
Michiel Op de Beeck
Researcher

OCTAVVS : A graphical toolbox for high-throughput preprocessing and analysis of vibrational spectroscopy imaging data
Author
Summary, in English
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.
Department/s
- Computational Biology and Biological Physics - Undergoing reorganization
- Department of Astronomy and Theoretical Physics - Undergoing reorganization
- BECC: Biodiversity and Ecosystem services in a Changing Climate
- MEMEG
- Molecular Ecology and Evolution Lab
- Department of Biology
- Centre for Environmental and Climate Science (CEC)
Publishing year
2020-01-01
Language
English
Pages
1-15
Publication/Series
Methods and Protocols
Volume
3
Issue
2
Document type
Journal article
Publisher
MDPI AG
Topic
- Biological Sciences
- Other Physics Topics
Keywords
- Atmospheric correction
- Hyperspectral
- Infrared spectroscopy
- MCR-ALS
- Mie scattering correction
Status
Published
Research group
- Molecular Ecology and Evolution Lab
ISBN/ISSN/Other
- ISSN: 2409-9279