To find generalised threshold value of an image
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rohith bharadwaj
el 26 de En. de 2018
Comentada: Image Analyst
el 26 de En. de 2018
I extracted the tumour from the original image by using the following code. I found the threshold value by trial and error method. How to find the generalised threshold value?
I=imread('tum.tif');
a=imadjust(I);
a=imadjust(I,[0.3; 0.7],[0.3; 0.7]);
b=im2bw(a);
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/169470/image.jpeg)
3 comentarios
Rik
el 26 de En. de 2018
That depends on how general you want your code to work. There might not be answer that works for all tumors, but density based segmentation might work for all your images. I'm sure you'll be able to find some examples if you type that into your favorite internet search engine.
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Image Analyst
el 26 de En. de 2018
I also don't know what a "generalised" threshold is. I disagree that kmeans is a good method. While it may work good for images where you know for a fact that there is definitely a good sized tumor there, it will not work in general for small tumors, and you don't want to miss those. A fixed threshold, perhaps based on some reference if your overall intensity is not stable, would detect tumors of any size.
1 comentario
Image Analyst
el 26 de En. de 2018
Go here for tumor finding algorithms: http://www.visionbib.com/bibliography/contentsmedical.html#Medical%20Applications,%20CAT,%20MRI,%20Ultrasound,%20Heart%20Models,%20Brain%20Models
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