Measurement and model error assessment of a single-pixel frequency-domain photon migration apparatus and diffusion model for imaging applications

Research into the near-infrared biomedical optical imaging has produced a multitude of inverse imaging algorithms. Recent experience has shown that when these algorithms are tested with experimental data, they falter due to a mismatch between observed and simulated measurements. When considering measurements for imaging, one must consider both measurement and model error. If data is recorded properly, then measurement error tends to be normally distributed with a mean of zero. Model error can be biased and spatially correlated due to inaccuracies in the diffusion approximation, inaccurate parameter estimates, numerical error, and other factors. This contribution discusses trends in the measurement and model error observed from measurements on a single-pixel, frequency domain photon migration system developed for biomedical optical imaging. In order to reduce the model error bias, an empirical approach was applied to find experimental variables that significantly affect it. This approach reduced the mean of the model error on a test data set and produced a slight smoothing effect on its distribution. Image reconstruction attempts show that the modified data set produces an improved image over the image reconstructed from the raw data set. To our knowledge, this is the first time that model and measurement error information have been incorporated into a three dimensional image reconstruction algorithm.