Pham TTH, Ngoc Quach TN, Vo QHQ. Analysis of polarization features of human breast cancer tissue by Mueller matrix visualization.
J Biomed Opt 2024;
29:052917. [PMID:
38223746 PMCID:
PMC10787228 DOI:
10.1117/1.jbo.29.5.052917]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 12/03/2023] [Accepted: 12/20/2023] [Indexed: 01/16/2024]
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.
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