Strategies for MCR image analysis of large hyperspectral data-sets

Scurr, David J. and Hook, Andrew L. and Burley, Jonathan and Williams, Philip M. and Anderson, Daniel G. and Langer, Robert and Davies, Martyn C. and Alexander, Morgan R. (2012) Strategies for MCR image analysis of large hyperspectral data-sets. Surface and Interface Analysis, 45 (1). pp. 466-470. ISSN 0142-2421

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Abstract

Polymer microarrays are a key enabling technology for high throughput materials discovery. In this study, multivariate image analysis, specifically multivariate curve resolution (MCR), is applied to the hyperspectral time of flight secondary ion mass spectroscopy (ToF-SIMS) data from eight individual microarray spots. Rather than analysing the data individually, the data-sets are collated and analysed as a single large data-set. Desktop computing is not a practical method for undertaking MCR analysis of such large data-sets due to the constraints of memory and computational overhead. Here, a distributed memory High-Performance Computing facility (HPC) is used. Similar to what is achieved using MCR analysis of individual samples, the results from this consolidated data-set allow clear identification of the substrate material; furthermore, specific chemistries common to different spots are also identified. The application of the HPC facility to the MCR analysis of ToF-SIMS hyperspectral data-sets demonstrates a potential methodology for the analysis of macro-scale data without compromising spatial resolution (data ‘binning’)

Item Type: Article
Additional Information: This is the accepted version of the following article: Scurr, D. J., Hook, A. L., Burley, J., Williams, P. M., Anderson, D. G., Langer, R., Davies, M. C. and Alexander, M. R. (2013), Strategies for MCR image analysis of large hyperspectral data-sets. Surf. Interface Anal., 45: 466–470. doi: 10.1002/sia.5040 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/sia.5040/full
Keywords: Time-of-flight secondary ion mass spectrometry, Multivariate curve resolution, Microarray, High-performance computing
Schools/Departments: University of Nottingham UK Campus > Faculty of Science > School of Pharmacy
Identification Number: https://doi.org/10.1002/sia.5040
Depositing User: Chamberlain, Mr Dick
Date Deposited: 12 May 2014 09:42
Last Modified: 15 Sep 2016 06:19
URI: http://eprints.nottingham.ac.uk/id/eprint/3134

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