Abstract

We apply different polarization imaging techniques for cancerous liver tissues, and compare the relative contrasts for difference polarization imaging (DPI), degree of polarization imaging (DOPI) and rotating linear polarization imaging (RLPI). Experimental results show that a number of polarization imaging parameters are capable of differentiating cancerous cells in isotropic liver tissues. To analyze the contrast mechanism of the cancer-sensitive polarization imaging parameters, we propose a scattering model containing two types of spherical scatterers and carry on Monte Carlo simulations based on this bi-component model. Both the experimental and Monte Carlo simulated results show that the RLPI technique can provide a good imaging contrast of cancerous tissues. The bi-component scattering model provides a useful tool to analyze the contrast mechanism of polarization imaging of cancerous tissues.

Highlights

  • The rate of cancer incidence is currently increasing year by year, and has become a major threat to human health

  • The healthy and cancerous tissues can be distinguished by measuring the variations of polarization parameters, which re°ect the interactions between polarized photons and microstructures.6Ă€8 most biological tissues are highly turbid in the visible and near-infrared regions

  • We have developed a rotating linear polarization imaging technique (RLPI)

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Summary

Introduction

The rate of cancer incidence is currently increasing year by year, and has become a major threat to human health. For both the diagnosis and treatment of cancer, the detection of early-stage cancerous tissues is very essential.[1] Optical techniques have been widely used in biomedical applications for their characteristics of nondestructive, noncontact and. This is an Open Access article published by World Scientic Publishing Company. Since more than 85% of early-stage cancerous changes originate in epidermal tissues, polarization optical methods are of promising prospects for early detection of cancers.[10,11]

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