2 research outputs found
Hyperspectral Visualization of Mass Spectrometry Imaging Data
The acquisition of localized molecular spectra with mass
spectrometry
imaging (MSI) has a great, but as yet not fully realized, potential
for biomedical diagnostics and research. The methodology generates
a series of mass spectra from discrete sample locations, which is
often analyzed by visually interpreting specifically selected images
of individual masses. We developed an intuitive color-coding scheme
based on hyperspectral imaging methods to generate a single overview
image of this complex data set. The image color-coding is based on
spectral characteristics, such that pixels with similar molecular
profiles are displayed with similar colors. This visualization strategy
was applied to results of principal component analysis, self-organizing
maps and t-distributed stochastic neighbor embedding. Our approach
for MSI data analysis, combining automated data processing, modeling
and display, is user-friendly and allows both the spatial and molecular
information to be visualized intuitively and effectively
Hyperspectral Visualization of Mass Spectrometry Imaging Data
The acquisition of localized molecular spectra with mass
spectrometry
imaging (MSI) has a great, but as yet not fully realized, potential
for biomedical diagnostics and research. The methodology generates
a series of mass spectra from discrete sample locations, which is
often analyzed by visually interpreting specifically selected images
of individual masses. We developed an intuitive color-coding scheme
based on hyperspectral imaging methods to generate a single overview
image of this complex data set. The image color-coding is based on
spectral characteristics, such that pixels with similar molecular
profiles are displayed with similar colors. This visualization strategy
was applied to results of principal component analysis, self-organizing
maps and t-distributed stochastic neighbor embedding. Our approach
for MSI data analysis, combining automated data processing, modeling
and display, is user-friendly and allows both the spatial and molecular
information to be visualized intuitively and effectively