In our group, we have developed comprehensive spectral imaging approaches like Spatial Frequency Domain Spectroscopy (SFDS) that can provide fine spectral detail of both absorption and scattering from in vivo tissue. Data from these systems are critical for the characterization of medical application specific tissue constituents as well as other sources of normal biological variance that may confound or corrupt the interpretation of optical data. These approaches have also led towards the development of practical models and methods for extracting depth specific information in tissue non-invasively. However, SFDS is often better suited in controlled environments and dedicated clinical studies rather than general clinical practice due to its size, cost and bulkiness.
SFDS can characterize tissue spectral properties to within 1nm precision, but do we need all that detail? Under this project, we have developed analysis methods for data reduction and virtual instrument design to translate the critical spectral information content extracted from SFDS investigations down to the minimal necessary measurement details. From this data-driven perspective, we can then search for optimized imaging solutions and instrument designs that would maintain the data integrity and robustness of SFDS, but deliver this tool in a smaller, easy to use, and cost effective formfactor.
Objective: low-cost, handheld devices present a pragmatic approach toward seamless integration in to clinical practice, reducing translational barriers novel technologies and methods.