OCTAVVS

OCTAVVS provides high-throughput preprocessing and analysis of vibrational spectroscopy imaging data, with emphasis on infrared absorption hyperspectral images acquired using focal plane array detectors.

Key Features:

• High-throughput preprocessing: Processes focal plane array infrared hyperspectral images containing thousands of spectra and spatial resolutions down to a few micrometers.
• Atmospheric correction: Removes distortions caused by atmospheric absorption from spectroscopic data.
• Resonant Mie scattering correction: Implements a resonant Mie scattering algorithm optimized for speed and stability to correct light scattering by cellular structures.
• Baseline correction: Corrects varying baseline levels in vibrational spectroscopy data.
• Spectral decomposition (MCR-ALS): Performs Multivariate Curve Resolution - Alternating Least Squares (MCR-ALS) to decompose spectra into constituent components with region-of-interest selection.
• Clustering and cluster annotation: Clusters spectral data and provides cluster annotation capabilities to aid interpretation.
• Spatial heterogeneity handling: Supports analysis of spatially heterogeneous samples through localized preprocessing and decomposition.

Scientific Applications:

• Infrared absorption imaging: Analysis of infrared absorption hyperspectral images acquired with focal plane array detectors.
• Biological samples and cellular structures: Correction and analysis of spectra affected by light scattering and atmospheric absorption in spatially heterogeneous biological specimens.
• Biomedical imaging: Preprocessing and component analysis for biomedical imaging studies using vibrational spectroscopy.
• Materials science and chemical analysis: Spectral decomposition, clustering, and annotation for materials characterization and chemical analysis.

Methodology:

Atmospheric absorption correction; resonant Mie scattering correction algorithm for light scattering; baseline correction; Multivariate Curve Resolution - Alternating Least Squares (MCR-ALS) with region-of-interest selection for spectral decomposition; clustering and cluster annotation applied to focal plane array infrared hyperspectral images.