Estimating missing information by maximum likelihood deconvolution

Heintzmann, Rainer

doi:10.1016/j.micron.2006.07.009

Cited by 32 publications

(28 citation statements)

References 17 publications

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“…1(c,iv) and Fig. 1(c,v), the deconvolution makes the already recognized regions more distinct and the reconstructed spokes thinner, which validates the frequency-lifting ability of the RL deconvolution method [29]. Apparently, NFOMM achieves subtler details without the mal-positioning issue, confirming the superiority of this nonlinear modulation method.…”

Section: Textsupporting

confidence: 59%

Nonlinear Focal Modulation Microscopy

et al. 2018

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We demonstrate nonlinear focal modulation microscopy (NFOMM) to achieve superresolution imaging. Traditional approaches to superresolution that utilize point scanning often rely on spatially reducing the size of the emission pattern by directly narrowing (e.g., through minimizing the detection pinhole in Airyscan, Zeiss) or indirectly peeling its outer profiles [e.g., through depleting the outer emission region in stimulated emission depletion (STED) microscopy]. We show that an alternative conceptualization that focuses on maximizing the optical system's frequency shifting ability offers advantages in further improving resolution while reducing system complexity. In NFOMM, a spatial light modulator and a suitably intense laser illumination are used to implement nonlinear focal-field modulation to achieve a transverse spatial resolution of ∼60 nm (∼λ/10). We show that NFOMM is comparable with STED microscopy and suitable for fundamental biology studies, as evidenced in imaging nuclear pore complexes, tubulin and vimentin in Vero cells. Since NFOMM is readily implemented as an add-on module to a laser-scanning microscope, we anticipate wide utility of this new imaging technique.

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Section: Textsupporting

confidence: 59%

Nonlinear Focal Modulation Microscopy

et al. 2018

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“…As a result, the measurement matrix H is rank deficient and the inverse problem is underdetermined. Fortunately, the Richardson-Lucy algorithm favors sparse solutions to the inverse problem [22], and we believe that this provides a degree of regularization that allows it to produce reasonable volumes even in this underdetermined case. However, reconstructing this many voxels may not be necessary or efficient.…”

Section: Reconstruction Of a 3-d Specimenmentioning

confidence: 99%

Wave optics theory and 3-D deconvolution for the light field microscope

et al. 2013

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Abstract:Light field microscopy is a new technique for high-speed volumetric imaging of weakly scattering or fluorescent specimens. It employs an array of microlenses to trade off spatial resolution against angular resolution, thereby allowing a 4-D light field to be captured using a single photographic exposure without the need for scanning. The recorded light field can then be used to computationally reconstruct a full volume. In this paper, we present an optical model for light field microscopy based on wave optics, instead of previously reported ray optics models. We also present a 3-D deconvolution method for light field microscopy that is able to reconstruct volumes at higher spatial resolution, and with better optical sectioning, than previously reported. To accomplish this, we take advantage of the dense spatio-angular sampling provided by a microlens array at axial positions away from the native object plane. This dense sampling permits us to decode aliasing present in the light field to reconstruct high-frequency information. We formulate our method as an inverse problem for reconstructing the 3-D volume, which we solve using a GPU-accelerated iterative algorithm. Theoretical limits on the depth-dependent lateral resolution of the reconstructed volumes are derived. We show that these limits are in good agreement with experimental results on a standard USAF 1951 resolution target. Finally, we present 3-D reconstructions of pollen grains that demonstrate the improvements in fidelity made possible by our method.

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“…Additional prior knowledge, such as the emitted signal being positive, enables deconvolution algorithms to “guess” details beyond Abbe’s limit. However, the obtained improvement depends on the studied object with best results for sparse objects such as filaments or vesicles (Heintzmann, 2007) and little improvement for other objects.…”

Section: Classical Ways To Enhance the Resolution Of Light Microscopymentioning

confidence: 99%

A guide to super-resolution fluorescence microscopy

Schermelleh

Heintzmann

Leonhardt

2010

Journal of Cell Biology

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1,175

901

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For centuries, cell biology has been based on light microscopy and at the same time been limited by its optical resolution. However, several new technologies have been developed recently that bypass this limit. These new super-resolution technologies are either based on tailored illumination, nonlinear fluorophore responses, or the precise localization of single molecules. Overall, these new approaches have created unprecedented new possibilities to investigate the structure and function of cells.

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Estimating missing information by maximum likelihood deconvolution

Cited by 32 publications

References 17 publications

Nonlinear Focal Modulation Microscopy

Nonlinear Focal Modulation Microscopy

Wave optics theory and 3-D deconvolution for the light field microscope

A guide to super-resolution fluorescence microscopy

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