How can I improve my segmented image?

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Ghazal Hnr
Ghazal Hnr 2018-5-7
评论： Ghazal Hnr 2018-5-8
Hi, I wrote the code below in order to segment blood vessels of the retina. But the result is not really good. Even I tried another way that I put it here to but it didn't make it better too. Can anyone give me a suggestion about how can I improve it? My images are from STARE database (<http://cecas.clemson.edu/~ahoover/stare/>) here is the example of my image:
FIRST WAY:
clc; clear all; close all;
%%Specifying path folders
%%%ex.d_img2 - F:\folder1\folder2\...\foldern\*.format %%%
%%%ex.di_img2 - F:\folder1\folder2\...\foldern\ %%%
d_img2 = 'F:\Uni\Project\MATLAB\myMatlab\prepImages\*.ppm';
di_img2 = 'F:\Uni\Project\MATLAB\myMatlab\prepImages\';
%%Reading images
srcFiles_prepImage = dir(d_img2);
N_img_prep = length(srcFiles_prepImage);
% i = 1; %%50
% i = 2; %%150
i = 3; %%200
filename2 = strcat(di_img2, srcFiles_prepImage(i).name);
prepImage = imread(filename2);
prepImage = prepImage(:,:,2); %?% the picture had been saved in rgb format?
figure
imshow(prepImage, 'InitialMagnification', 'fit')
%%Histogram
[row,column] = size(prepImage);
figure
imhist(prepImage);
%%Creating & Applying binary mask in order to making the background (outside of eye) black
%Using threshold
threshold_value = 100;
mask = prepImage > threshold_value; % Bright objects will be chosen.
mask = imfill(mask, 'holes'); % Do a "hole fill" to get rid of any background pixels or "holes".
%%%%check if there is any black part inside the white part
figure
imshow(mask, 'InitialMagnification', 'fit')
% Applying binary mask to image
maskedImage = bsxfun(@times, prepImage, cast(mask,class(prepImage)));
figure
imshow(maskedImage, 'InitialMagnification', 'fit')
figure
subplot(1,3,1)
imhist(maskedImage)
%%Thresholding histogram
[pixelCount,grayLevels] = imhist(maskedImage,256);
peaks = findpeaks(pixelCount);
peaks = transpose(peaks);
maxBin = max(peaks);
maxBinLocation = find(pixelCount == maxBin);
maxI = find(peaks == maxBin);
% Find low threshold
TlowLocation = min(find(pixelCount == 0)); % Find first zero
% Place vertical bar on histogram to show Tlow
subplot(1,3,3)
imhist(maskedImage)
hold on
y2 = ylim();
line([TlowLocation, TlowLocation], [y2(1), y2(2)], ...
'Color', 'r', 'LineWidth', 2);
% Find high threshold
minBinL = min(peaks); %%Find the minimum on left side of peak
minBinLocationL = find(pixelCount == minBinL);
%%%%
% if minBinLocation>maxBinLocation
%%%%need an IF to make sure that it is on left side
%%%%
% Find the minimum on left side of peak
minIL = find(peaks == minBinL);
leftBins = peaks(minIL:maxI);
leftMean = mean(leftBins);
subLeft = maxBin - leftMean;
% Find the closest value to subLeft
[subLeftClosest,indexLeftClosest] = min(abs(leftBins - subLeft));
ThighBin = leftBins(indexLeftClosest);
ThighLocation = find(pixelCount == ThighBin);
% Place vertical bar on histogram to show Thigh
subplot(1,3,2)
imhist(maskedImage)
hold on
yl = ylim();
line([ThighLocation, ThighLocation], [yl(1), yl(2)], ...
'Color', 'r', 'LineWidth', 2);
% Place vertical bars on histogram to show Tlow&Thigh
figure
imhist(maskedImage)
hold on
yl = ylim();
line([TlowLocation, TlowLocation], [yl(1), yl(2)], ...
'Color', 'r', 'LineWidth', 2);
hold on
y2 = ylim();
line([ThighLocation, ThighLocation], [y2(1), y2(2)], ...
'Color', 'r', 'LineWidth', 2);
% Find pixels between the thresholds
betweenThresholds = maskedImage<ThighLocation & maskedImage>TlowLocation;
Vs = betweenThresholds;
Ts = length(Vs);
figure
imshow(betweenThresholds, 'InitialMagnification', 'fit');
SECOND WAY:
clc; clear all; close all;
%%Specifying path folders
%%%ex.d_img2 - F:\folder1\folder2\...\foldern\*.format %%%
%%%ex.di_img2 - F:\folder1\folder2\...\foldern\ %%%
d_img2 = 'F:\Uni\Project\MATLAB\myMatlab\prepImages\*.ppm';
di_img2 = 'F:\Uni\Project\MATLAB\myMatlab\prepImages\';
%%Reading images
srcFiles_prepImage = dir(d_img2);
N_img_prep = length(srcFiles_prepImage);
% i = 1; %%50
% i = 2; %%150
i = 3; %%200
filename2 = strcat(di_img2, srcFiles_prepImage(i).name);
prepImage = imread(filename2);
IG = uint8(prepImage*255);
prepImage = prepImage(:,:,2); %?% the picture had been saved in rgb format?
figure
imshow(prepImage, 'InitialMagnification', 'fit')
%%Histogram
[row,column] = size(prepImage);
figure
imhist(prepImage,256);
%%Thresholding histogram
[pixelCounts,grayLevels] = imhist(prepImage,256);
cdf = cumsum(pixelCounts); % Sum histogram counts to get cumulative distribution function
cdf = cdf / cdf(end); % Normalize
% Get data value where ?%&?% is.
data30 = find(cdf>= 0.2, 1, 'first');
data70 = find(cdf>= 0.4, 1, 'first');
% Place vertical bars on histogram to show Tlow&Thigh
figure
imhist(prepImage)
hold on
y1 = ylim();
line([data30, data30], [y1(1), y1(2)], ...
'Color', 'r', 'LineWidth', 2);
hold on
y2 = ylim();
line([data70, data70], [y2(1), y2(2)], ...
'Color', 'r', 'LineWidth', 2);
% Find pixels between the thresholds
betweenThresholds = prepImage<data70 & prepImage>30;
Vs = betweenThresholds;
Ts = length(Vs);
figure
imshow(betweenThresholds, 'InitialMagnification', 'fit');
%%Creating & Applying binary mask in order to making the background (outside of eye) black
%Using threshold
threshold_value = 100;
mask = prepImage > threshold_value; % Bright objects will be chosen.
mask = imfill(mask, 'holes'); % Do a "hole fill" to get rid of any background pixels or "holes".
%%%%check if there is any black part inside the white part
figure
imshow(mask, 'InitialMagnification', 'fit')
% Applying binary mask to image
maskedImage = bsxfun(@times, betweenThresholds, cast(mask,class(betweenThresholds)));
figure
imshow(maskedImage, 'InitialMagnification', 'fit')

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采纳的回答

Image Analyst
Image Analyst 2018-5-8
Basically you're just doing a primitive global histogram. No matter how you decide on a global threshold, it won't get all the vessels, no matter which threshold you pick.
You'd be better off using one of the successful published algorithms here: http://www.visionbib.com/bibliography/contentsmedical.html#Medical%20Applications,%20CAT,%20MRI,%20Ultrasound,%20Heart%20Models,%20Brain%20Models

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