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Por favor, use este identificador para citar o enlazar este ítem: https://hdl.handle.net/20.500.12008/52117 Cómo citar
Título: Field of view extension in Mueller matrix microscopy for whole-slide imaging of biological samples
Autor: Demczylo, Roman
Silva Piedra, Diego
Lecumberry, Federico
Fernández, Ariel
Tipo: Artículo
Palabras clave: Polarized light microscopy, Mueller matrix, Whole slide imaging
Fecha de publicación: 2025
Resumen: Quantitative measures of the interaction of polarized light with tissue have been established as a powerful tool for biomedical diagnosis in recent years. In this regard, we implemented a microscopy setup that incorporates a polarized sensor in the imaging plane to obtain Stokes parameters corresponding to a given Field of View (FoV) of a tissue sample. By illuminating with linearly independent States of Polarization in the input, Mueller matrix elements can also be retrieved from the same FoV of the sample. In order to achieve whole-slide imaging the FoV can be extended by stitching multiple images taken after XY displacement. We propose introducing polarimetric features, specifically the Mueller matrix norm for each pixel, into the stitching algorithm. This allows for FoV extension with minimal overlap between neighboring images, substantially reducing the total number of images required for the entire sample. This approach can significantly reduce acquisition time and data storage requirements for whole-slide MM imaging. Validation results for the retrieval of whole-slide MM of tissue samples show SSIM = 0.93±0.04 and 100% stitching success from images with overlapping as low as 35%.
Editorial: Elsevier
EN: Results in Optics, vol. 21, dec. 2025, pp. 1-9.
Financiadores: Comisión Sectorial de Investigación Científica (22520240100040UD).
Citación: Demczylo, R., Silva Piedra, D., Lecumberry, F. y otros. "Field of view extension in Mueller matrix microscopy for whole-slide imaging of biological samples". Results in Optics. [en línea]. 2025, vol. 21, pp. 1-9. DOI: 10.1016/j.rio.2025.100916.
ISSN: 2666-9501
Departamento académico: Procesamiento de Señales
Grupo de investigación: Tratamiento de Imagenes
Licencia: Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
Aparece en las colecciones: Publicaciones académicas y científicas - Instituto de Ingeniería Eléctrica

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