OCTAVVS : A graphical toolbox for high-throughput preprocessing and analysis of vibrational spectroscopy imaging data
(2020) In Methods and Protocols 3(2). p.1-15- Abstract
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... (More)
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.
(Less)
- author
- Troein, Carl LU ; Siregar, Syahril LU ; Op De Beeck, Michiel LU ; Peterson, Carsten LU ; Tunlid, Anders LU and Persson, Per LU
- organization
-
- Computational Science for Health and Environment (research group)
- MEMEG
- Computational Biology and Biological Physics - Has been reorganised
- Department of Astronomy and Theoretical Physics - Has been reorganised
- BECC: Biodiversity and Ecosystem services in a Changing Climate
- Molecular Ecology and Evolution Lab (research group)
- Department of Biology
- Centre for Environmental and Climate Science (CEC)
- publishing date
- 2020-01-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Atmospheric correction, Hyperspectral, Infrared spectroscopy, MCR-ALS, Mie scattering correction
- in
- Methods and Protocols
- volume
- 3
- issue
- 2
- article number
- 34
- pages
- 15 pages
- publisher
- MDPI AG
- external identifiers
-
- pmid:32369914
- scopus:85089852713
- ISSN
- 2409-9279
- DOI
- 10.3390/mps3020034
- language
- English
- LU publication?
- yes
- id
- c488309b-0f8f-4235-b508-fb069bcc87ca
- date added to LUP
- 2020-09-07 12:59:23
- date last changed
- 2024-09-19 05:34:29
@article{c488309b-0f8f-4235-b508-fb069bcc87ca, abstract = {{<p>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.</p>}}, author = {{Troein, Carl and Siregar, Syahril and Op De Beeck, Michiel and Peterson, Carsten and Tunlid, Anders and Persson, Per}}, issn = {{2409-9279}}, keywords = {{Atmospheric correction; Hyperspectral; Infrared spectroscopy; MCR-ALS; Mie scattering correction}}, language = {{eng}}, month = {{01}}, number = {{2}}, pages = {{1--15}}, publisher = {{MDPI AG}}, series = {{Methods and Protocols}}, title = {{OCTAVVS : A graphical toolbox for high-throughput preprocessing and analysis of vibrational spectroscopy imaging data}}, url = {{http://dx.doi.org/10.3390/mps3020034}}, doi = {{10.3390/mps3020034}}, volume = {{3}}, year = {{2020}}, }