SOS! PLEASE SAVE MY CODE:

Question

Chanille 2023-3-9

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1925900-sos-please-save-my-code

编辑： Chanille 2023-3-14

In my code I have the following issues: 1. the count measurement is not accurately outputting the count of blobs in the zones of the image. 2. When I normalize the count the count becomes decimal values, how can I fix this? 3. I want to make sure that the code is not measuring any of the large black areas in the image. Can someone please help me fix this, thanks!

1 个评论
显示 -1更早的评论隐藏 -1更早的评论

Walter Roberson 2023-3-9

We are not going to read through hundreds of lines code mentally modeling everything that could possibly go wrong. We need some of your images, and you have to describe the difference between what you get and what you want for each one.

请先登录，再进行评论。

请先登录，再回答此问题。

Answer 1

Kevin Holly 2023-3-9

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1925900-sos-please-save-my-code#answer_1189670

在 MATLAB Online 中打开

C1_L1_WDa.jpg

Instead of trying to figure out how you calculated the areas. I used the following approach to find the masks:

fig = figure;
fontSize = 12;
% directoryInfo = dir('*.tif');
allFileNames = {'C1_L1_WDa.jpg'};
numfiles = length(allFileNames);
% Define the pixel size in square microns
pixelSize = 1;
numZones = 12;
for m = 1:numfiles
    fprintf('Processing file #%d of %d : "%s".\n', m, numfiles, allFileNames{m});
    MyRGBImage = fullfile(pwd, allFileNames{m});
    % Read in image.
    imageData = imread(MyRGBImage);
    [rows, columns, numberOfColorChannels] = size(imageData);
    if numberOfColorChannels > 1
        grayImage = rgb2gray(imageData); % Convert to color.
    end
    % Apply background subtraction.
    grayImage = imtophat(grayImage, strel('disk', 100));
    %the lower this number the less lipid droplets
    % Apply contrast correction.
    grayImage = imadjust(grayImage);
    % Apply Gaussian filtering.
    grayImage = imgaussfilt(grayImage, 3);
    % Apply thresholding.
    thresholdValue = graythresh(grayImage);
    binaryImage = imbinarize(grayImage, thresholdValue);
    % Remove black elongated shapes.
    binaryImage = bwareaopen(binaryImage, 200);
    binaryImage = imclearborder(binaryImage);
    binaryImage = imfill(binaryImage, 'holes');
    % mask
    % Threshold the image to create a binary mask
    gray_img = rgb2gray(imageData); % Convert to color.
    threshold = 5;
    mask = gray_img > threshold;
    % Remove small objects
    min_size = 1000;
    mask = bwareaopen(mask, min_size);
    % Fill holes
    mask = imfill(mask, 'holes');
    % Erode and dilate the mask to remove noise and smooth edges
    se = strel('disk', 5);
    mask = imerode(mask, se);
    mask = imdilate(mask, se);
    
    close; 
    figure;
    % ZZ: Right now for each single image, a separate window (figure) 
    % will be created to plot the related info, and the former figure will
    % be closed.
    subplot(3, 4, 4);
    imshow(mask);
    title('Functional Mask, thres = 5');
    % Display the organelle segmented image.
    subplot(3, 4, 2);
    imshow(binaryImage, []);
    axis on;
    title('Organelle Segmented Image', 'FontSize', fontSize);
    % Display the original image.
    subplot(3, 4, 1);
    imshow(imageData, []);
    axis on;
    title('Original Image', 'FontSize', fontSize);
    % Set up figure properties:
    set(gcf, 'Units', 'Normalized', 'OuterPosition', [0, 0.04, 1, 0.96]);
    sgtitle(sprintf('Analysis of Organelles in Image "%s"', allFileNames{m}), 'FontSize', 28);
% %     % Locate the center
% %     promptMessage = sprintf('Click at the center of the periportal region');
% %     titleBarCaption = 'Continue?';
% %     buttonText = questdlg(promptMessage, titleBarCaption, 'OK', 'Quit', 'OK');
% %     if strcmpi(buttonText, 'Quit')
% %         return;
% %     end
% %     [x,y] = ginput(1);
    x = 4592.86363636364;
    y = 705.954545454545;
    
    % Find out what the max distance will be by computing the distance to each corner.
    distanceToUL = sqrt((1-y)^2 + (1-x)^2);
    distanceToUR = sqrt((1-y)^2 + (columns-x)^2);
    distanceToLL = sqrt((rows-y)^2 + (1-x)^2);
    distanceToLR= sqrt((rows-y)^2 + (columns-x)^2);
    maxDistance = ceil(max([distanceToUL, distanceToUR, distanceToLL, distanceToLR]));
    
    % Calculate the radius of each zone
    radius = linspace(0, maxDistance, numZones+1);
    
    subplot(3, 4, 3);
    imshow(mask, []);
    axis on;
    title('Bin drawing', 'FontSize', fontSize);
    hold on;
    line([x, x], [1, rows], 'Color', 'r', 'LineWidth', 2);
    line([1, columns], [y, y], 'Color', 'r', 'LineWidth', 2);

