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Diffraction Tomography from Single-Molecule Localization Microscopy: Numerical Feasibility

Thanh-An Michel Pham, Emmanuel Emilien Louis Soubies, Ferréol Arnaud Marie Soulez, Michaël Unser

Single-molecule localization microscopy (SMLM) is a fluorescence microscopy technique that achieves super-resolution imaging by sequentially activating and localizing random sparse subsets of fluorophores. Each activated fluorophore emits light that then scatters through the sample, thus acting as a source of illumination from inside the sample. Hence, the sequence of SMLM frames carries information on the distribution of the refractive index of the sample. In this proof-of-concept work, we explore the possibility of exploiting this information to recover the refractive index of the imaged sample, given the localized molecules. Our results with simulated data suggest that it is possible to exploit the phase information that underlies the SMLM data.

IEEE2021

Optical diffraction tomography from single-molecule localization microscopy

Thanh-An Michel Pham, Emmanuel Emilien Louis Soubies, Ferréol Arnaud Marie Soulez, Michaël Unser

Single-molecule localization microscopy (SMLM) is a powerful method for the imaging of cellular structures. This modality delivers nanoscale resolution by sequentially activating a subset of fluorescent molecules and by extracting their super-resolved positions from the microscope images. The emission patterns of individual molecules can be distorted by the refractive-index (RI) map of the sample, which reduces the accuracy of the molecule localization if not accounted for. In this work, we show that one can exploit those sample-induced aberrations to reveal the structural information of the specimen. Our work is related to the optical diffraction tomography in that we aim to recover the RI map. To that end, we propose an optimization framework in which we reconstruct the RI map and optimize the positions of the molecules in a joint fashion. The benefits of our method are twofold. On one side, we effectively recover the RI map of the sample. On the other side, we further improve the molecule localization—the primary purpose of SMLM. We validate our joint-optimization framework on simulated data. Our results lay the foundation of an exciting and novel extension of SMLM.

2021

Pocket guide to solve inverse problems with GlobalBioIm

Thomas Jean Debarre, Laurène Donati, Michael Thompson McCann, Thanh-An Michel Pham, Daniel Sage, Emmanuel Emilien Louis Soubies, Ferréol Arnaud Marie Soulez, Michaël Unser

GlobalBioIm is an open-source MATLAB (R) library for solving inverse problems. The library capitalizes on the strong commonalities between forward models to standardize the resolution of a wide range of imaging inverse problems. Endowed with an operator-algebra mechanism, GlobalBioIm allows one to easily solve inverse problems by combining elementary modules in a lego-like fashion. This user-friendly toolbox gives access to cutting-edge reconstruction algorithms, while its high modularity makes it easily extensible to new modalities and novel reconstruction methods. We expect GlobalBioIm to respond to the needs of imaging scientists looking for reliable and easy-to-use computational tools for solving their inverse problems. In this paper, we present in detail the structure and main features of the library. We also illustrate its flexibility with examples from multichannel deconvolution microscopy.

IOP PUBLISHING LTD2019