Dataset Information

One-shot phase-recovery using a cellphone RGB camera on a Jamin-Lebedeff microscope.

ABSTRACT: Jamin-Lebedeff (JL) polarization interference microscopy is a classical method for determining the change in the optical path of transparent tissues. Whilst a differential interference contrast (DIC) microscopy interferes an image with itself shifted by half a point spread function, the shear between the object and reference image in a JL-microscope is about half the field of view. The optical path difference (OPD) between the sample and reference region (assumed to be empty) is encoded into a color by white-light interference. From a color-table, the Michel-Levy chart, the OPD can be deduced. In cytology JL-imaging can be used as a way to determine the OPD which closely corresponds to the dry mass per area of cells in a single image. Like in other interference microscopy methods (e.g. holography), we present a phase retrieval method relying on single-shot measurements only, thus allowing real-time quantitative phase measurements. This is achieved by adding several customized 3D-printed parts (e.g. rotational polarization-filter holders) and a modern cellphone with an RGB-camera to the Jamin-Lebedeff setup, thus bringing an old microscope back to life. The algorithm is calibrated using a reference image of a known phase object (e.g. optical fiber). A gradient-descent based inverse problem generates an inverse look-up-table (LUT) which is used to convert the measured RGB signal of a phase-sample into an OPD. To account for possible ambiguities in the phase-map or phase-unwrapping artifacts we introduce a total-variation based regularization. We present results from fixed and living biological samples as well as reference samples for comparison.

SUBMITTER: Diederich B

PROVIDER: S-EPMC6938357 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Publications

One-shot phase-recovery using a cellphone RGB camera on a Jamin-Lebedeff microscope.

Diederich Benedict B Marsikova Barbora B Amos Brad B Heintzmann Rainer R

PloS one 20191231 12

Jamin-Lebedeff (JL) polarization interference microscopy is a classical method for determining the change in the optical path of transparent tissues. Whilst a differential interference contrast (DIC) microscopy interferes an image with itself shifted by half a point spread function, the shear between the object and reference image in a JL-microscope is about half the field of view. The optical path difference (OPD) between the sample and reference region (assumed to be empty) is encoded into a c ...[more]

PMID: 31891618

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Project description:Plant canopy structure can strongly affect crop functions such as yield and stress tolerance, and canopy size is an important aspect of canopy structure. Manual assessment of canopy size is laborious and imprecise, and cannot measure multi-dimensional traits such as projected leaf area and canopy volume. Field-based high throughput phenotyping systems with imaging capabilities can rapidly acquire data about plants in field conditions, making it possible to quantify and monitor plant canopy development. The goal of this study was to develop a 3D imaging approach to quantitatively analyze cotton canopy development in field conditions. A cotton field was planted with 128 plots, including four genotypes of 32 plots each. The field was scanned by GPhenoVision (a customized field-based high throughput phenotyping system) to acquire color and depth images with GPS information in 2016 covering two growth stages: canopy development, and flowering and boll development. A data processing pipeline was developed, consisting of three steps: plot point cloud reconstruction, plant canopy segmentation, and trait extraction. Plot point clouds were reconstructed using color and depth images with GPS information. In colorized point clouds, vegetation was segmented from the background using an excess-green (ExG) color filter, and cotton canopies were further separated from weeds based on height, size, and position information. Static morphological traits were extracted on each day, including univariate traits (maximum and mean canopy height and width, projected canopy area, and concave and convex volumes) and a multivariate trait (cumulative height profile). Growth rates were calculated for univariate static traits, quantifying canopy growth and development. Linear regressions were performed between the traits and fiber yield to identify the best traits and measurement time for yield prediction. The results showed that fiber yield was correlated with static traits after the canopy development stage (R2 = 0.35-0.71) and growth rates in early canopy development stages (R2 = 0.29-0.52). Multi-dimensional traits (e.g., projected canopy area and volume) outperformed one-dimensional traits, and the multivariate trait (cumulative height profile) outperformed univariate traits. The proposed approach would be useful for identification of quantitative trait loci (QTLs) controlling canopy size in genetics/genomics studies or for fiber yield prediction in breeding programs and production environments.

Dataset Information

One-shot phase-recovery using a cellphone RGB camera on a Jamin-Lebedeff microscope.

Publications

One-shot phase-recovery using a cellphone RGB camera on a Jamin-Lebedeff microscope.

Similar Datasets

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