Abstract
The role that deconvolution plays in the achievable spatial resolution in optical diffusion tomography is examined for the case of imaging an inhomogeneity in an otherwise homogeneous medium. It is shown that, in the measured data, it is the shape of the turbid medium modulation transfer function that determines the maximum spatial resolution. When the turbid medium transfer function is deconvolved from the measured data, it is the signal-to-noise ratio properties of the Fourier-transformed measured data that determine the maximum spatial resolution. It is shown that deconvolution-based methods can improve the spatial resolution in measured data up to a factor of 5 for realistic noise levels. These results are demonstrated with computer-simulated data.
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