Automatic pseudo-coloring approaches to improve visual perception and contrast in polarimetric images of biological tissues
Rodríguez, Carla (Universitat Autònoma de Barcelona. Departament de Física)
Van Eeckhout, A. (Institut Polytechnique de Paris)
Garcia-Caurel, E. (Institut Polytechnique de Paris)
Lizana Tutusaus, Ángel (Universitat Autònoma de Barcelona. Departament de Física)
Campos Coloma, Juan (Universitat Autònoma de Barcelona. Departament de Física)

Data:	2022
Resum:	Imaging polarimetry methods have proved their suitability to enhance the image contrast between tissues and structures in organic samples, or even to reveal structures hidden in regular intensity images. These methods are nowadays used in a wide range of biological applications, as for the early diagnosis of different pathologies. To include the discriminatory potential of different polarimetric observables in a single image, a suitable strategy reported in literature consists in associating different observables to different color channels, giving rise to pseudo-colored images helping the visualization of different tissues in samples. However, previous reported polarimetric based pseudo-colored images of tissues are mostly based on simple linear combinations of polarimetric observables whose weights are set ad-hoc, and thus, far from optimal approaches. In this framework, we propose the implementation of two pseudo-colored methods. One is based on the Euclidean distances of actual values of pixels and an average value taken over a given region of interest in the considered image. The second method is based on the likelihood for each pixel to belong to a given class. Such classes being defined on the basis of a statistical model that describes the statistical distribution of values of the pixels in the considered image. The methods are experimentally validated on four different biological samples, two of animal origin and two of vegetal origin. Results provide the potential of the methods to be applied in biomedical and botanical applications.
Ajuts:	Agencia Estatal de Investigación PID2021-126509OB-C21
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Image processing ; Imaging ; Light responses ; Optics and photonics ; Software
Publicat a:	Scientific reports, Vol. 12 Núm. 1 (december 2022) , p. 18479, ISSN 2045-2322

DOI: 10.1038/s41598-022-23330-6
PMID: 36323771

16 p, 3.6 MB

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