Content Based Medical image retrieval can assist physicians in binding information supporting their diagnosis. Systems that allow to search for medical images need to provide tool for quick and easy navigation as the time for information search is very easy to find the images. Relevance feedback is a powerful tool for information retrieval. Content-based image retrieval with relevance feedback schemes based on Method Fuzzy Logic Gaussian Mixture model didn’t require much time when compared to GMM. Also FLGMM gives efficient clustering. It gives best result for overlapped data sets. It is used to retrieve the medical image effectively and efficiently. Results show the potential of relevance feedback techniques in medical image retrieval and the superiority of the proposed algorithm over commonly used approaches. This technique users to retrieve a similar query images from a database.