Title :
Multivariate classification of fMRI images
Author :
Karahan, Esin ; Öztürk, Cengizhan
Author_Institution :
Biyomed. Muhendislik Enstitusu, Bogazici Univ., Istanbul, Turkey
Abstract :
Functional Magnetic Resonance Imaging (fMRI) gives vast amount of information on the neural activity of the brain. Researchers analyse fMRI data to investigate the functions and structure of the brain. Using machine learning tools that have been widely used in recent years in fMRI area, has enabled to predict the cognitive states of subject which is called ldquobrain readingrdquo also. In this study, fMRI data is taken from Ishai et. al. who explored the representation of object categories in brain. By using Naive Gauss classifier and support vector machines, it is tried to identify the patterns of objects and by analyzing fMRG images prediction on the cognitive state of the subject is performed.
Keywords :
biomedical MRI; brain; cognition; image classification; learning (artificial intelligence); medical image processing; neurophysiology; pattern recognition; support vector machines; Naive Gauss classifier; brain neural activity; cognitive state; fMRG image prediction; fMRI image; functional magnetic resonance imaging; machine learning tool; multivariate classification; pattern prediction; support vector machine; Data analysis; Gaussian processes; Image analysis; Machine learning; Magnetic analysis; Magnetic resonance imaging; Pattern analysis; Performance analysis; Support vector machine classification; Support vector machines;
Conference_Titel :
Biomedical Engineering Meeting, 2009. BIYOMUT 2009. 14th National
Conference_Location :
Balcova, Izmir
Print_ISBN :
978-1-4244-3605-7
Electronic_ISBN :
978-1-4244-3606-4
DOI :
10.1109/BIYOMUT.2009.5130368
