I am wondering if there are some better machine learning methods for medical imaging segmentation?
Currently, I have some relatively low-resolution MRI images and I tried to use histogram and k-means algorithm, which is an old method to do a general clustering based segmentation. However, pixel may help estimate more than one cluster in the k-means procedure.
Is there any novel direction for clustering pixel values in order to do the segmentation?
I think this can be done by two ways:
Change the clustering similarity measurements but still use k-means, e.g., change histogram based clustering into something like using mutual information, but it might be well done by other people (if you know any, please give me the reference).
Change k-means to other clustering methods but keep the similarity measurements, i.e., histogram.
Any ideas would be appreciated. Thanks a lot.