Title :
Fuzzy classification of metabolic brain diseases utilizing MR Spectroscopy signals
Author :
Mahmoodabadi, Sina Zarei ; Alirezaie, Javad ; Babyn, Paul
Author_Institution :
Dept. of Electr. & Comput. Eng., Ryerson Univ., Toronto, ON
Abstract :
A suspected metabolic brain disorder presents a difficult challenge to the physician and the patient. We have developed a fully automated system in order to classify the Magnetic Resonance Spectroscopy (MRS) signals. Novel fuzzy rules and a fuzzy classifier have been designed in this study to categorize metabolic brain diseases in children. The sensitivity and positive predictivity of 75% plusmn 43 in detecting five metabolic brain diseases have been achieved.
Keywords :
brain; diseases; fuzzy set theory; magnetic resonance spectroscopy; medical signal processing; paediatrics; signal classification; MR spectroscopy signal classification; fuzzy classification; metabolic brain disease; Diseases; Fuzzy sets; Hospitals; Humans; Java; Magnetic resonance; Magnetic resonance imaging; Medical diagnosis; Pediatrics; Spectroscopy;
Conference_Titel :
Fuzzy Information Processing Society, 2008. NAFIPS 2008. Annual Meeting of the North American
Conference_Location :
New York City, NY
Print_ISBN :
978-1-4244-2351-4
Electronic_ISBN :
978-1-4244-2352-1
DOI :
10.1109/NAFIPS.2008.4531247
