Automatic mapping magnetic resonance images into multimedia database using SIFT

Abstract

This paper focuses on the representation of magnetic resonances of different parts of the human body, such as knees, spinal column, arms, elbows, etc., using ontologies. First, it maps the resonance im ages in a multimedia database. Then, automatically, using the SIFT pattern recognition algorithm, descriptors of the images stored in the database ar e extracted in order to recover useful data for the user; it use s the ontologies as an artificial intelligence tool and, in consequen ce, reduces generation of useless data. Why do we think this is an interesting task? Because, if the user requires information abo ut any topics or (s)he has some illness or needs to undergo magnet ic resonance, this tool will show him /her images and text to conve y a better understanding, helping t o obtain useful conclusions. Artificial intelligence techniques are used, such as machine learning, knowledge representat ion, and pattern recognition. The ontological relations introduced here are based on the common representation of language , using definition dictionarie s, Roget’s thesaurus, synonym dictionaries, and other resources The system generates an output in the OM ontological language [1]. This language represents a structure where our system adds the data scanned by the SIFT algorithm. The tests have been made in Spanish; however, thanks to the portability of our system, it is possible to extend the method to any language.