I added this section below

% Preallocate

zonemask = zeros(size(mask,1),size(mask,2),numZones+1);

fig2 = figure;

imshow(mask)

figure(fig2)

c(1) = drawcircle("Center",[x, y],"Radius",radius(1),"LineWidth",1,"Color","b","Visible","off");

% Draw the circles for each zone

for ii = 2:numZones+1

figure(fig2)

c(ii) = drawcircle("Center",[x, y],"Radius",radius(ii),"LineWidth",1,"Color","b","Visible","off");

zonemask(:,:,ii) = createMask(c(ii))-createMask(c(ii-1));

viscircles([x, y], radius(ii), 'LineStyle', '--', 'LineWidth', 1);

total_intensity(ii) = sum(sum(gray_img.*uint8(mask).*uint8(zonemask(:,:,ii)))); % or replace binaryImage with mask

total_zone_pixels(ii) = sum(sum(uint8(mask).*uint8(zonemask(:,:,ii))));

end

mean_intensity_zone = total_intensity./total_zone_pixels

end

Processing file #1 of 1 : "C1_L1_WDa.jpg".

mean_intensity_zone = 1×13

NaN 20.2110 18.5171 18.3373 16.1967 20.3758 21.0019 24.8756 23.1034 23.8200 22.3985 23.9102 16.3538

Verify Zones

figure

tiledlayout(5,3)

nexttile

imshow(zonemask(:,:,1))

nexttile

imshow(double(mask).*zonemask(:,:,1))

nexttile

imshow(gray_img.*uint8(mask).*uint8(zonemask(:,:,1)))

for ii = 2:5

nexttile

imshow(zonemask(:,:,ii))

nexttile

imshow(double(mask).*zonemask(:,:,ii))

nexttile

imshow(gray_img.*uint8(mask).*uint8(zonemask(:,:,ii)))

end

Below I made a colored version with the original image.

figure

mask2(:,:,1) = uint8(mask).*uint8(zonemask(:,:,ii));

mask2(:,:,2) = mask2(:,:,1);

mask2(:,:,3) = mask2(:,:,1);

imshow(imageData.*mask2)

10 个评论
显示 8更早的评论隐藏 8更早的评论

Chanille 2023-3-12

编辑：Walter Roberson 2023-3-12

在 MATLAB Online 中打开

@Image Analyst

What do you mean by XY problem sorry? Also here is how i am calculating the blobs. Is this correct? @Kevin Holly

 numObjects = length(stats);
        if numObjects > 0
            areas = [stats.Area];
            profileCounts(k) = length(stats)%-sum(index,"all");%# of objects should be numObjects but not 1
            totalArea(k) = nansum(areas)*pixelSize^2; %mc:this is supposed to be the total area of each zone
            avgSize(k) = nanmean(areas)*pixelSize^2;
            zoneArea(k) = areaOfEachZone(k); %mc:this is supposed to be the total area of each blob in the zone being measured
            circularities = [stats.Circularity];%circularities(index) = nan;
            avgCircularity(k) = nanmean(circularities);
            ferets = [stats.MajorAxisLength];% ferets(index)=nan;
            avgFeret(k) = nanmean(ferets)*pixelSize;
            minFerets = [stats.MinorAxisLength];% minFerets(index)=nan;
            avgMinFeret(k) = nanmean(minFerets)*pixelSize;
        end

Walter Roberson 2023-3-12

@Chanille

An "XY Problem" is when a person asks to do something (X) because they think it will help them reach their goals, but their goals turn out to be something else (Y) that turns out not to need to use X after-all.

Suppose for example you were asking how to get epoxy to stick to anodized aluminum, but it turned out that your real question was about how to fasten down the piece of anodized aluminum. You would (in this example) have decided that you needed to "epoxy" to solve your problem, but "epoxy" turned out to be a distraction, and if you had stated from the beginning what you needed to fasten to what, then perhaps someone could have suggested bolts or welding or crazy glue.

Chanille 2023-3-13

@Walter Roberson

Thanks. My question was answered!

请先登录，再进行评论。

SOS! PLEASE SAVE MY CODE:

1 个评论
显示 -1更早的评论隐藏 -1更早的评论

采纳的回答

10 个评论
显示 8更早的评论隐藏 8更早的评论

更多回答（0 个）

另请参阅

类别

标签

Community Treasure Hunt

SOS! PLEASE SAVE MY CODE:

1 个评论 显示 -1更早的评论隐藏 -1更早的评论

采纳的回答

10 个评论 显示 8更早的评论隐藏 8更早的评论

更多回答（0 个）

另请参阅

类别

标签

Community Treasure Hunt

1 个评论
显示 -1更早的评论隐藏 -1更早的评论

10 个评论
显示 8更早的评论隐藏 8更早的评论