Question

I’m looking for local and global descriptors for medical image processing. I know about SIFT/SURF/GLOH/HOG, that are mainly applied to computer vision problems, but I would like to know if they are also applied to medical images to describe features or if there are specific descriptors in this field.

I would really appreciate any hint.

Thanks in advance,

Federico

Answer 1

I assumed you need the descriptors for matching.

I’d personally submitted a poster submission and got it accepted for using SIFT as part of the feature detection and matching framework that my work was intended to do.

The feature detection methods you mentioned are good for general images and will work as a good general initial input for your framework, too. Now, since every anatomical region and every modality lives in its own feature domain(ie. brain regions done by MR, live regions done by CT, they all probably imply distinctive landmarks); its best that you first identify what it is unique in your or near your target anatomical region and then see if the aforementioned algorithms would locate your distinctive features(distinctive enough that it has to be in your region and no where else), then find ways to differentiate from the bag of features(that get detected along with your distinctive features). And the result sets would be the key features/descriptors that you would like to keep.

So, Yes, many feature detection algorithms have been extensively used for various areas in medical imaging.