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Dynamic Sparse Sampling for Confocal Raman Microscopy.

ABSTRACT: The total number of data points required for image generation in Raman microscopy was greatly reduced using sparse sampling strategies, in which the preceding set of measurements informed the next most information-rich sampling location. Using this approach, chemical images of pharmaceutical materials were obtained with >99% accuracy from 15.8% sampling, representing an ?6-fold reduction in measurement time relative to full field of view rastering with comparable image quality. This supervised learning approach to dynamic sampling (SLADS) has the distinct advantage of being directly compatible with standard confocal Raman instrumentation. Furthermore, SLADS is not limited to Raman imaging, potentially providing time-savings in image reconstruction whenever the single-pixel measurement time is the limiting factor in image generation.

SUBMITTER: Zhang S

PROVIDER: S-EPMC6025898 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Dynamic Sparse Sampling for Confocal Raman Microscopy.

Zhang Shijie S Song Zhengtian Z Godaliyadda G M Dilshan P GMDP Ye Dong Hye DH Chowdhury Azhad U AU Sengupta Atanu A Buzzard Gregery T GT Bouman Charles A CA Simpson Garth J GJ

Analytical chemistry 20180320 7

The total number of data points required for image generation in Raman microscopy was greatly reduced using sparse sampling strategies, in which the preceding set of measurements informed the next most information-rich sampling location. Using this approach, chemical images of pharmaceutical materials were obtained with >99% accuracy from 15.8% sampling, representing an ∼6-fold reduction in measurement time relative to full field of view rastering with comparable image quality. This supervised l ...[more]

PMID: 29521493

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