Linear unmixing protocol for hyperspectral image fusion analysis applied to a case study of vegetal tissues

Abstract Hyperspectral imaging (HSI) is a useful non-invasive technique that offers spatial and chemical information of samples. Often, different HSI techniques are used to obtain complementary information from the sample by combining different image modalities (Image Fusion). However, issues relate...

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Autores principales:	Adrián Gómez-Sánchez, Mónica Marro, Maria Marsal, Sara Zacchetti, Rodrigo Rocha de Oliveira, Pablo Loza-Alvarez, Anna de Juan
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/b2dc5839ffeb4ad7b15619402b09013c
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spelling	oai:doaj.org-article:b2dc5839ffeb4ad7b15619402b09013c2021-12-02T18:48:23ZLinear unmixing protocol for hyperspectral image fusion analysis applied to a case study of vegetal tissues10.1038/s41598-021-98000-02045-2322https://doaj.org/article/b2dc5839ffeb4ad7b15619402b09013c2021-09-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-98000-0https://doaj.org/toc/2045-2322Abstract Hyperspectral imaging (HSI) is a useful non-invasive technique that offers spatial and chemical information of samples. Often, different HSI techniques are used to obtain complementary information from the sample by combining different image modalities (Image Fusion). However, issues related to the different spatial resolution, sample orientation or area scanned among platforms need to be properly addressed. Unmixing methods are helpful to analyze and interpret the information of HSI related to each of the components contributing to the signal. Among those, Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) offers very suitable features for image fusion, since it can easily cope with multiset structures formed by blocks of images coming from different samples and platforms and allows the use of optional and diverse constraints to adapt to the specific features of each HSI employed. In this work, a case study based on the investigation of cross-sections from rice leaves by Raman, synchrotron infrared and fluorescence imaging techniques is presented. HSI of these three different techniques are fused for the first time in a single data structure and analyzed by MCR-ALS. This example is challenging in nature and is particularly suitable to describe clearly the necessary steps required to perform unmixing in an image fusion context. Although this protocol is presented and applied to a study of vegetal tissues, it can be generally used in many other samples and combinations of imaging platforms.Adrián Gómez-SánchezMónica MarroMaria MarsalSara ZacchettiRodrigo Rocha de OliveiraPablo Loza-AlvarezAnna de JuanNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Adrián Gómez-Sánchez Mónica Marro Maria Marsal Sara Zacchetti Rodrigo Rocha de Oliveira Pablo Loza-Alvarez Anna de Juan Linear unmixing protocol for hyperspectral image fusion analysis applied to a case study of vegetal tissues
description	Abstract Hyperspectral imaging (HSI) is a useful non-invasive technique that offers spatial and chemical information of samples. Often, different HSI techniques are used to obtain complementary information from the sample by combining different image modalities (Image Fusion). However, issues related to the different spatial resolution, sample orientation or area scanned among platforms need to be properly addressed. Unmixing methods are helpful to analyze and interpret the information of HSI related to each of the components contributing to the signal. Among those, Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) offers very suitable features for image fusion, since it can easily cope with multiset structures formed by blocks of images coming from different samples and platforms and allows the use of optional and diverse constraints to adapt to the specific features of each HSI employed. In this work, a case study based on the investigation of cross-sections from rice leaves by Raman, synchrotron infrared and fluorescence imaging techniques is presented. HSI of these three different techniques are fused for the first time in a single data structure and analyzed by MCR-ALS. This example is challenging in nature and is particularly suitable to describe clearly the necessary steps required to perform unmixing in an image fusion context. Although this protocol is presented and applied to a study of vegetal tissues, it can be generally used in many other samples and combinations of imaging platforms.
format	article
author	Adrián Gómez-Sánchez Mónica Marro Maria Marsal Sara Zacchetti Rodrigo Rocha de Oliveira Pablo Loza-Alvarez Anna de Juan
author_facet	Adrián Gómez-Sánchez Mónica Marro Maria Marsal Sara Zacchetti Rodrigo Rocha de Oliveira Pablo Loza-Alvarez Anna de Juan
author_sort	Adrián Gómez-Sánchez
title	Linear unmixing protocol for hyperspectral image fusion analysis applied to a case study of vegetal tissues
title_short	Linear unmixing protocol for hyperspectral image fusion analysis applied to a case study of vegetal tissues
title_full	Linear unmixing protocol for hyperspectral image fusion analysis applied to a case study of vegetal tissues
title_fullStr	Linear unmixing protocol for hyperspectral image fusion analysis applied to a case study of vegetal tissues
title_full_unstemmed	Linear unmixing protocol for hyperspectral image fusion analysis applied to a case study of vegetal tissues
title_sort	linear unmixing protocol for hyperspectral image fusion analysis applied to a case study of vegetal tissues
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/b2dc5839ffeb4ad7b15619402b09013c
work_keys_str_mv	AT adriangomezsanchez linearunmixingprotocolforhyperspectralimagefusionanalysisappliedtoacasestudyofvegetaltissues AT monicamarro linearunmixingprotocolforhyperspectralimagefusionanalysisappliedtoacasestudyofvegetaltissues AT mariamarsal linearunmixingprotocolforhyperspectralimagefusionanalysisappliedtoacasestudyofvegetaltissues AT sarazacchetti linearunmixingprotocolforhyperspectralimagefusionanalysisappliedtoacasestudyofvegetaltissues AT rodrigorochadeoliveira linearunmixingprotocolforhyperspectralimagefusionanalysisappliedtoacasestudyofvegetaltissues AT pablolozaalvarez linearunmixingprotocolforhyperspectralimagefusionanalysisappliedtoacasestudyofvegetaltissues AT annadejuan linearunmixingprotocolforhyperspectralimagefusionanalysisappliedtoacasestudyofvegetaltissues
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Linear unmixing protocol for hyperspectral image fusion analysis applied to a case study of vegetal tissues

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