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Journal of Biomedical Optics • Open Access

Quantitatively differentiating microstructures of tissues by frequency distributions of Mueller matrix images
Author(s): Chao He; Honghui He; Xianpeng Li; Jintao Chang; Ye Wang; Shaoxiong Liu; Nan Zeng; Yonghong He; Hui Ma

Paper Abstract

We present a new way to extract characteristic features of the Mueller matrix images based on their frequency distributions and the central moments. We take the backscattering Mueller matrices of tissues with distinctive microstructures, and then analyze the frequency distribution histograms (FDHs) of all the matrix elements. For anisotropic skeletal muscle and isotropic liver tissues, we find that the shapes of the FDHs and their central moment parameters, i.e., variance, skewness, and kurtosis, are not sensitive to the sample orientation. Comparisons among different tissues further indicate that the frequency distributions of Mueller matrix elements and their corresponding central moments can be used as indicators for the characteristic microstructural features of tissues. A preliminary application to human cervical cancerous tissues shows that the distribution curves and central moment parameters may have the potential to give quantitative criteria for cancerous tissues detections.

Paper Details

Date Published: 21 October 2015
PDF: 9 pages
J. Biomed. Opt. 20(10) 105009 doi: 10.1117/1.JBO.20.10.105009
Published in: Journal of Biomedical Optics Volume 20, Issue 10
Show Author Affiliations
Chao He, Graduate School at Shenzhen, Tsinghua Univ. (China)
Institute of Optical Imaging and Sensing (China)
Shenzhen Key Lab. for Minimal Invasive Medical Technologies (China)
Honghui He, Graduate School at Shenzhen, Tsinghua Univ. (China)
Institute of Optical Imaging and Sensing (China)
Shenzhen Key Lab. for Minimal Invasive Medical Technologies (China)
Xianpeng Li, Graduate School at Shenzhen, Tsinghua Univ. (China)
Institute of Optical Imaging and Sensing (China)
Shenzhen Key Lab. for Minimal Invasive Medical Technologies (China)
Jintao Chang, Graduate School at Shenzhen, Tsinghua Univ. (China)
Institute of Optical Imaging and Sensing (China)
Shenzhen Key Lab. for Minimal Invasive Medical Technologies (China)
Ye Wang, Graduate School at Shenzhen, Tsinghua Univ. (China)
Institute of Optical Imaging and Sensing (China)
Shenzhen Key Lab. for Minimal Invasive Medical Technologies (China)
Shaoxiong Liu, Huazhong Univ. of Science and Technology (China)
Shenzhen Sixth People’s Hospital Nanshan Hospital (China)
Nan Zeng, Graduate School at Shenzhen, Tsinghua Univ. (China)
Institute of Optical Imaging and Sensing (China)
Shenzhen Key Lab. for Minimal Invasive Medical Technologies (China)
Yonghong He, Graduate School at Shenzhen, Tsinghua Univ. (China)
Institute of Optical Imaging and Sensing (China)
Shenzhen Key Lab. for Minimal Invasive Medical Technologies (China)
Hui Ma, Graduate School at Shenzhen, Tsinghua Univ. (China)
Institute of Optical Imaging and Sensing (China)
Shenzhen Key Lab. for Minimal Invasive Medical Technologies (China)


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