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Copy pathPreprocessing_before_creating_patches.m
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Preprocessing_before_creating_patches.m
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clc
clear all
%% pre-processing: enhance the colours for each class:
%training_folder = 'C:\Users\NeuroBeast\Desktop\images_high_resolution\Testing\ground truth\case1video4';
us_folder='C:\Users\NeuroBeast\Desktop\us + masks\case1video4\ground truth';
us_files = dir(fullfile(us_folder,'*.jpg'));
us_files = {us_files.name};
path = us_folder;
addpath(us_folder);
m_files = dir(fullfile(us_folder,'*.jpg'));
m_files = {m_files.name};
%% case1video4
%{
for iii = 1:length(m_files)
filename=m_files{iii};
ground_truth = imread(filename);
%us_folder ='C:\Users\NeuroBeast\Desktop\semantic case1video4';
%addpath(us_folder);
us_file = fullfile(us_folder,filename);
us = imread(us_file);
hsv_ground_truth = rgb2hsv(ground_truth);
[height,width,channel_size]= size(hsv_ground_truth);
%modified_ground_truth = zeros(height,width,channel_size);
% maximise v values to enhance the colours of all classes
for m = 1:height
for n = 1:width
hsv_ground_truth(m,n,2)=1;
end
end
%figure
%imshow(hsv_ground_truth)
% transform enhanced hsv images back to rgb
processed_img = hsv2rgb(hsv_ground_truth);
processed_img = processed_img*255;
%figure
%imshow(processed_img)
R_channel_processed = processed_img(:,:,1);r=mean2(R_channel_processed);r_std=std2(R_channel_processed);
G_channel_processed = processed_img(:,:,2);g=mean2(G_channel_processed);g_std=std2(G_channel_processed);
B_channel_processed = processed_img(:,:,2);b=mean2(B_channel_processed);b_std=std2(B_channel_processed);
for i = 1:height
for j = 1:width
%{
if ((us(i,j,1)<5 && us(i,j,2)<5 && us(i,j,3)<5))
processed_img(i,j,1)=0;
processed_img(i,j,2)=0;
processed_img(i,j,3)=0;
%}
% white matter
if (processed_img(i,j,1)< 120 &&processed_img(i,j,1)>50 && processed_img(i,j,2)<80 && processed_img(i,j,2)>40 && processed_img(i,j,3)<5)
processed_img(i,j,1)=0;
processed_img(i,j,2)=255;
processed_img(i,j,3)=0;
% matter
elseif (processed_img(i,j,1)<5 && processed_img(i,j,2)> 50 && processed_img(i,j,3)>50)
processed_img(i,j,1)=0;
processed_img(i,j,2)=255;
processed_img(i,j,3)=0;
% sulcus
elseif (processed_img(i,j,1)> 60 && processed_img(i,j,1)<80 &&processed_img(i,j,2)> 70 &&processed_img(i,j,2)< 90 &&processed_img(i,j,3)< 1)
processed_img(i,j,1)=0;
processed_img(i,j,2)=0;
processed_img(i,j,3)=255;
elseif (processed_img(i,j,1)> 70 && processed_img(i,j,2)> 70 &&processed_img(i,j,2)< 1)
processed_img(i,j,1)=0;
processed_img(i,j,2)=0;
processed_img(i,j,3)=255;
elseif (processed_img(i,j,1)> 80 && processed_img(i,j,2)> 80)
processed_img(i,j,1)=0;
processed_img(i,j,2)=0;
processed_img(i,j,3)=255;
% sulcus
elseif (processed_img(i,j,1)> 40 && processed_img(i,j,2)> 40 && processed_img(i,j,2)< 1)
processed_img(i,j,1)=0;
processed_img(i,j,2)=0;
processed_img(i,j,3)=255;
% tumour
elseif (processed_img(i,j,1)< 20 && processed_img(i,j,3)<22 && processed_img(i,j,2)>50)
processed_img(i,j,1)=255;
processed_img(i,j,2)=0;
processed_img(i,j,3)=0;
%{
elseif (processed_img(i,j,1)< 20 && processed_img(i,j,2) >70 && processed_img(i,j,2) <110 && processed_img(i,j,3)<10)
processed_img(i,j,1)=255;
processed_img(i,j,2)=0;
