white to our gray level
%       registrated1 (i,j, 1) = 240;
%       registrated1 (i,j, 2) = 240;
%       registrated1 (i,j, 3) = 240;
%     end
%     end
% end
% figure();imshow(registrated1);