Evaluating tissue mechanical properties using Mueller matrix polarimetry

Jiahao Fan; Honghui He; Hui Ma

doi:10.1117/12.2691003

28 July 2023 Evaluating tissue mechanical properties using Mueller matrix polarimetry

Jiahao Fan, Honghui He, Hui Ma

Proceedings Volume 12753, Second Conference on Biomedical Photonics and Cross-Fusion (BPC 2023); 1275303 (2023) https://doi.org/10.1117/12.2691003
Event: Second Conference on Biomedical Photonics and Cross-Fusion (BPC 2023), 2023, Shanghai, China

Abstract

Evaluating tissue mechanical properties is an important issue in the biomedical field. While traditional in vitro tissue deformation experiments have been used to measure mechanical properties, optical methods are becoming increasingly popular due to their non-invasive and non-contact advantages. In this study, we utilized Mueller matrix polarimetry to quantify the mechanical properties of bovine tendon tissue. We acquired 3×3 Mueller matrix images of the tendon tissue samples under various stretching states using a backscattering measurement setup based on a polarization camera, enabling us to examine changes in both structural information and optical properties. Subsequently, we extracted frequency distribution histograms of Mueller matrix elements to elucidate the structural changes in the tendon tissue during the stretching process. We then calculated the Mueller matrix transformation parameters, namely the total anisotropy t1 and anisotropy direction α1 of the tendon tissue samples under different stretching processes, to characterize their structural changes quantitatively. For better discrimination of tendon tissues under different stretching states, we trained an image classification neural network using the derived MMT parameters as input. Ultimately, we obtained a highly accurate model with 90% precision. The results demonstrate the potential of Mueller matrix polarimetry as a tool for evaluating tissue mechanical properties.

Citation Download Citation

Jiahao Fan, Honghui He, and Hui Ma "Evaluating tissue mechanical properties using Mueller matrix polarimetry", Proc. SPIE 12753, Second Conference on Biomedical Photonics and Cross-Fusion (BPC 2023), 1275303 (28 July 2023); https://doi.org/10.1117/12.2691003

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KEYWORDS

Mueller matrices

Biological samples

Tissues

Polarization

Polarimetry

Anisotropy

Neural networks

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