Image Segmentation and Classification
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I have recently been tasked to a project which primarily deals with image segmentation. I am supposed to read in an MR brain image and apply k-means clustering on the image with k = 5. Obtain segmented regions through pixel classification using the clustered classes. Compare the segmented regions with those obtained from the optimal gray value thresholding method.
I know k-means clustering is not too difficult but I'm not sure how to "Obtain segmented regions through pixel classification using the clustered classes" and I would like to seek some professional advice from the community to point me in the right direction on what I should be looking at or doing.
Feel free to drop me any comments. Any help rendered is deeply appreciated.
Best Regards Westin Messer
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Image Analyst
2018-3-13
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See my attached kmeans demo for a gray scale image. Adapt as needed.
By the way, kmeans is a dumb (bad) method for tumor detection. I assume it's just for an illustrative student exercise rather than a real world situation.
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Westin Messer
2018-3-13
Westin Messer
2018-3-13
Image Analyst
2018-3-14
So did it work for you? Like I said, it is not robust so it won't detect every tumor from 0% to 100% in size. Plus any pixels with that gray level will get selected, regardless if they are actually tumor pixels or not, that just happen to have the same gray levels by chance.
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