DocumentCode :
2491828
Title :
MRI cases containing cerebral tumors retrieval using Bayesian networks
Author :
Yazid, Hedi ; Kalti, Karim ; Elouni, Fatma ; Ben Amara Essoukri, Najoua ; Tlili, Kalthoum
Author_Institution :
Eng. Nat. Sch., Sousse, Tunisia
fYear :
2010
fDate :
15-18 Dec. 2010
Firstpage :
7
Lastpage :
12
Abstract :
We propose in this paper a Bayesian model for the retrieving of MRI (magnetic resonance imaging) exams that contain cerebral tumors. Bayesian network proved its efficiency and reliability in several AI (Artificial Intelligence) problems and especially in aid-decision applications. To diagnose a cerebral tumor in a MRI exam, we need to interpret diverse sequences and to refer to visual descriptors and, also, to the patient´s clinical information´s (age, sex, other diseases ...etc.). Our main idea is argued by the probabilistic aspect chosen in the decision making of diagnosis process. This aspect will be translated as a probabilistic decision model. Our work is tested in a several medical cases that were collected from Sahloul Hospital. Performance indices of experiments are promising.
Keywords :
artificial intelligence; belief networks; biomedical MRI; decision making; medical diagnostic computing; patient diagnosis; tumours; Bayesian model; Bayesian networks; MRI; aid-decision applications; artificial intelligence; cerebral tumor retrieval; clinical informations; decision making; diverse sequence; magnetic resonance imaging; probabilistic decision model; visual descriptors; Bayesian methods; Biomedical imaging; Computational modeling; Data preprocessing; Metastasis; Semantics; Visualization; Bayesian network; Cerebral tumors; Euclidian Distance; Indexing; MR Imaging; Retrieval; Similarity Measurement; component;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing and Information Technology (ISSPIT), 2010 IEEE International Symposium on
Conference_Location :
Luxor
Print_ISBN :
978-1-4244-9992-2
Type :
conf
DOI :
10.1109/ISSPIT.2010.5711742
Filename :
5711742
Link To Document :
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