Cargando…

OCTAVVS: A Graphical Toolbox for High-Throughput Preprocessing and Analysis of Vibrational Spectroscopy Imaging Data

Modern vibrational spectroscopy techniques enable the rapid collection of thousands of spectra in a single hyperspectral image, allowing researchers to study spatially heterogeneous samples at micrometer resolution. A number of algorithms have been developed to correct for effects such as atmospheri...

Descripción completa

Detalles Bibliográficos
Autores principales: Troein, Carl, Siregar, Syahril, Op De Beeck, Michiel, Peterson, Carsten, Tunlid, Anders, Persson, Per
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7359710/
https://www.ncbi.nlm.nih.gov/pubmed/32369914
http://dx.doi.org/10.3390/mps3020034
_version_ 1783559100369469440
author Troein, Carl
Siregar, Syahril
Op De Beeck, Michiel
Peterson, Carsten
Tunlid, Anders
Persson, Per
author_facet Troein, Carl
Siregar, Syahril
Op De Beeck, Michiel
Peterson, Carsten
Tunlid, Anders
Persson, Per
author_sort Troein, Carl
collection PubMed
description Modern vibrational spectroscopy techniques enable the rapid collection of thousands of spectra in a single hyperspectral image, allowing researchers to study spatially heterogeneous samples at micrometer resolution. A number of algorithms have been developed to correct for effects such as atmospheric absorption, light scattering by cellular structures and varying baseline levels. After preprocessing, spectra are commonly decomposed and clustered to reveal informative patterns and subtle spectral changes. Several of these steps are slow, labor-intensive and require programming skills to make use of published algorithms and code. We here present a free and platform-independent graphical toolbox that allows rapid preprocessing of large sets of spectroscopic images, including atmospheric correction and a new algorithm for resonant Mie scattering with improved speed. The software also includes modules for decomposition into constituent spectra using the popular Multivariate Curve Resolution–Alternating Least Squares (MCR-ALS) algorithm, augmented by region-of-interest selection, as well as clustering and cluster annotation.
format Online
Article
Text
id pubmed-7359710
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-73597102020-08-07 OCTAVVS: A Graphical Toolbox for High-Throughput Preprocessing and Analysis of Vibrational Spectroscopy Imaging Data Troein, Carl Siregar, Syahril Op De Beeck, Michiel Peterson, Carsten Tunlid, Anders Persson, Per Methods Protoc Article Modern vibrational spectroscopy techniques enable the rapid collection of thousands of spectra in a single hyperspectral image, allowing researchers to study spatially heterogeneous samples at micrometer resolution. A number of algorithms have been developed to correct for effects such as atmospheric absorption, light scattering by cellular structures and varying baseline levels. After preprocessing, spectra are commonly decomposed and clustered to reveal informative patterns and subtle spectral changes. Several of these steps are slow, labor-intensive and require programming skills to make use of published algorithms and code. We here present a free and platform-independent graphical toolbox that allows rapid preprocessing of large sets of spectroscopic images, including atmospheric correction and a new algorithm for resonant Mie scattering with improved speed. The software also includes modules for decomposition into constituent spectra using the popular Multivariate Curve Resolution–Alternating Least Squares (MCR-ALS) algorithm, augmented by region-of-interest selection, as well as clustering and cluster annotation. MDPI 2020-05-01 /pmc/articles/PMC7359710/ /pubmed/32369914 http://dx.doi.org/10.3390/mps3020034 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Troein, Carl
Siregar, Syahril
Op De Beeck, Michiel
Peterson, Carsten
Tunlid, Anders
Persson, Per
OCTAVVS: A Graphical Toolbox for High-Throughput Preprocessing and Analysis of Vibrational Spectroscopy Imaging Data
title OCTAVVS: A Graphical Toolbox for High-Throughput Preprocessing and Analysis of Vibrational Spectroscopy Imaging Data
title_full OCTAVVS: A Graphical Toolbox for High-Throughput Preprocessing and Analysis of Vibrational Spectroscopy Imaging Data
title_fullStr OCTAVVS: A Graphical Toolbox for High-Throughput Preprocessing and Analysis of Vibrational Spectroscopy Imaging Data
title_full_unstemmed OCTAVVS: A Graphical Toolbox for High-Throughput Preprocessing and Analysis of Vibrational Spectroscopy Imaging Data
title_short OCTAVVS: A Graphical Toolbox for High-Throughput Preprocessing and Analysis of Vibrational Spectroscopy Imaging Data
title_sort octavvs: a graphical toolbox for high-throughput preprocessing and analysis of vibrational spectroscopy imaging data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7359710/
https://www.ncbi.nlm.nih.gov/pubmed/32369914
http://dx.doi.org/10.3390/mps3020034
work_keys_str_mv AT troeincarl octavvsagraphicaltoolboxforhighthroughputpreprocessingandanalysisofvibrationalspectroscopyimagingdata
AT siregarsyahril octavvsagraphicaltoolboxforhighthroughputpreprocessingandanalysisofvibrationalspectroscopyimagingdata
AT opdebeeckmichiel octavvsagraphicaltoolboxforhighthroughputpreprocessingandanalysisofvibrationalspectroscopyimagingdata
AT petersoncarsten octavvsagraphicaltoolboxforhighthroughputpreprocessingandanalysisofvibrationalspectroscopyimagingdata
AT tunlidanders octavvsagraphicaltoolboxforhighthroughputpreprocessingandanalysisofvibrationalspectroscopyimagingdata
AT perssonper octavvsagraphicaltoolboxforhighthroughputpreprocessingandanalysisofvibrationalspectroscopyimagingdata