Multiorder
Correction Algorithms to Remove Image Distortions
from Mass Spectrometry Imaging Data Sets
- Publication date
- Publisher
Abstract
Time-of-flight
secondary ion mass spectrometry imaging is a rapidly
evolving technology. Its main application is the study of the distribution
of small molecules on biological tissues. The sequential image acquisition
process remains susceptible to measurement distortions that can render
imaging data less analytically useful. Most of these artifacts show
a repetitive nature from tile to tile. Here we statistically describe
these distortions and derive two different algorithms to correct them.
Both a generalized linear model approach and the linear discriminant
analysis approach are able to increase image quality for negative
and positive ion mode data sets. Additionally, performing simulation
studies with repetitive and nonrepetitive tiling error we show that
both algorithms are only removing repetitive distortions. It is further
shown that the spectral component of the data set is not altered by
the use of these correction methods. Both algorithms presented in
this work greatly increase the image quality and improve the analytical
usefulness of distorted images dramatically