IR principles for content-based indexing and retrieval of functional brain images

Authors:
Bing Bai;Paul Kantor;Nicu Cornea;Deborah Silver
Affiliations:
Rutgers University, New Brunswick, NJ;Rutgers University, New Brunswick, NJ;Rutgers University, Piscataway, New Jersey;Rutgers University, Piscataway, New Jersey
Venue:
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Year:
2006

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Abstract

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.