Strategies for MCR image analysis of large hyperspectral data-setsTools Scurr, David J., Hook, Andrew L., Burley, Jonathan, Williams, Philip M., Anderson, Daniel G., Langer, Robert, 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 Full text not available from this repository.
Official URL: http://onlinelibrary.wiley.com/doi/10.1002/sia.5040/full
AbstractPolymer 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’)
Actions (Archive Staff Only)
|
Tools
Tools
