TY - JOUR
T1 - Automatic Mapping Magnetic Resonance Images into Multimedia Database Using SIFT
AU - Reynoso, J. L.
AU - Cuevas, A. D.
AU - García, F.
AU - Guzmán, A.
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/8
Y1 - 2015/8
N2 - 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 images in a multimedia database. Then, automatically, using the SIFT pattern recognition algorithm, descriptors of the images stored in the database are extracted in order to recover useful data for the user; it uses the ontologies as an artificial intelligence tool and, in consequence, reduces generation of useless data. Why do we think this is an interesting task? Because, if the user requires information about any topics or (s)he has some illness or needs to undergo magnetic resonance, this tool will show him/her images and text to convey a better understanding, helping to obtain useful conclusions. Artificial intelligence techniques are used, such as machine learning, knowledge representation, and pattern recognition. The ontological relations introduced here are based on the common representation of language, using definition dictionaries, 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.
AB - 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 images in a multimedia database. Then, automatically, using the SIFT pattern recognition algorithm, descriptors of the images stored in the database are extracted in order to recover useful data for the user; it uses the ontologies as an artificial intelligence tool and, in consequence, reduces generation of useless data. Why do we think this is an interesting task? Because, if the user requires information about any topics or (s)he has some illness or needs to undergo magnetic resonance, this tool will show him/her images and text to convey a better understanding, helping to obtain useful conclusions. Artificial intelligence techniques are used, such as machine learning, knowledge representation, and pattern recognition. The ontological relations introduced here are based on the common representation of language, using definition dictionaries, 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.
KW - Artificial Intelligence
KW - Magnetic Resonance
KW - Multimedia Database
KW - Ontology
KW - Pattern Recognition
UR - http://www.scopus.com/inward/record.url?scp=84959476228&partnerID=8YFLogxK
U2 - 10.1109/TLA.2015.7332153
DO - 10.1109/TLA.2015.7332153
M3 - Artículo
AN - SCOPUS:84959476228
SN - 1548-0992
VL - 13
SP - 2709
EP - 2714
JO - IEEE Latin America Transactions
JF - IEEE Latin America Transactions
IS - 8
M1 - 7332153
ER -