OASIcs.GCB.2012.39.pdf
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A Two-Step Soft Segmentation Procedure for MALDI Imaging Mass Spectrometry Data
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German Conference on Bioinformatics 2012 (GCB 2012)
Series: Open Access Series in Informatics (OASIcs) - License:
Creative Commons Attribution-NoDerivs 3.0 Unported license
- Publication Date: 2012-09-13
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Ilya Chernyavsky, Theodore Alexandrov, Peter Maass, and Sergey I. Nikolenko. A Two-Step Soft Segmentation Procedure for MALDI Imaging Mass Spectrometry Data. In German Conference on Bioinformatics 2012. Open Access Series in Informatics (OASIcs), Volume 26, pp. 39-48, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)
https://doi.org/10.4230/OASIcs.GCB.2012.39
https://doi.org/10.4230/OASIcs.GCB.2012.39
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.
Keywords
- MALDI imaging mass spectrometry
- hyperspectral image segmentation
- probabilistic graphical models
- latent Dirichlet allocation
- Markov random field
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