processed_img(i,j,3)=0;
% tumour
elseif (processed_img(i,j,1)< 10 && processed_img(i,j,2) >110 && processed_img(i,j,3)<15)
processed_img(i,j,1)=255;
processed_img(i,j,2)=0;
processed_img(i,j,3)=0;
%}
% artifacts
elseif (processed_img(i,j,1)> 50 && processed_img(i,j,2) < 5)
processed_img(i,j,1)=0;
processed_img(i,j,2)=0;
processed_img(i,j,3)=255;
elseif (processed_img(i,j,1)> 90 && processed_img(i,j,2) > 20 && processed_img(i,j,3)>80)
processed_img(i,j,1)=0;
processed_img(i,j,2)=0;
processed_img(i,j,3)=255;
% others
else
processed_img(i,j,1)=0;
processed_img(i,j,2)=0;
processed_img(i,j,3)=0;
end
end
end
[FILEPATH,name,EXT] =fileparts(filename);
labelfilename=strcat(name,'_after.png');
figure
imshow(processed_img)
fullname = fullfile(path,labelfilename);
imwrite(processed_img,fullname);
end
%}
%% case1video1
%{
for iii = 1:length(m_files)
filename=m_files{iii};
filename = fullfile(us_folder,filename);
img = imread(filename);
%us_folder ='C:\Users\NeuroBeast\Desktop\images_high_resolution\Testing\US';
%addpath(us_folder);
%case_index=filename(18:20);
%us_name=strcat('case1_video10',case_index,'.jpeg');
%us_file = fullfile(us_folder,us_name);
%us = imread(us_file);
img = rgb2hsv(img);
[height,width,channel_size]= size(img);
%labels_map = zeros(height,width);
% maximise v values to enhance the colours of all classes
for m = 1:height
for n = 1:width
img(m,n,2)=1;
end
end
% transform enhanced hsv images back to rgb
img = hsv2rgb(img);
figure
imshow(img)
R_channel_processed = img(:,:,1);r=mean2(R_channel_processed);r_std=std2(R_channel_processed);
G_channel_processed = img(:,:,2);g=mean2(G_channel_processed);g_std=std2(G_channel_processed);
B_channel_processed = img(:,:,2);b=mean2(B_channel_processed);b_std=std2(B_channel_processed);
for i = 1:height
for j = 1:width
%{
if ((processed_img(i,j,1)+processed_img(i,j,2)+processed_img(i,j,3))/3<=5)
processed_img(i,j,1)=0;
processed_img(i,j,2)=0;
processed_img(i,j,3)=0;
labels_map(i,j)=0;
else
%}
% tumour
if (img(i,j,1)< (r-0*r_std) && img(i,j,2) >(g-0*g_std) && img(i,j,3)<(b-0*b_std))
img(i,j,1)=255;
img(i,j,2)=0;
img(i,j,3)=0;
%labels_map(i,j)=0;
% healthy
elseif (img(i,j,1)< (r-0*r_std) && img(i,j,2) >(g-0*g_std) && img(i,j,3)>(b-0*b_std))
img(i,j,1)=0;
img(i,j,2)=255;
img(i,j,3)=0;
%labels_map(i,j)=2;
% sulcus
elseif (img(i,j,1)> (r+0*r_std) && img(i,j,2)> (g+0*g_std) && img(i,j,3)<(b+0*b_std))
img(i,j,1)=0;
img(i,j,2)=0;
img(i,j,3)=255;
%labels_map(i,j)=3;
% background
elseif(img(i,j,1)< (r-0*r_std) && img(i,j,2) <(g-0*g_std) && img(i,j,3)<(b-0*b_std))
img(i,j,1)=0;
img(i,j,2)=0;
img(i,j,3)=0;
%labels_map(i,j)=1;
% others
else
img(i,j,1)=0;
img(i,j,2)=0;
img(i,j,3)=255;
%labels_map(i,j)=3;
end
end
end
[FILEPATH,name,EXT] =fileparts(m_files{iii});
labelfilename=strcat(name,'.png');
%fulllabelname=fullfile(path,labelfilename);
%imwrite(labels_map,fulllabelname);
%save(fulllabelname,'labels_map');
figure
imshow(img)
fullname = fullfile(path,labelfilename);
%fullname=fullfile('C:\Users\NeuroBeast\Desktop',m_files{iii});
imwrite(img,fullname);
end
%}
%% case 2
for iii = 1:length(m_files)
filename=m_files{iii};
ground_truth = imread(filename);
%us_folder ='C:\Users\NeuroBeast\Desktop\semantic case1video4';
%addpath(us_folder);
us_file = fullfile(us_folder,filename);
us = imread(us_file);
