2026-08-18T12:34:18Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:3716 2024-03-06T10:29:05Z ddc:004 open_access

A Two-Step Soft Segmentation Procedure for MALDI Imaging Mass Spectrometry Data Chernyavsky, Ilya Alexandrov, Theodore Maass, Peter Nikolenko, Sergey I. MALDI imaging mass spectrometry hyperspectral image segmentation probabilistic graphical models latent Dirichlet allocation Markov random field 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. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Ilya Chernyavsky and Theodore Alexandrov and Peter Maass and Sergey I. Nikolenko 2012 Is Part Of OASIcs, Volume 26, German Conference on Bioinformatics 2012 InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.GCB.2012.39 urn:nbn:de:0030-drops-37163 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.GCB.2012.39 eng https://creativecommons.org/licenses/by-nd/3.0/legalcode