Random-subset fitting of digital holograms for fast three-dimensional particle tracking [Invited]

Dimiduk, Thomas G.; Perry, Rebecca W.; Fung, Jerome; Manoharan, Vinothan N.

doi:10.1364/ao.53.00g177

Cited by 16 publications

(33 citation statements)

References 29 publications

(42 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…for x = x j . Summing over j, this implies that formula (13) for the adjoint holds pointwise as long as we do not reach the screen where the hologram is recorded.…”

Section: Discussionmentioning

confidence: 99%

“…The dimensionless wavenumbers are ke = 16.07 and ki = 19.33. Slice y = 0 of (b) the topological derivative computed using expression (10) with forward and adjoint fields given by (11)-(13), and (c) the scalar approximation of the topological derivative in A. The blue contour represents the true object, while the lighter magenta contour represents an approximation using the topological derivative.…”

mentioning

confidence: 99%

See 1 more Smart Citation

When topological derivatives met regularized Gauss-Newton iterations in holographic 3D imaging

Carpio

Dimiduk

Louër

et al. 2019

Journal of Computational Physics

Self Cite

View full text Add to dashboard Cite

We propose an automatic algorithm for 3D inverse electromagnetic scattering based on the combination of topological derivatives and regularized Gauss-Newton iterations. The algorithm is adapted to decoding digital holograms. A hologram is a two-dimensional light interference pattern that encodes information about three-dimensional shapes and their optical properties. The formation of the hologram is modeled using Maxwell theory for light scattering by particles. We then seek shapes optimizing error functionals which measure the deviation from the recorded holograms. Their topological derivatives provide initial guesses of the objects. Next, we correct these predictions by regularized Gauss-Newton techniques. In contrast to standard Gauss-Newton methods, in our implementation the number of objects can be automatically updated during the iterative procedure by new topological derivative computations. We show that the combined use of topological derivative based optimization and iteratively regularized Gauss-Newton methods produces fast and accurate descriptions of the geometry of objects formed by multiple components with nanoscale resolution, even for a small number of detectors and non convex components aligned in the incidence direction. The method could be applied in general imaging set-ups involving other waves (microwave imaging, elastography...) provided closed-form expressions for the topological and Fréchet derivatives are determined.

show abstract

“…for x = x j . Summing over j, this implies that formula (13) for the adjoint holds pointwise as long as we do not reach the screen where the hologram is recorded.…”

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

When topological derivatives met regularized Gauss-Newton iterations in holographic 3D imaging

Carpio

Dimiduk

Louër

et al. 2019

Journal of Computational Physics

Self Cite

View full text Add to dashboard Cite

show abstract

“…Therefore, formula (13) provides a first approximation to the objects without knowing their optical properties beforehand. For biological samples β ∼ 1 and the gradient Evaluate the analytical expression (12) for the topological energy ET with (9,11) Record the hologram Fit objects (13) to the most relevant peaks of ET Fig. 6.…”

mentioning

confidence: 99%

“…Consider the configurations with multiple balls along the z axis in Figure 4(d). Using expression (13) we define an approximation Ω (0) to the scatterers. We may take…”

mentioning

confidence: 99%

Optimization Methods for In-Line Holography

Carpio¹,

Dimiduk²,

Selgás³

et al. 2018

SIAM J. Imaging Sci.

View full text Add to dashboard Cite

We present a procedure to reconstruct objects from holograms recorded in in-line holography settings. Working with one beam of polarized light, the topological derivatives and energies of functionals quantifying hologram deviations yield predictions of the number, location, shape and size of objects with nanometer resolution. When the permittivity of the objects is unknown, we approximate it by parameter optimization techniques. Iterative procedures combining topological field based geometry corrections and parameter optimization sharpen the initial predictions. Additionally, we devise a strategy which exploits the measured holograms to produce numerical approximations of the full electric field (amplitude and phase) at the screen where the hologram is recorded. Shape and parameter optimization of functionals employing such approximations of the electric field also yield images of the holographied objects.

show abstract

“…It considers a background subtracted hologram, experimental parameters including distances and light source wavelengths and then reconstructs the hologram using two Fourier transforms. Alternatively, hologram fitting is provided by HoloPy where the position of a scatterer is simulated in order to produce the same interference pattern instead of image back-propagation [56]. For the case of a known number of scatterers, this method can be recommended as it allows to reconstruct spherical or cylindrical object shapes.…”

Section: Image Reconstructionmentioning

confidence: 99%

3D-printable portable open-source platform for low-cost lens-less holographic cellular imaging

Amann

Witzleben

Breuer

2019

Sci Rep

View full text Add to dashboard Cite

Digital holographic microscopy is an emerging, potentially low-cost alternative to conventional light microscopy for micro-object imaging on earth, underwater and in space. Immediate access to micron-scale objects however requires a well-balanced system design and sophisticated reconstruction algorithms, that are commercially available, however not accessible cost-efficiently. Here, we present an open-source implementation of a lens-less digital inline holographic microscope platform, based on off-the-shelf optical, electronic and mechanical components, costing less than $190. It employs a Blu-Ray semiconductor-laser-pickup or a light-emitting-diode, a pinhole, a 3D-printed housing consisting of 3 parts and a single-board portable computer and camera with an open-source implementation of the Fresnel-Kirchhoff routine. We demonstrate 1.55 μm spatial resolution by laser-pickup and 3.91 μm by the light-emitting-diode source. The housing and mechanical components are 3D printed. Both printer and reconstruction software source codes are open. The light-weight microscope allows to image label-free micro-spheres of 6.5 μm diameter, human red-blood-cells of about 8 μm diameter as well as fast-growing plant Nicotiana-tabacum-BY-2 suspension cells with 50 μm sizes. The imaging capability is validated by imaging-contrast quantification involving a standardized test target. The presented 3D-printable portable open-source platform represents a fully-open design, low-cost modular and versatile imaging-solution for use in high- and low-resource areas of the world.

show abstract

Random-subset fitting of digital holograms for fast three-dimensional particle tracking [Invited]

Cited by 16 publications

References 29 publications

When topological derivatives met regularized Gauss-Newton iterations in holographic 3D imaging

When topological derivatives met regularized Gauss-Newton iterations in holographic 3D imaging

Optimization Methods for In-Line Holography

3D-printable portable open-source platform for low-cost lens-less holographic cellular imaging

Contact Info

Product

Resources

About