hsv_ground_truth = rgb2hsv(ground_truth);
[height,width,channel_size]= size(hsv_ground_truth);
%modified_ground_truth = zeros(height,width,channel_size);
% maximise v values to enhance the colours of all classes
for m = 1:height
for n = 1:width
hsv_ground_truth(m,n,2)=1;
end
end
%figure
%imshow(hsv_ground_truth)
% transform enhanced hsv images back to rgb
processed_img = hsv2rgb(hsv_ground_truth);
[FILEPATH,name,EXT] =fileparts(filename);
labelfilename=strcat('enhanced',name,'.png');
figure
imshow(processed_img)
fullname = fullfile(path,labelfilename);
imwrite(processed_img,fullname);
%processed_img = processed_img*255;
%figure
%imshow(processed_img)
%{
R_channel_processed = processed_img(:,:,1);r=mean2(R_channel_processed);r_std=std2(R_channel_processed);
G_channel_processed = processed_img(:,:,2);g=mean2(G_channel_processed);g_std=std2(G_channel_processed);
B_channel_processed = processed_img(:,:,2);b=mean2(B_channel_processed);b_std=std2(B_channel_processed);
%}
%{
for i = 1:height
for j = 1:width
%{
if ((us(i,j,1)<5 && us(i,j,2)<5 && us(i,j,3)<5))
processed_img(i,j,1)=0;
processed_img(i,j,2)=0;
processed_img(i,j,3)=0;
%}
% red
%
if (processed_img(i,j,1)> 70 && processed_img(i,j,2)< 40 && processed_img(i,j,2)< 6)
processed_img(i,j,1)=0;
processed_img(i,j,2)=0;
processed_img(i,j,3)=255;
%
% necrosis
elseif (processed_img(i,j,1)>= 100 && processed_img(i,j,1)<= 150 && processed_img(i,j,2)>= 80 && processed_img(i,j,2)<= 100 && processed_img(i,j,3)<= 10)
processed_img(i,j,1)=255;
processed_img(i,j,2)=0;
processed_img(i,j,3)=0;
elseif (processed_img(i,j,1)>= 60 && processed_img(i,j,2)>= 40 && processed_img(i,j,2)<= 80 && processed_img(i,j,3)<= 15)
processed_img(i,j,1)=255;
processed_img(i,j,2)=0;
processed_img(i,j,3)=0;
%
% sulcus
elseif (processed_img(i,j,1)> 80 && processed_img(i,j,2)> 80 && processed_img(i,j,2)> 10)
processed_img(i,j,1)=255;
processed_img(i,j,2)=255;
processed_img(i,j,3)=0;
%{
elseif (processed_img(i,j,1)> 120 && processed_img(i,j,2)> 120 && processed_img(i,j,2)> 20)
processed_img(i,j,1)=0;
processed_img(i,j,2)=0;
processed_img(i,j,3)=255;
%}
% odemma
elseif (processed_img(i,j,1)<20 && processed_img(i,j,2)< 20 && processed_img(i,j,3)> 60)
processed_img(i,j,1)=0;
processed_img(i,j,2)=0;
processed_img(i,j,3)=255;
%{
% white matter
elseif (processed_img(i,j,1)< 120 &&processed_img(i,j,1)>50 && processed_img(i,j,2)<80 && processed_img(i,j,2)>40 && processed_img(i,j,3)<5)
processed_img(i,j,1)=0;
processed_img(i,j,2)=255;
processed_img(i,j,3)=0;
%}
% grey matter
elseif (processed_img(i,j,1)<5 && processed_img(i,j,2)> 50 && processed_img(i,j,3)>50)
processed_img(i,j,1)=0;
processed_img(i,j,2)=255;
processed_img(i,j,3)=0;
% tumour
elseif (processed_img(i,j,1)< 20 && processed_img(i,j,3)<22 && processed_img(i,j,2)>50)
processed_img(i,j,1)=255;
processed_img(i,j,2)=0;
processed_img(i,j,3)=0;
%{
elseif (processed_img(i,j,1)< 20 && processed_img(i,j,2) >70 && processed_img(i,j,2) <110 && processed_img(i,j,3)<10)
processed_img(i,j,1)=255;
processed_img(i,j,2)=0;
processed_img(i,j,3)=0;
% tumour
elseif (processed_img(i,j,1)< 10 && processed_img(i,j,2) >110 && processed_img(i,j,3)<15)
processed_img(i,j,1)=255;
processed_img(i,j,2)=0;
processed_img(i,j,3)=0;
%}
% artifacts
elseif (processed_img(i,j,1)> 50 && processed_img(i,j,2) < 5)
