Abstract

Diffuse optical fluorescence tomography often relies on the assumption that samples are homogeneous. This degrades the correspondence between tomography data sets and model predictions. We provide evidence that data normalization significantly improve on this situation. Article not available.

© 2008 Optical Society of America