Content-Based Medical Image Retrieval Using Low-Level Visual Features and Modality Identification

Juan C. Caicedo, Fabio A. González, Eduardo Romero

Abstract: This paper presents the image retrieval results obtained by the BioIngenium Research Group, in the frame of the ImageCLEFmed 2007 edition. The applied approach consists of two main phases: a pre-processing phase, which builds an image category index and a retrieval phase, which ranks similar images. Both phases are based only on visual information. The experiments show a consistent frame with theory in content-based image retrieval: filtering images with a conceptual index outperforms only-ranking-based strategies; combining features is better than using individual features; and low-level features are not enough to model image semantics.