Spatial segmentation of imaging mass spectrometry data with edge-preserving image denoising and clustering.
In recent years, matrix-assisted laser desorption/ionization (MALDI)-imaging mass spectrometry has become a mature technology, allowing for reproducible high-resolution measurements to localize proteins and smaller molecules. However, despite this impressive technological advance, only a few papers have been published concerned with computational methods for MALDI-imaging data. We address this issue proposing a new procedure for spatial segmentation of MALDI-imaging data sets. This procedure clusters all spectra into different groups based on their similarity. This partition is represented by a segmentation map, which helps to understand the spatial structure of the sample. The core of our segmentation procedure is the edge-preserving denoising of images corresponding to specific masses that reduces pixel-to-pixel variability and improves the segmentation map significantly. Moreover, before applying denoising, we reduce the data set selecting peaks appearing in at least 1% of spectra. High dimensional discriminant clustering completes the procedure. We analyzed two data sets using the proposed pipeline. First, for a rat brain coronal section the calculated segmentation maps highlight the anatomical and functional structure of the brain. Second, a section of a neuroendocrine tumor invading the small intestine was interpreted where the tumor area was discriminated and functionally similar regions were indicated.
Center for Industrial Mathematics, ZeTeM, University of Bremen, 28334 Bremen, Germany. theodore@math.uni-bremen.de
Theodore
T
Alexandrov
Michael
M
Becker
Sren-Oliver
SO
Deininger
Günther
G
Ernst
Liane
L
Wehder
Markus
M
Grasmair
Ferdinand
F
von Eggeling
Herbert
H
Thiele
Peter
P
Maass
D000818:Animals; D001921:Brain / Q000033:anatomy & histology*; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D007421:Intestine, Small / Q000473:pathology; D008953:Models, Anatomic; D018358:Neuroendocrine Tumors / Q000473:pathology; D051381:Rats; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods*