Analysis of polarization features of human breast cancer tissue by Mueller matrix visualization

Abstract

Significance: Breast cancer ranks second in the world in terms of the number of women diagnosed. Effective methods for its early-stage detection are critical for facilitating timely intervention and lowering the mortality rate.

Aim: Polarimetry provides much useful information on the structural properties of breast cancer tissue samples and is a valuable diagnostic tool. The present study classifies human breast tissue samples as healthy or cancerous utilizing a surface-illuminated backscatter polarization imaging technique.

Approach: The viability of the proposed approach is demonstrated using 95 breast tissue samples, including 35 healthy samples, 20 benign cancer samples, 20 grade-2 malignant samples, and 20 grade-3 malignant samples.

Results: The observation results reveal that element $m_{23}$ in the Mueller matrix of the healthy samples has a deeper color and greater intensity than that in the breast cancer samples. Conversely, element $m_{32}$ shows a lighter color and reduced intensity. Finally, element $m_{44}$ has a darker color in the healthy samples than in the cancer samples. The analysis of variance test results and frequency distribution histograms confirm that elements $m_{23}$, $m_{32}$, and $m_{44}$ provide an effective means of detecting and classifying human breast tissue samples.

Conclusions: Overall, the results indicate that surface-illuminated backscatter polarization imaging has significant potential as an assistive tool for breast cancer diagnosis and classification.

Keywords: Mueller matrix transformation; backscattering polarization imaging; depolarization power; human breast cancer.