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msi-image-norm-jss.pdf (2.92 MB)

Contrast Optimization of Mass Spectrometry Imaging (MSI) Data Visualization by Threshold Intensity Quantization (TrIQ)

submitted on 15.05.2020 and posted on 18.05.2020 by Robert Winkler, Ignacio Rosas-Román
Mass spectrometry imaging (MSI) enables the unbiased characterization of surfaces with respect to their chemical composition. In biological MSI, zones with differential
mass profiles hint towards localized physiological processes, such as the tissue-specific accumulation of secondary metabolites, or diseases, such as cancer. Thus, the efficient
discovery of ‘regions of interest’ (ROI) is of utmost importance in MSI. However, often the discovery of ROIs is hampered by high background noise and artifact signals. Especially in ambient ionization MSI, unmasking biologically relevant information from crude data sets is challenging. Therefore, we implemented a Threshold Intensity Quantization (TrIQ) algorithm for augmenting the contrast in MSI data visualizations. The simple algorithm reduces the impact of extreme values (‘outliers’) and rescales the dynamic range of mass signals. We provide an R script for post-processing MSI data in the imzML community format ( and implemented the TrIQ in our open-source imaging software RmsiGUI ( Applying these programs to different biological MSI data sets demonstrated the universal applicability of TrIQ for improving the contrast in the MSI data visualization. We show that TrIQ improves a subsequent detection of ROIs by sectioning. In addition, the adjustment of the dynamic signal intensity range makes MSI data sets comparable.


CONACyT-DFG 2016/277850

CONACyT PostDoc scholarship


Email Address of Submitting Author


Cinvestav Unidad Irapuato



ORCID For Submitting Author


Declaration of Conflict of Interest

RW is the co-inventor of the patent application “Non-thermal plasma jet device as source of spatial ionisation for ambient mass spectrometry and method of application” (WO 2014/057409) and a shareholder of the company Kuturabi SA de CV.

Version Notes

Initial version.