Assessing tissues’ inhomogeneous optical properties is helpful for diagnosis, but high-cost measurement and experimental setups limit its development, data collecting and applications. In this paper, a portable microscope is proposed to assess the inhomogeneous optical properties of the sample. With a LED illumination, accurate quantitative phase (QP) map can be recovered from 5 intensity images captured at different axial positions. Then based on the scattering-phase theorem and statistical dispersion relation (SDR), the inhomogeneous optical properties of the sample can be quantitatively assessed from these QP maps. In contrast to DHM and SLIM, our setup is cost-effective, use-flexible, and with a small amount of data acquisition, thus having the potential to promote the development of assessing tissues’ inhomogeneous optical properties, especially in resource-limited areas.
Assessing tissues’ inhomogeneous optical properties is helpful for label-free diagnosis. In this paper, a method and a setup are proposed to assess the tissues’ inhomogeneous optical properties based on quantitative phase imaging (QPI) and dark-field microscopy using LED illumination. In the bright-field and coherent dark-field imaging, quantitative phase (QP) can be recovered from multi-frame intensity images captured at different axial positions by Transport-intensity-equation (TIE) and multi-height Gerchberg-Saxton(G-S) phase retrieval algorithms. In the incoherent dark-field imaging, some scattering samples can be observed easily without any computation and the resolution can be improved in contrast to bright-field illumination. According to the scattering-phase theorem and the statistical dispersion relation (SDR), tissues’ inhomogeneous optical properties can be assessed. In our experiments, we find, it is a good idea to combine QP maps and dark-field images to assess inhomogeneous optical properties of bio-samples. In contrast to the DHM and interferometers, our setup is cost-effective and use-flexible, thus having the potential to serve as a very powerful tool in biological applications.
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