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An efficient TOF-SIMS image analysis with spatial correlation and alternating non–negativity-constrained least squares
Author(s) -
Parham Aram,
Lingli Shen,
John Pugh,
Seetharaman Vaidyanathan,
Visakan Kadirkamanathan
Publication year - 2014
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btu734
Subject(s) - computer science , image resolution , least squares function approximation , sample (material) , image (mathematics) , resolution (logic) , spatial analysis , data mining , artificial intelligence , algorithm , pattern recognition (psychology) , mathematics , statistics , chemistry , chromatography , estimator
Advances in analytical instrumentation towards acquiring high-resolution images of mass spectrometry constantly demand efficient approaches for data analysis. This is particularly true of time-of-flight secondary ion mass spectrometry imaging where recent advances enable acquisition of high-resolution data in multiple dimensions. In many applications, the distribution of different species from a sampled surface is spatially continuous in nature and a model that incorporates the spatial correlation across the surface would be preferable to estimations at discrete spatial locations. A key challenge here is the capability to analyse the high-resolution multidimensional data to extract relevant information reliably and efficiently.

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