6 June 2000 Optimal linear filter for fMRI analysis
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Abstract
This paper presents development and application of an optimal linear filter for delineation of activated areas of the brain from functional MRI (fMRI) time series data. The steps of the work accomplished are as follows. (1) Delineation of activated areas is formulated as an optimal linear filtering problem. In this formulation, a linear filter (image combination method) is looked for, which maximizes the signal-to-noise ratio (SNR) of the activated areas subject to the constraint of removing inactivated areas from the image. (2) An analytical solution for the problem is found. (3) Image pixel vectors and expected time series pattern (signature) for inactivated pixels are used to calculate the weighting vectors numerically. (4) The segmented image by the proposed method is compared to those generated by the conventional methods (correlation, t- statistic, and z-statistic). Visual qualities of the images as well as their SNR's are compared. The optimal linear filter outperforms the conventional methods of fMRI analysis based on improved SNR and contrast-to-noise ratio (CNR) of the images generated by the proposed method compared to those generated by the other methods. In addition, this method does not require a priori knowledge of the fMRI response to the paradigm for its application. The method is linear and most of the work is done analytically, thereby numerical implementation and execution of the method are faster than the conventional methods.
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Hamid Soltanian-Zadeh, Hamid Soltanian-Zadeh, Donald J. Peck, Donald J. Peck, David O. Hearshen, David O. Hearshen, Renee R. Lajiness-O'Neill, Renee R. Lajiness-O'Neill, } "Optimal linear filter for fMRI analysis", Proc. SPIE 3979, Medical Imaging 2000: Image Processing, (6 June 2000); doi: 10.1117/12.387741; https://doi.org/10.1117/12.387741
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