Polarimetric data-based model for tissue recognition
Carla Rodríguez,Albert Van Eeckhout,Laia Ferrer,Enrique Garcia-Caurel,Emilio González-Arnay,Juan Campos,Angel Lizana +6 more
TLDR
In this paper, the potential of a predictive optical model method for tissue recognition, based on the statistical analysis of different polarimetric indicators that retrieve complete polarIMetric information (selective absorption, retardance and depolarization) of samples.Abstract:
We highlight the potential of a predictive optical model method for tissue recognition, based on the statistical analysis of different polarimetric indicators that retrieve complete polarimetric information (selective absorption, retardance and depolarization) of samples. The study is conducted on the experimental Mueller matrices of four biological tissues (bone, tendon, muscle and myotendinous junction) measured from a collection of 157 ex-vivo chicken samples. Moreover, we perform several non-parametric data distribution analyses to build a logistic regression-based algorithm capable to recognize, in a single and dynamic measurement, whether a sample corresponds (or not) to one of the four different tissue categories.read more
Citations
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Polarization-Based Histopathology Classification of Ex Vivo Colon Samples Supported by Machine Learning
Deyan Ivanov,Viktor Dremin,Ts. Genova,Alexander Bykov,Tatiana Novikova,Razvigor Ossikovski,Igor Meglinski +6 more
TL;DR: The presented polarimetric model was able to support the physical interpretation of the results from previous studies and relate the latter to the samples’ health condition, respectively.
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Polarization-based probabilistic discriminative model for quantitative characterization of cancer cells
TL;DR: In this paper , a polarization-based probabilistic discriminative model for deriving a set of new sigmoid-transformed polarimetry feature parameters, which not only enables accurate and quantitative characterization of cancer cells at pixel level, but also accomplish the task with a simple and stable model.
Journal ArticleDOI
Polarimetric observables for the enhanced visualization of plant diseases
Carla Rodríguez,Enrique Garcia-Caurel,Teresa Garnatje,Mireia Serra I Ribas,Jordi Luque,Juan Campos,Angel Lizana +6 more
TL;DR: In this article , a set of different plant specimens showing various disease symptoms and infection stages were inspected by means of a complete image Mueller polarimeter, from which the depolarization information of vegetal tissues leads to the enhancement of image contrast between healthy and diseased tissues.
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Automatic pseudo-coloring approaches to improve visual perception and contrast in polarimetric images of biological tissues
TL;DR: In this paper , two pseudo-colored methods are proposed 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.
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Optimizing the classification of biological tissues using machine learning models based on polarized data
TL;DR: In this paper , a comparative study of 12 classification models based on different polarimetric datasets was conducted to find the ideal framework to construct tissues classification models, which highlight the importance of using raw Mueller matrix elements for the design of classification models.
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