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                  <mods:namePart>Gil, José J.</mods:namePart>
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                  <mods:namePart>San José, Ignacio</mods:namePart>
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                  <mods:namePart>Canabal-Carbia, Mónica</mods:namePart>
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                  <mods:namePart>Estévez, Irene</mods:namePart>
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                  <mods:namePart>González-Arnay, Emilio</mods:namePart>
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                  <mods:namePart>Luque, Jordi</mods:namePart>
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                  <mods:namePart>Garnatje, Teresa</mods:namePart>
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                  <mods:namePart>Campos, Juan</mods:namePart>
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                  <mods:namePart>Lizana, Angel</mods:namePart>
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                  <mods:namePart>Producció Vegetal</mods:namePart>
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                  <mods:namePart>Protecció Vegetal Sostenible</mods:namePart>
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                  <mods:dateAccessioned encoding="iso8601">2025-10-22T11:27:14Z</mods:dateAccessioned>
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                  <mods:dateIssued encoding="iso8601">2023-06-08</mods:dateIssued>
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               <mods:identifier type="citation">Gil, José J., Ignacio San José, Mónica Canabal-Carbia, Irene Estévez, Emilio González-Arnay, Jordi Luque, Teresa Garnatje, Juan Campos, and Angel Lizana. 2023. "Polarimetric Images Of Biological Tissues Based On The Arrow Decomposition Of Mueller Matrices". Photonics 10 (6): 669. https://www.mdpi.com/2304-6732/10/6/669.</mods:identifier>
               <mods:identifier type="issn">2304-6732</mods:identifier>
               <mods:identifier type="uri">http://hdl.handle.net/20.500.12327/2264</mods:identifier>
               <mods:identifier type="doi">https://doi.org/10.3390/photonics10060669</mods:identifier>
               <mods:abstract>Polarimetric techniques are widely used in a vast number of applications such as remote sensing, material characterization, astronomy and biological tissue inspection. In this last scenario, different polarimetric observables have proved their potential for enhancing imaging visualization. In this work we use a set of polarimetric observables derived from the arrow decomposition of the Mueller matrix for the first time: enpolarizing, retarding and depolarizing descriptors. In particular, the mean intensity coefficient and the three indices of polarimetric purity, the absolute values and Poincaré orientations of diattenuation, polarizance, entrance retardance and exit retardance vectors are considered. Results show images with enhanced visualization or even revealing invisible structures when compared to standard intensity images. In particular, thanks to these metrics, we improve the visualization of the necrotic areas of a Vitis rupestris leaf. In the case of animal samples, boundaries between different fascicles inside a tendon of an ex vivo chicken sample are revealed, as is the directionality of fiber tracts of the subcortical white matter in an ex vivo cow brain. The experimental results show the potential for biophotonics imaging and how polarimetric techniques could be useful for biomedical and botanical applications.</mods:abstract>
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                  <mods:title>Polarimetric Images of Biological Tissues Based on the Arrow Decomposition of Mueller Matrices</mods:title>
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