Segmentation of Multi-Isotope Imaging Mass Spectrometry Data for Semi-Automatic Detection of Regions of Interest

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Segmentation of Multi-Isotope Imaging Mass Spectrometry Data for Semi-Automatic Detection of Regions of Interest

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Title: Segmentation of Multi-Isotope Imaging Mass Spectrometry Data for Semi-Automatic Detection of Regions of Interest
Author: Gormanns, Philipp; Reckow, Stefan; Poczatek, J. Collin; Turck, Christoph W.; Lechene, Claude P.

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Citation: Gormanns, Philipp, Stefan Reckow, J. Collin Poczatek, Christoph W. Turck, and Claude Lechene. 2012. Segmentation of multi-isotope imaging mass spectrometry data for semi-automatic detection of regions of interest. PLoS ONE 7(2): e30576.
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Abstract: Multi-isotope imaging mass spectrometry (MIMS) associates secondary ion mass spectrometry (SIMS) with detection of several atomic masses, the use of stable isotopes as labels, and affiliated quantitative image-analysis software. By associating image and measure, MIMS allows one to obtain quantitative information about biological processes in sub-cellular domains. MIMS can be applied to a wide range of biomedical problems, in particular metabolism and cell fate. In order to obtain morphologically pertinent data from MIMS images, we have to define regions of interest (ROIs). ROIs are drawn by hand, a tedious and time-consuming process. We have developed and successfully applied a support vector machine (SVM) for segmentation of MIMS images that allows fast, semi-automatic boundary detection of regions of interests. Using the SVM, high-quality ROIs (as compared to an expert's manual delineation) were obtained for 2 types of images derived from unrelated data sets. This automation simplifies, accelerates and improves the post-processing analysis of MIMS images. This approach has been integrated into “Open MIMS,” an ImageJ-plugin for comprehensive analysis of MIMS images that is available online at http://www.nrims.hms.harvard.edu/NRIMS_ImageJ.php.
Published Version: doi:10.1371/journal.pone.0030576
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3276494/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:9361513

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