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.
Alexandrov
Theodore
T
Center for Industrial Mathematics, ZeTeM, University of Bremen, 28334 Bremen, Germany. theodore@math.uni-bremen.de
Becker
Michael
M
Deininger
Sren-Oliver
SO
Ernst
Günther
G
Wehder
Liane
L
Grasmair
Markus
M
von Eggeling
Ferdinand
F
Thiele
Herbert
H
Maass
Peter
P
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*