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Kim, M. ; Lee, H.R.* ; Ossikovski, R.* ; Jobart-Malfait, A.* ; Lamarque, D.* ; Novikova, T.*

Digital histology of gastric tissue biopsies with liquid crystal-based Mueller microscope and machine learning approach.

In: (Liquid Crystals Optics and Photonic Devices 2024, 8-11 April 2024, Strasbourg). 1000 20th St, Po Box 10, Bellingham, Wa 98227-0010 Usa: SPIE, 2024. DOI: 10.1117/12.3021846 (Proc. SPIE ; 13016)

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We investigated gastric tissue biopsies using a liquid crystal-based Mueller microscope and a machine-learning approach to examine the degree of inflammation. Machine learning and statistical analysis were performed with the multidimensional dataset including the polarimetric properties (linear retardance and dichroism, and circular depolarization) and total transmitted intensity images of the unstained thin sections of gastric tissue to identify and quantify the microstructural differences between healthy control, chronic gastritis, and gastric cancer.

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