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The study classifies human breast tissue as healthy or cancerous using surface-illuminated backscatter polarization imaging and evaluates feasibility with 95 samples. Variance and histogram analyses identify Mueller matrix elements m23, m32, and m44 as effective discriminators.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & 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is the main objective of this study?","Question",{"text":63,"@type":64},"To classify human breast tissue samples as healthy or cancerous by analyzing polarization features using Mueller matrix visualization with a surface-illuminated backscatter polarization imaging technique.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"Which Mueller matrix elements are most informative for discrimination?",{"text":68,"@type":64},"Elements m23, m32, and m44 show distinct intensity and color characteristics between healthy and cancer samples, and statistical tests confirm their effectiveness.",{"name":70,"@type":61,"acceptedAnswer":71},"How many breast tissue samples were used to validate the approach?",{"text":72,"@type":64},"The proposed approach was evaluated using 95 tissue samples: 35 healthy, 20 benign cancer, 20 grade-2 malignant, and 20 grade-3 malignant 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features of human breast cancer tissue by Mueller matrix visualization  \nThi-Thu-Hien Pham  ,a,b,* Thao-Ngan Ngoc Quach,a,b and  \nQuoc-Hoang-Quyen Voa,b  \naInternational University, School of Biomedical Engineering, Ho Chi Minh City, Vietnam  \nbVietnam National University HCMC, Ho Chi Minh City, Vietnam  \n\n| 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.\u003Cbr>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 surfaceilluminated backscatter polarization imaging technique.\u003Cbr>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.\u003Cbr>Results: The observation results reveal that element m23 in the Mueller matrix of the healthy samples has a deeper color and greater intensity than that in the breast cancer samples. Conversely, element m32 shows a lighter color and reduced intensity. Finally, element m44 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 m23 , m32 , and m44 provide an effective means of detecting and classifying human breast tissue samples.\u003Cbr>Conclusions: Overall, the results indicate that surface-illuminated backscatter polarization imaging has significant potential as an assistive tool for breast cancer diagnosis and classification.\u003Cbr>© The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI. [DOI: 10.1117/1.JBO.29.5.052917]\u003Cbr>Keywords: human breast cancer; backscattering polarization imaging; depolarization power; Mueller matrix transformation\u003Cbr>Paper 230264GR received Sep. 7, 2023; revised Dec. 3, 2023; accepted Dec. 20, 2023; published Jan.\u003Cbr>13, 2024 . |\n| --- |\n| 1 Introduction\u003Cbr>With an estimated 2.26 million new cases of breast cancer globally and around 685,000 breast cancer-related deaths, breast cancer accounted for around 24.5% of all cancer cases around the world in 2020 and 15 .5% of cancer deaths among women.1,2 Breast cancer was the most common cause of cancer mortality in women in 2020 and the fifth most common cause of cancer death.2 Furthermore, the number of breast cancer cases is expected to exceed 4 .4 million by 2070 .1\u003Cbr>The human breast is made up primarily of adipose (fat) and milk-producing glandular lobules.2 The lobules connect to create lobes, with each breast having around 15 to 20 lobesin total. Within the lobules, milk glands are connected to small ducts, which join together to |\n\n*Address all correspondence to Thi-Thu-Hien Pham, [ptthien@hcmiu.edu.vn](ptthien@hcmiu.edu.vn)  \nJournal of Biomedical Optics 052917-1 May 2024 • Vol. 29(5)  \nPham, Ngoc Quach, and Vo: Analysis of polarization features of human breast cancer. . .  \nform larger milk ducts that emerge through the nipple. The breast is linked to a network of blood and lymph veins, which serve to regulate the local fluid balance along with filter out harmful substances. Breast cancer metastases are formed mainly in the lymph nodes near the breast. However, the lymph veins carry lymph fluid to lymph nodes throughout the body, and thus breast cancer frequently spreads to other nearby lymph nodes, such as under the arm, above the collarbone, or in the chest. The breast is physically supported by a network of connective tissue that contains collagen. The breast densit","cbCaiuKQGv4BskjR","https://ap.wps.com/l/cbCaiuKQGv4BskjR","pdf",12331842,"English","# Abstract\n# 1 Introduction\n## Breast cancer burden and anatomy\n## Tumor definitions, classification, and stages\n## Treatment overview\n## Diagnostic imaging background","[{\"question\":\"What is the main objective of this study?\",\"answer\":\"To classify human breast tissue samples as healthy or cancerous by analyzing polarization features using Mueller matrix visualization with a surface-illuminated backscatter polarization imaging technique.\"},{\"question\":\"Which Mueller matrix elements are most informative for discrimination?\",\"answer\":\"Elements m23, m32, and m44 show distinct intensity and color characteristics between healthy and cancer samples, and statistical tests confirm their effectiveness.\"},{\"question\":\"How many breast tissue samples were used to validate the approach?\",\"answer\":\"The proposed approach was evaluated using 95 tissue samples: 35 healthy, 20 benign cancer, 20 grade-2 malignant, and 20 grade-3 malignant samples.\"}]","Analysis of polarization features of human breast cancer tissue by Mueller matrix visualization - Research Paper | PDF",1789975212,48]