MATLAB: Can any one help me with ideas

cancerimage analysisimage processingImage Processing Toolboxlung cancer

I need some ideas for finding Cancerous nodules in side lungs i extract the lungs correctly then segmenting lungs using morphology , but now i need usefull way to find "Cancerous nodules in side lungs" i am working on CT-scan image

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We don't partner with you to develop complicated algorithms like that. If you find an algorithm here, then we can help with syntax, error messages, etc. if you post your code. The link I gave you will give you some ideas , which answers your question of where to get some ideas.

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MATLAB: Removing some connected component

Hi Selim,

if your input is a label image, you can use the following syntax:

   img(img == ind) = 0;

This will detect which pixels are labeled with label IND, and set them to 0, which is the usual label for background. You can convert binary image to label image by using the bwlabel function.

If you want to remove the region around the point (40, 50):

ind = img(50, 40); % beware of index ordering
img(img == ind) = 0;

If you want to remove labels touching right border:

inds = unique(img(:, end));
inds(inds==0) = 0;
img(ismember(img, inds)) = 0;

Not that the bwconncomp function may be useful too. The output structure is different, and may be more efficient in some cases.

Regards

MATLAB: How to extract objects from an image after i have measured properties through regionprops

See my image segmentation tutorial - it goes over all of that. http://www.mathworks.com/matlabcentral/fileexchange/25157-image-segmentation-tutorial

Here's the relevant snippet. Change the filter parameters to be eccentricity and aspect ratio and you're all set.

% Now I'll demonstrate how to select certain blobs based using the ismember() function.
% Let's say that we wanted to find only those blobs
% with an intensity between 150 and 220 and an area less than 2000 pixels.
% This would give us the three brightest dimes (the smaller coin type).
allBlobIntensities = [blobMeasurements.MeanIntensity];
allBlobAreas = [blobMeasurements.Area];
% Get a list of the blobs that meet our criteria and we need to keep.
% These will be logical indices - lists of true or false depending on whether the feature meets the criteria or not.
% for example [1, 0, 0, 1, 1, 0, 1, .....].  Elements 1, 4, 5, 7, ... are true, others are false.
allowableIntensityIndexes = (allBlobIntensities > 150) & (allBlobIntensities < 220);
allowableAreaIndexes = allBlobAreas < 2000; % Take the small objects.
% Now let's get actual indexes, rather than logical indexes, of the  features that meet the criteria.
% for example [1, 4, 5, 7, .....] to continue using the example from above.
keeperIndexes = find(allowableIntensityIndexes & allowableAreaIndexes);
% Extract only those blobs that meet our criteria, and
% eliminate those blobs that don't meet our criteria.
% Note how we use ismember() to do this.  Result will be an image - the same as labeledImage but with only the blobs listed in keeperIndexes in it.
keeperBlobsImage = ismember(labeledImage, keeperIndexes);
% Re-label with only the keeper blobs kept.
labeledDimeImage = bwlabel(keeperBlobsImage, 8);     % Label each blob so we can make measurements of it
% Now we're done.  We have a labeled image of blobs that meet our specified criteria.

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Related Solutions

MATLAB: Removing some connected component

MATLAB: How to extract objects from an image after i have measured properties through regionprops

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