Title :
Detection of Neural Activities in FMRI Using Jensen-Shannon Divergence
Author_Institution :
IBM India Res. Lab., New Delhi
Abstract :
In this paper, we present a statistical technique based on Jensen-Shanon divergence for detecting the regions of activity in fMRI images. The method is model free and we exploit the metric property of the square root of Jensen-Shannon divergence to accumulate the variations between successive time frames of fMRI images. Experimentally we show the effectiveness of our algorithm.
Keywords :
biomedical MRI; medical image processing; Jensen-Shannon divergence; fMRI images; neural activities; Head; Image sequences; Independent component analysis; Pattern recognition; Probability distribution; Q measurement; Random variables; Robustness; Signal processing algorithms; Spatial resolution;
Conference_Titel :
Advances in Pattern Recognition, 2009. ICAPR '09. Seventh International Conference on
Conference_Location :
Kolkata
Print_ISBN :
978-1-4244-3335-3
DOI :
10.1109/ICAPR.2009.61
