Peak detection for MALDI mass spectrometry imaging data using sparse frame multipliers

2019/10/31 by Lieb, Florian, Boskamp, Tobias, Stark, Hans-Georg
#FOS: Electrical engineering #FOS: Mathematics #Image and Video Processing (eess.IV) #Numerical Analysis (math.NA) #electronic engineering #information engineering

paper · doi:10.48550/arxiv.1911.00491

Abstract

MALDI mass spectrometry imaging (MALDI MSI) is a spatially resolved analytical tool for biological tissue analysis by measuring mass-to-charge ratios of ionized molecules. With increasing spatial and mass resolution of MALDI MSI data, appropriate data analysis and interpretation is getting more and more challenging. A reliable separation of important peaks from noise (aka peak detection) is a prerequisite for many subsequent processing steps and should be as accurate as possible. We propose a novel peak detection algorithm based on sparse frame multipliers, which can be applied to raw MALDI MSI data without prior preprocessing. The accuracy is evaluated on a simulated data set in comparison with a state-of-the-art algorithm. These results also show the proposed method's robustness to baseline and noise effects. In addition, the method is evaluated on two real MALDI-TOF data sets, whereby spatial information can be included in the peak picking process.

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