Hyperspectral fluorescence microscopy based on compressed sensing

Vincent Studer; Jérome Bobin; Makhlad Chahid; Hamed Mousavi; Emmanuel Candes; Maxime Dahan

doi:10.1117/12.908532

2 February 2012 Hyperspectral fluorescence microscopy based on compressed sensing

Vincent Studer, Jérome Bobin, Makhlad Chahid, Hamed Mousavi, Emmanuel Candes, Maxime Dahan

Proceedings Volume 8227, Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XIX; 82270D (2012) https://doi.org/10.1117/12.908532
Event: SPIE BiOS, 2012, San Francisco, California, United States

Abstract

In fluorescence microscopy, one can distinguish two kinds of imaging approaches, wide field and raster scan microscopy, differing by their excitation and detection scheme. In both imaging modalities the acquisition is independent of the information content of the image. Rather, the number of acquisitions N, is imposed by the Nyquist-Shannon theorem. However, in practice, many biological images are compressible (or, equivalently here, sparse), meaning that they depend on a number of degrees of freedom K that is smaller that their size N. Recently, the mathematical theory of compressed sensing (CS) has shown how the sensing modality could take advantage of the image sparsity to reconstruct images with no loss of information while largely reducing the number M of acquisition. Here we present a novel fluorescence microscope designed along the principles of CS. It uses a spatial light modulator (DMD) to create structured wide field excitation patterns and a sensitive point detector to measure the emitted fluorescence. On sparse fluorescent samples, we could achieve compression ratio N/M of up to 64, meaning that an image can be reconstructed with a number of measurements of only 1.5 % of its pixel number. Furthemore, we extend our CS acquisition scheme to an hyperspectral imaging system.

Citation Download Citation

Vincent Studer, Jérome Bobin, Makhlad Chahid, Hamed Mousavi, Emmanuel Candes, and Maxime Dahan "Hyperspectral fluorescence microscopy based on compressed sensing", Proc. SPIE 8227, Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XIX, 82270D (2 February 2012); https://doi.org/10.1117/12.908532

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