21 February 2017 Sparsely-sampled hyperspectral stimulated Raman scattering microscopy: a theoretical investigation
Author Affiliations +
A hyperspectral image corresponds to a data cube with two spatial dimensions and one spectral dimension. Through linear un-mixing, hyperspectral images can be decomposed into spectral signatures of pure components as well as their concentration maps. Due to this distinct advantage on component identification, hyperspectral imaging becomes a rapidly emerging platform for engineering better medicine and expediting scientific discovery. Among various hyperspectral imaging techniques, hyperspectral stimulated Raman scattering (HSRS) microscopy acquires data in a pixel-by-pixel scanning manner. Nevertheless, current image acquisition speed for HSRS is insufficient to capture the dynamics of freely moving subjects. Instead of reducing the pixel dwell time to achieve speed-up, which would inevitably decrease signal-to-noise ratio (SNR), we propose to reduce the total number of sampled pixels. Location of sampled pixels are carefully engineered with triangular wave Lissajous trajectory. Followed by a model-based image in-painting algorithm, the complete data is recovered for linear unmixing. Simulation results show that by careful selection of trajectory, a fill rate as low as 10% is sufficient to generate accurate linear unmixing results. The proposed framework applies to any hyperspectral beam-scanning imaging platform which demands high acquisition speed.
Conference Presentation
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Haonan Lin, Haonan Lin, Chien-Sheng Liao, Chien-Sheng Liao, Pu Wang, Pu Wang, Kai-Chih Huang, Kai-Chih Huang, Charles A. Bouman, Charles A. Bouman, Nan Kong, Nan Kong, Ji-Xin Cheng, Ji-Xin Cheng, } "Sparsely-sampled hyperspectral stimulated Raman scattering microscopy: a theoretical investigation", Proc. SPIE 10069, Multiphoton Microscopy in the Biomedical Sciences XVII, 1006912 (21 February 2017); doi: 10.1117/12.2256936; https://doi.org/10.1117/12.2256936

Back to Top