Toward content-based indexing and retrieval of brain images

In this paper, we explore the concept of a "library of brain images", which implies not only a repository of brain images, but also efficient search and retrieval mechanisms that are based on models derived from IR practice. As a preliminary study, we have worked with a collection of functional MRI brain images assembled in the study of several distinct cognitive tasks. We adapt several classical IR methods (inverted indexing, TFIDF and Latent Semantic Indexing(LSI)) to content-based brain image retrieval. Our results show that efficient and accurate retrieval of brain images is possible, and that representations motivated by the IR perspective are somewhat more effective than are methods based on retaining the full image information.