To find generalised threshold value of an image
1 vue (au cours des 30 derniers jours)
Afficher commentaires plus anciens
rohith bharadwaj
le 26 Jan 2018
Commenté : Image Analyst
le 26 Jan 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 commentaires
Rik
le 26 Jan 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.
Réponse acceptée
Image Analyst
le 26 Jan 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 commentaire
Image Analyst
le 26 Jan 2018
Go here for tumor finding algorithms: http://www.visionbib.com/bibliography/contentsmedical.html#Medical%20Applications,%20CAT,%20MRI,%20Ultrasound,%20Heart%20Models,%20Brain%20Models
Plus de réponses (0)
Voir également
Produits
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!