Automatic Generic Registration of Mass Spectrometry
Imaging Data to Histology Using Nonlinear Stochastic Embedding
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Abstract
The
combination of mass spectrometry imaging and histology has
proven a powerful approach for obtaining molecular signatures from
specific cells/tissues of interest, whether to identify biomolecular
changes associated with specific histopathological entities or to
determine the amount of a drug in specific organs/compartments. Currently
there is no software that is able to explicitly register mass spectrometry
imaging data spanning different ionization techniques or mass analyzers.
Accordingly, the full capabilities of mass spectrometry imaging are
at present underexploited. Here we present a fully automated generic
approach for registering mass spectrometry imaging data to histology
and demonstrate its capabilities for multiple mass analyzers, multiple
ionization sources, and multiple tissue types