Trying to display the segmentation result in the same type as of the original image.

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Warid Islam 2022-11-2

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评论： Warid Islam 2022-11-4

I have applied basic segmentation on my image. 's1.png' is the original image and 's2.png' is the segmented image. I want the segmented image to be of the same type(color) as the original image. However, I am unable to do it. Any suggestions would be appreciated.

m=imread('s1.png');
se = strel('disk',10);
closeBW = imclose(m,se);
figure, imshow(closeBW)
level = multithresh(closeBW);
seg_I = imquantize(closeBW,level);
figure, imshow(seg_I,[])
img_class1=class(m);
fill1=cast(seg_I,img_class1);
m1=fill1.*m;
figure,imshow(fill1,[])

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DGM 2022-11-2

在 MATLAB Online 中打开

s1.png

it's not clear how you're trying to apply seg_I to m, but the math itself probably isn't working like you expect. Seg_I is an image of class 'double', containing only values 1 or 2 (quantized). Image m is class 'uint8'. Mixed-class multiplication between the two won't work, but if you cast seg_I as 'uint8' you can perform the multiplication. The problem is that the multiplication will cause data truncation, since it's performed in uint8.

You could do the multiplication in floating point instead, but you're still going to end up with an image that's improperly-scaled for its class. It won't display correctly, and it won't save correctly if you try to write it to disk.

Since I don't know the purpose of applying the quantized mask like this or if there may be masks with more than 2 levels, I'm just going to throw out this wild guess.

m=imread('s1.png');

se = strel('disk',10);

closeBW = imclose(m,se);

%figure, imshow(closeBW)

level = multithresh(closeBW);

seg_I = imquantize(closeBW,level);

%figure, imshow(seg_I,[])

img_class1 = class(m);

fill1=cast(seg_I,img_class1);

m1=fill1.*m;

% perform multiplication in floating-point

% normalize quantized mask regardless of number of levels

fill1 = im2uint8(im2double(m).*mat2gray(seg_I));

imshow(fill1)

I doubt that's what you want, but maybe it's enough to help guide the troubleshooting forward a bit.

Warid Islam 2022-11-2

I have one more query. Is it possible to do further mprphological operation on the above image to perform further segmentation?

DGM 2022-11-3

Since I don't really understand the use of multithresh() and imquantize() in this method, I don't know if that's appropriate or not. You certainly could do morphological operations on any image; I just don't know if it's appropriate in this context.

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回答（1 个）

DGM 2022-11-2

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编辑：DGM 2022-11-2

在 MATLAB Online 中打开

I think you might be asking how to programmatically cast and scale an image to a specific class from any class. If that's the case, then this is how you'd do it within the scope of base MATLAB/IPT:

% say we want to cast/scale image FG to have the same class as image BG
outclass = class(BG);
switch outclass
    case 'uint8'
        FG = im2uint8(FG);
    case 'double'
        FG = im2double(FG);
    case 'single'
        FG = im2single(FG);
    case 'uint16'
        FG = im2uint16(FG);
    case 'int16'
        FG = im2int16(FG);	
    case 'logical'
        FG = logical(FG); % this is a great way to create problems
    otherwise
        error('some error message goes here')
end

... because the primary parameter (the class name) is embedded in the function names. It's almost like you're being tempted to use eval() or something.

You could also use cast(), which does support the class name as a parameter, but then you'll have to take care to correctly scale the data for each possible combination, because cast() doesn't scale anything.

... or you can just use MIMT imcast():

FG = imcast(FG,class(BG));

That said, you might presume that your input image is uint8 and just use im2uint8(). That's certainly fallible,but it's simple and might cover your needs.

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Image Analyst 2022-11-3

Sorry we can't help you. We don't know what the original image looks like so we don't know what you want to find in it. Somehow you found a squiggly shape but apparently it's not good for some unknown (to us) reason. And we don't even know what would be the perfect, ideal segmentation since you're not showing us that, so we don't know how to alter your existing, bad segmentation to give you the ideal, perfect, optimal segmentation. Good luck though.

Warid Islam 2022-11-4

Hi @Image Analyst,

The original slice of image looks like 'original.png'. The '8004.3.png' is the segmented region annotated by the radiologists. The next slice of image is 'IMG-0012-00219.png' which is the image I want to segment next. I tried to segment the 'IMG-0012-00219.png' using the region growing algorithm but it didn't work. The next thing I tried was further segmenting the already segmented '8004.3.png'. I am assuming that segmenting this region would give the segmenting result of the next slice('IMG-0012-00219.png') of the original image.

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