Paper Info
Title
Convolution model for automated localization of brain activity in fMRI images
Abstract
In this article, we present an efficient technique for automated detection of neural activity from time-varying three-dimensional fMRI images. We develop a hemodynamic response model based on the impulse response function and the stimuli onset pattern that results in a linear combination of incomplete gamma functions. In order to improve the detection, we employ a spatial filtering approach based on a convolution model that improves the signal-to-noise ratio by suitably adapting to the local activity patterns. Then we develop a correlation model of the convolution signals and propose a method to detect the active regions based on the maximum correlation values. It eventually results in a nonlinear optimization problem with correlation maximization as the objective and bounds on impulse response parameters as the constraints. We propose an efficient method for the solution. We then implemented and tested it on real set of images. Experimental results show the effectiveness of our method for localization of brain activity in fMRI images
Year
DOI
Venue
2006
10.1109/ISBI.2006.1625070
Arlington, VA
Keywords
Field
DocType
biomedical MRI,brain,convolution,haemodynamics,medical image processing,neurophysiology,optimisation,spatial filters,automated brain activity localization,automated neural activity detection,convolution model,correlation maximization,hemodynamic response model,impulse response function,incomplete gamma functions,maximum correlation values,nonlinear optimization problem,signal-to-noise ratio,spatial filtering,stimuli onset pattern,time-varying three-dimensional fMRI images
Computer vision,Impulse response,Linear combination,Pattern recognition,Convolution,Computer science,Signal-to-noise ratio,Filter (signal processing),Artificial intelligence,Adaptive filter,Image resolution,Maximization
Conference
ISSN
ISBN
Citations 
1945-7928
0-7803-9576-X
0
PageRank 
References 
Authors
0.34
4
2
Name
Order
Citations
PageRank
Tapan K Nayak1213.93
Ravi Kothari200.34