Journal of Biomedical OpticsEffective contrast recovery in rapid dynamic near-infrared diffuse optical tomography using ℓ1-norm-based linear image reconstruction method
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Traditional image reconstruction methods in rapid dynamic diffuse optical tomography employ ℓ2-norm-based regularization, which is known to remove the high-frequency components in the reconstructed images and make them appear smooth. The contrast recovery in these type of methods is typically dependent on the iterative nature of method employed, where the nonlinear iterative technique is known to perform better in comparison to linear techniques (noniterative) with a caveat that nonlinear techniques are computationally complex. Assuming that there is a linear dependency of solution between successive frames resulted in a linear inverse problem. This new framework with the combination of ℓ1-norm-based regularization can provide better robustness to noise and provide better contrast recovery compared to conventional ℓ2-based techniques. Moreover, it is shown that the proposed ℓ1-based technique is computationally efficient compared to its counterpart (ℓ2-based one). The proposed framework requires a reasonably close estimate of the actual solution for the initial frame, and any suboptimal estimate leads to erroneous reconstruction results for the subsequent frames.