Fluorescence optical diffusion tomography (FODT) uses diffusely scattered light to image deep into tissue. This new biomedical imaging modality has tremendous potential in the early diagnosis of cancer and the development of new pharmaceuticals because:
1) it offers the chemical and molecular specificity of spectroscopy;
2) it can also be coupled to fluorescent molecular imaging agents to target specific cancers or biological processes of interest;
3) it is minimally invasive since it only requires exposure to light;
4) it has the potential to be low cost since it does not require coherent optical sources and demodulation.
However, a critical barrier to this technology is the creation of algorithms which can reconstruct images from light that has been diffusely scattered by seemingly opaque tissue. This research creates the foundation for FODT technology by developing the algorithms that can accurately reconstruct FODT images from this diffusely scattered light.
The algorithms are based on Bayesian inverse methods and multigrid optimization of the resulting cost functionals. Critical goals of the research are to reconstruct accurate fluorescence yield volume renderings, to directly estimate pharmaco-kinetic parameters, to form reconstructions which use modulation and wavelength diversity to improve specificity, and to develop novel polarization-sensitive imaging methods.
2. A level of effort statement:
The PIs will make every attempt to meet to the original scope and level of effort of the project.
