Bimodal tissue differentiation using hyperspectral imaging and elastographic Fourier transform profilometry

Multispectral imaging is a common method to enhance tissue differentiation based on different cell or tissue structures.These differences arise from the unique structural properties of each tissue type, which result in characteristic differences in spectral absorption.In the context of distinguishing between healthy and malignant tissues, differences are observed not only in spectral absorption but also in their elastic properties.To improve the reliability of measurement devices, we present a novel bimodal measurement system that includes a hyperspectral and an elastographic Fourier transform profilometry system to combine the individual results and to improve the overall task of tissue differentiation.The results of both subsystems show good ability to differentiate between healthy and malignant tissue.However, some limitations were identified for each individual sensor concept, such as contamination with pathological dye in hyperspectral imaging and insufficient sample thickness in elastographic measurements.Nevertheless, the multimodal combination of the individual sensor systems ensures good tissue differentiation.While the elastographic sensor can differentiate tissue even when contaminated with pathological staining agents, hyperspectral imaging can be used on very thin tissue samples and also enables the detection of tumor boundaries.