Hee Ryung Lee,1 Pengcheng Li,2 Hui Ma,2 Christian Lotz,3,4 Florian Kai Groeber-Becker,3,4 Sofia Dembski,3,4 Razvigor Ossikovski,1 Tatiana Novikovahttps://orcid.org/0000-0002-9048-91581
1Lab. de Physique des Interfaces et des Couches Minces, CNRS (France) 2Tsinghua Univ. (China) 3Universitätsklinikum Würzburg (Germany) 4Fraunhofer-Institut für Silicatforschung ISC (Germany)
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Tissue-based diagnostic relies on histological analysis of tissue cuts by a pathologist who links data derived from microscopy image content to a specific disease. We explored the potential of Mueller microscopy combined with density-based spatial clustering algorithm for applications with noise for the automated analysis of tissue histological cuts.
Mueller microscopic images of unstained artificial human skin histological cuts were analyzed by applying differential Mueller matrix decomposition. Scalar retardance, depolarization and total transmitted intensity images were used for the automated segmentation of microscopic images. An algorithm of polarimetric data post-processing which mitigates the impact of tissue thickness fluctuations was suggested.
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