ArticleScientific reports2023
Müller matrix polarimetry for pancreatic tissue characterization.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 15 citations in OpenAlex.
- Polarimetric feature analysis of Mueller matrices for brain tumor image segmentation.Optics express · 2025Article
- Alignment of histological and polarimetric large-scale imaging for brain tissue characterization.Journal of biomedical optics · 2025Article
- On-Chip Polarization Light Microscopy.Biosensors · 2025Article
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11 authors at 2 institutions in 1 country.
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Abstract
Polarimetry is an optical characterization technique capable of analyzing the polarization state of light reflected by materials and biological samples. In this study, we investigate the potential of Müller matrix polarimetry (MMP) to analyze fresh pancreatic tissue samples. Due to its highly heterogeneous appearance, pancreatic tissue type differentiation is a complex task. Furthermore, its challenging location in the body makes creating direct imaging difficult. However, accurate and reliable methods for diagnosing pancreatic diseases are critical for improving patient outcomes. To this end, we measured the Müller matrices of ex-vivo unfixed human pancreatic tissue and leverage the feature-learning capabilities of a machine-learning model to derive an optimized data representation that minimizes normal-abnormal classification error. We show experimentally that our approach accurately differentiates between normal and abnormal pancreatic tissue. This is, to our knowledge, the first study to use ex-vivo unfixed human pancreatic tissue combined with feature-learning from raw Müller matrix readings for this purpose.
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