processed_img(i,j,1)=255;
processed_img(i,j,2)=0;
processed_img(i,j,3)=255;
elseif (processed_img(i,j,1)> 90 && processed_img(i,j,2) > 20 && processed_img(i,j,3)>80)
processed_img(i,j,1)=255;
processed_img(i,j,2)=0;
processed_img(i,j,3)=255;
% others
else
processed_img(i,j,1)=0;
processed_img(i,j,2)=0;
processed_img(i,j,3)=0;
end
end
end
[FILEPATH,name,EXT] =fileparts(filename);
labelfilename=strcat('multi-classes',name,'.png');
figure
imshow(processed_img)
fullname = fullfile(path,labelfilename);
%imwrite(processed_img,fullname);
%}
end
%
%% case 3
%{
for iii = 1:length(m_files)
filename=m_files{iii};
ground_truth = imread(filename);
%us_folder ='C:\Users\NeuroBeast\Desktop\semantic case1video4';
%addpath(us_folder);
us_file = fullfile(us_folder,filename);
us = imread(us_file);
hsv_ground_truth = rgb2hsv(ground_truth);
[height,width,channel_size]= size(hsv_ground_truth);
%modified_ground_truth = zeros(height,width,channel_size);
% maximise v values to enhance the colours of all classes
for m = 1:height
for n = 1:width
hsv_ground_truth(m,n,2)=1;
end
end
%figure
%imshow(hsv_ground_truth)
% transform enhanced hsv images back to rgb
processed_img = hsv2rgb(hsv_ground_truth);
processed_img = processed_img*255;
%figure
%imshow(processed_img)
%{
[FILEPATH,name,EXT] =fileparts(filename);
labelfilename=strcat(name,'after.png');
figure
imshow(processed_img)
fullname = fullfile(path,labelfilename);
imwrite(processed_img,fullname)
%}
for i = 1:height
for j = 1:width
%{
if ((us(i,j,1)<5 && us(i,j,2)<5 && us(i,j,3)<5))
processed_img(i,j,1)=0;
processed_img(i,j,2)=0;
processed_img(i,j,3)=0;
%}
% sulcus
if (processed_img(i,j,1)> 40 && processed_img(i,j,2)> 40)
processed_img(i,j,1)=0;
processed_img(i,j,2)=0;
processed_img(i,j,3)=255;
% white matter
elseif (processed_img(i,j,1)< 100 && processed_img(i,j,1)>50 && processed_img(i,j,2)<80 && processed_img(i,j,2)>40 && processed_img(i,j,3)<5)
processed_img(i,j,1)=0;
processed_img(i,j,2)=255;
processed_img(i,j,3)=0;
% matter
elseif (processed_img(i,j,1)<10 && processed_img(i,j,2)> 50 && processed_img(i,j,3)>50)
processed_img(i,j,1)=0;
processed_img(i,j,2)=255;
processed_img(i,j,3)=0;
% tumour
elseif (processed_img(i,j,1)< 20 && processed_img(i,j,3)<22 && processed_img(i,j,2)>50)
processed_img(i,j,1)=255;
processed_img(i,j,2)=0;
processed_img(i,j,3)=0;
%{
elseif (processed_img(i,j,1)< 20 && processed_img(i,j,2) >70 && processed_img(i,j,2) <110 && processed_img(i,j,3)<10)
processed_img(i,j,1)=255;
processed_img(i,j,2)=0;
processed_img(i,j,3)=0;
% tumour
elseif (processed_img(i,j,1)< 10 && processed_img(i,j,2) >110 && processed_img(i,j,3)<15)
processed_img(i,j,1)=255;
processed_img(i,j,2)=0;
processed_img(i,j,3)=0;
%}
%{
%artifacts
elseif (processed_img(i,j,1)> 50 && processed_img(i,j,2) < 5)
processed_img(i,j,1)=0;
processed_img(i,j,2)=0;
processed_img(i,j,3)=255;
elseif (processed_img(i,j,1)> 90 && processed_img(i,j,2) > 20 && processed_img(i,j,3)>80)
processed_img(i,j,1)=0;
processed_img(i,j,2)=0;
processed_img(i,j,3)=255;
%}
% others
else
processed_img(i,j,1)=0;
processed_img(i,j,2)=0;
processed_img(i,j,3)=255;
end
end
end
[FILEPATH,name,EXT] =fileparts(filename);
labelfilename=strcat(name,'.png');
figure
imshow(processed_img)
fullname = fullfile(path,labelfilename);
% imwrite(processed_img,fullname);
end
%}