2020
DOI: 10.1002/jbio.202000083
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Depolarization metric spaces for biological tissues classification

Abstract: Classification of tissues is an important problem in biomedicine. An efficient tissue classification protocol allows, for instance, the guidedrecognition of structures through treated images or discriminating between healthy and unhealthy regions (e.g., early detection of cancer). In this framework, we study the potential of some polarimetric metrics, the so-called depolarization spaces, for the classification of biological tissues. The analysis is performed using 120 biological ex vivo samples of three differ… Show more

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Cited by 19 publications
(12 citation statements)
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“…A depolarization space gives information not just on how much light is depolarized but also on how it is depolarized by the sample. The definition of a depolarization space is not unique 52,53 and a choice must be done based on multiple criteria such as discrimination power between depolarization metrics, computation time, adequacy to the physical problem treated among others 54 . The depolarization space used in this work is composed by the IPPs 55 , which can be directly deduced from the measured Mueller matrix of the sample.…”
Section: Methodsmentioning
confidence: 99%
“…A depolarization space gives information not just on how much light is depolarized but also on how it is depolarized by the sample. The definition of a depolarization space is not unique 52,53 and a choice must be done based on multiple criteria such as discrimination power between depolarization metrics, computation time, adequacy to the physical problem treated among others 54 . The depolarization space used in this work is composed by the IPPs 55 , which can be directly deduced from the measured Mueller matrix of the sample.…”
Section: Methodsmentioning
confidence: 99%
“…We now further analyze the potential of those observables to discriminate between different typologies (healthy or diseased tissues) of plant structures. To do so, we represent the measured data on different polarimetric spaces 41 , this leading to a very intuitive visualization of data, and also providing quantitative information of the structures (or tissue types) that may be present in the images of the probed samples. Moreover, the data in each ROI is collected and grouped in what we call a data-cloud which can be used for ulterior statistical data treatment or for graphical representation.…”
Section: Resultsmentioning
confidence: 99%
“…30 The former also was observed to provide high classification efficiency and contrast in biological tissues. 31,32…”
Section: Mueller Matrix Calculation and Analysismentioning
confidence: 99%