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When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.GCB.2012.39
URN: urn:nbn:de:0030-drops-37163
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2012/3716/
Chernyavsky, Ilya ;
Alexandrov, Theodore ;
Maass, Peter ;
Nikolenko, Sergey I.
A Two-Step Soft Segmentation Procedure for MALDI Imaging Mass Spectrometry Data
Abstract
We propose a new method for soft spatial segmentation of matrix assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) data which is based on probabilistic clustering with subsequent smoothing. Clustering of spectra is done with the Latent Dirichlet Allocation (LDA) model. Then, clustering results are smoothed with a Markov random field (MRF) resulting in a soft probabilistic segmentation map. We show several extensions of the basic MRF model specifically tuned for MALDI-IMS data segmentation. We describe a highly parallel implementation of the smoothing algorithm based on GraphLab framework and show experimental results.
BibTeX - Entry
@InProceedings{chernyavsky_et_al:OASIcs:2012:3716,
author = {Ilya Chernyavsky and Theodore Alexandrov and Peter Maass and Sergey I. Nikolenko},
title = {{A Two-Step Soft Segmentation Procedure for MALDI Imaging Mass Spectrometry Data}},
booktitle = {German Conference on Bioinformatics 2012},
pages = {39--48},
series = {OpenAccess Series in Informatics (OASIcs)},
ISBN = {978-3-939897-44-6},
ISSN = {2190-6807},
year = {2012},
volume = {26},
editor = {Sebastian B{\"o}cker and Franziska Hufsky and Kerstin Scheubert and Jana Schleicher and Stefan Schuster},
publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
address = {Dagstuhl, Germany},
URL = {http://drops.dagstuhl.de/opus/volltexte/2012/3716},
URN = {urn:nbn:de:0030-drops-37163},
doi = {10.4230/OASIcs.GCB.2012.39},
annote = {Keywords: MALDI imaging mass spectrometry, hyperspectral image segmentation, probabilistic graphical models, latent Dirichlet allocation, Markov random field}
}
Keywords: |
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MALDI imaging mass spectrometry, hyperspectral image segmentation, probabilistic graphical models, latent Dirichlet allocation, Markov random field |
Collection: |
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German Conference on Bioinformatics 2012 |
Issue Date: |
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2012 |
Date of publication: |
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13.09.2012 |