DIC Microscopy Image Reconstruction Using a Novel Variational Framework

Koós, Krisztián; Molnár, J.; Horváth, Péter

doi:10.1109/dicta.2015.7371252

Cited by 4 publications

(2 citation statements)

References 13 publications

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“…To apply the gradient descent algorithm, the Euler-Lagrangian (EL) of the two terms in (5) and (6) have to be calculated. The complete derivation of the EL equations can be found in [14] and [15], but here we only describe and explain the final equations. The EL equation of the data term is very complex because of the local integrals introduced by the kernel function.…”

Section: Reconstruction Using a Variational Frameworkmentioning

confidence: 99%

Phase Measurement Using DIC Microscopy

2017

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The development of fluorescent probes and proteins has helped make light microscopy more popular by allowing the visualization of specific subcellular components, location and dynamics of biomolecules. However, it is not always feasible to label the cells as it may be phototoxic or perturb their functionalities. Label-free microscopy techniques allow us to work with live cells without perturbation and to evaluate morphological differences, which in turn can provide useful information for high-throughput assays. In this study, we use one of the most popular label-free techniques called differential interference contrast (DIC) microscopy to estimate the phase of cells and other nearly transparent objects and instantly estimate their height. DIC images provide detailed information about the optical path length (OPL) differences in the sample and they are visually similar to a gradient image. Our previous DIC construction algorithm outputs an image where the values are proportional to the OPL (or implicitly the phase) of the sample. Although the reconstructed images are capable of describing cellular morphology and to a certain extent turn DIC into a quantitative technique, the actual OPL has to be computed from the input DIC image and the microscope calibration settings. Here we propose a computational method to measure the phase and approximate height of cells after microscope calibration, assuming a linear formation model. After a calibration step the phase of further samples can be determined when the refractive indices of the sample and the surrounding medium is known. The precision of the method is demonstrated on reconstructing the thickness of known objects and real cellular samples.

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Section: Reconstruction Using a Variational Frameworkmentioning

confidence: 99%

Phase Measurement Using DIC Microscopy

2017

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“…First, we use a fast initialization heuristic and then refine the detection. The refinement step is the extension of our previous differential geometry-based method to 3 dimensions [46].…”

Section: Pipette Calibration and Automatic Detectionmentioning

confidence: 99%

Energy Minimization Algorithms for Image-Guided Automatic Patch Clamp Systems

Koós

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DIC image reconstruction using an energy minimization framework to visualize optical path length distribution

Koós

Molnár

Kelemen

et al. 2016

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Label-free microscopy techniques have numerous advantages such as low phototoxicity, simple setup and no need for fluorophores or other contrast materials. Despite their advantages, most label-free techniques cannot visualize specific cellular compartments or the location of proteins and the image formation limits quantitative evaluation. Differential interference contrast (DIC) is a qualitative microscopy technique that shows the optical path length differences within a specimen. We propose a variational framework for DIC image reconstruction. The proposed method largely outperforms state-of-the-art methods on synthetic, artificial and real tests and turns DIC microscopy into an automated high-content imaging tool. Image sets and the source code of the examined algorithms are made publicly available.

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DIC Microscopy Image Reconstruction Using a Novel Variational Framework

Cited by 4 publications

References 13 publications

Phase Measurement Using DIC Microscopy

Phase Measurement Using DIC Microscopy

Energy Minimization Algorithms for Image-Guided Automatic Patch Clamp Systems

DIC image reconstruction using an energy minimization framework to visualize optical path length distribution

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