Recent advances in electronics and optics have opened new possibilities for terahertz (THz) waves—an invisible type of light that falls between infrared light and microwaves on the spectrum. The use of THz scattering for medical diagnosis is a promising frontier in this field, as THz waves can probe tissue structures in ways that traditional imaging methods cannot. Emerging THz measurement methods have the potential to detect subtle changes in tissue architecture that occur in diseases like cancer and burn injuries, serving as a powerful diagnostic tool.
However, existing THz imaging techniques face significant limitations for medical applications. Most existing approaches rely primarily on water content differences between healthy and diseased tissue as their main source of diagnostic contrast—an approach that proves overly simplistic for complex disease conditions.
Moreover, while polarization measurements of reflected THz waves seem to be valuable for tissue diagnosis, the underlying mechanisms that create different polarization responses in tissues remain poorly understood. This gap in understanding underscores a need for computational models capable of explaining and predicting the phenomena that researchers have observed experimentally.
