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Spectral mapping tools from the earth sciences applied to spectral microscopy data.

A Thomas Harris¹

¹Global Services Consultant, ITT Visual Information Solutions, Boulder, CO 80301, USA. tharris@ittvis.com

Cytometry. Part a : the Journal of the International Society for Analytical Cytology

|September 14, 2006

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Spectral imaging algorithms from earth remote sensing can be successfully applied to spectral microscopy for material identification. These powerful tools, developed over decades, accurately map material locations and abundances in microscopic images.

Area of Science:

Microscopy
Spectroscopy
Remote Sensing

Background:

Spectral imaging, a technique from earth remote sensing, is increasingly used for material identification.
Existing spectral microscopy analysis methods often violate algorithm assumptions.
This study adapts advanced earth imaging algorithms for spectral microscopy.

Purpose of the Study:

To demonstrate the applicability of earth remote sensing spectral analysis tools to spectral microscopy data.
To adapt algorithms for material identification in microscopy images.

Main Methods:

Utilized earth imaging software (ENVI) to analyze spectral microscopy data from a Leica confocal microscope.
Selected spectral training signatures (endmembers) using the "spectral hourglass" processing flow.

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Applied ENVI mapping algorithms to determine endmember locations and abundances.

Main Results:

Spectral analysis algorithms showed broad agreement in mapping and abundance analysis.
Visual and statistical assessments confirmed the reliability of the output classification images.
Identified material locations and subpixel abundances with high accuracy.

Conclusions:

Powerful spectral analysis algorithms from earth imaging research are transferable to spectral microscopy.
Despite scale differences, the core problem of mapping materials based on spectral signatures remains consistent.
COTS software offers robust solutions for spectral microscopy data analysis.