Abstract
High density diffuse optical tomography has become increasingly important to detect underlying neuronal activities. Conventional methods first estimate the time courses of the changes in the absorption coefficients for all the voxels, and then estimate the hemodynamic response function (HRF). Activation-level maps are extracted at last based on this HRF. However, the error propagation among the successive processes degrades and even misleads the final results. Besides, the computation burden is heavy. To address the above problems, a direct method is proposed in this paper to simultaneously estimate the HRF and the activation-level maps from the boundary fluxes. It is assumed that all the voxels in the same activated brain region share the same HRF but differ in the activation levels, and no prior information is imposed on the specific shape of the HRF. The dynamic simulation and phantom experiments demonstrate that the proposed method outperforms the conventional one in terms of the estimation accuracy and computation speed.
Highlights
Optical neuroimaging techniques have shown promise to understand the brain function because of the advantages including good temporal resolution, portability, quietness and low sensitivity to motion artifacts [1,2]. They have evolved into high density diffuse optical tomography (HD-DOT) from the initial functional near-infrared spectroscopy
This optimal stimulation is used in the smooth finite impulse response (SFIR) and joint direct estimation (JDE) to estimate the hemodynamic response function (HRF), which is compared with the optimal HRF
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Summary
Optical neuroimaging techniques have shown promise to understand the brain function because of the advantages including good temporal resolution, portability, quietness and low sensitivity to motion artifacts [1,2]. The finite impulse response model has been proposed within the GLM framework [17] It contains one free parameter for every time point following the stimulation onsets. When the signal to noise ratio (SNR) is low, the accurate estimation is difficult To overcome these shortcomings, a joint direct estimation (JDE) method is proposed to simultaneously estimate the HRF and the activation-level maps from the boundary fluxes. Based on the low-rank constraint and the assumption that all the voxels in the same activated region share the same HRF, it avoids solving the μa changes for every time point. It imposes no constraint on the specific shape of the HRF. The a priori smooth information is utilized to improve the estimated HRF
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