Browse
Submit Data
Databases
API
Help

Dataset Information

18 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Noise-robust phase-space deconvolution for light-field microscopy.

ABSTRACT:

Significance

Light-field microscopy has achieved success in various applications of life sciences that require high-speed volumetric imaging. However, existing light-field reconstruction algorithms degrade severely in low-light conditions, and the deconvolution process is time-consuming.

Aim

This study aims to develop a noise robustness phase-space deconvolution method with low computational costs.

Approach

We reformulate the light-field phase-space deconvolution model into the Fourier domain with random-subset ordering and total-variation (TV) regularization. Additionally, we build a time-division-based multicolor light-field microscopy and conduct the three-dimensional (3D) imaging of the heart beating in zebrafish larva at over 95 Hz with a low light dose.

Results

We demonstrate that this approach reduces computational resources, brings a tenfold speedup, and achieves a tenfold improvement for the noise robustness in terms of SSIM over the state-of-the-art approach.

Conclusions

We proposed a phase-space deconvolution algorithm for 3D reconstructions in fluorescence imaging. Compared with the state-of-the-art method, we show significant improvement in both computational effectiveness and noise robustness; we further demonstrated practical application on zebrafish larva with low exposure and low light dose.

SUBMITTER: Zhu T

PROVIDER: S-EPMC9319196 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

DiLFM: an artifact-suppressed and noise-robust light-field microscopy through dictionary learning.

Project description:Light field microscopy (LFM) has been widely used for recording 3D biological dynamics at camera frame rate. However, LFM suffers from artifact contaminations due to the illness of the reconstruction problem via naïve Richardson-Lucy (RL) deconvolution. Moreover, the performance of LFM significantly dropped in low-light conditions due to the absence of sample priors. In this paper, we thoroughly analyze different kinds of artifacts and present a new LFM technique termed dictionary LFM (DiLFM) that substantially suppresses various kinds of reconstruction artifacts and improves the noise robustness with an over-complete dictionary. We demonstrate artifact-suppressed reconstructions in scattering samples such as Drosophila embryos and brains. Furthermore, we show our DiLFM can achieve robust blood cell counting in noisy conditions by imaging blood cell dynamic at 100 Hz and unveil more neurons in whole-brain calcium recording of zebrafish with low illumination power in vivo.

| S-EPMC8316327 | biostudies-literature

Direct imaging of phase objects enables conventional deconvolution in bright field light microscopy.

Project description:In transmitted optical microscopy, absorption structure and phase structure of the specimen determine the three-dimensional intensity distribution of the image. The elementary impulse responses of the bright field microscope therefore consist of separate absorptive and phase components, precluding general application of linear, conventional deconvolution processing methods to improve image contrast and resolution. However, conventional deconvolution can be applied in the case of pure phase (or pure absorptive) objects if the corresponding phase (or absorptive) impulse responses of the microscope are known. In this work, we present direct measurements of the phase point- and line-spread functions of a high-aperture microscope operating in transmitted bright field. Polystyrene nanoparticles and microtubules (biological polymer filaments) serve as the pure phase point and line objects, respectively, that are imaged with high contrast and low noise using standard microscopy plus digital image processing. Our experimental results agree with a proposed model for the response functions, and confirm previous theoretical predictions. Finally, we use the measured phase point-spread function to apply conventional deconvolution on the bright field images of living, unstained bacteria, resulting in improved definition of cell boundaries and sub-cellular features. These developments demonstrate practical application of standard restoration methods to improve imaging of phase objects such as cells in transmitted light microscopy.

| S-EPMC3928359 | biostudies-literature

Deconvolution of light sheet microscopy recordings.

Project description:We developed a deconvolution software for light sheet microscopy that uses a theoretical point spread function, which we derived from a model of image formation in a light sheet microscope. We show that this approach provides excellent blur reduction and enhancement of fine image details for image stacks recorded with low magnification objectives of relatively high NA and high field numbers as e.g. 2x NA 0.14 FN 22, or 4x NA 0.28 FN 22. For these objectives, which are widely used in light sheet microscopy, sufficiently resolved point spread functions that are suitable for deconvolution are difficult to measure and the results obtained by common deconvolution software developed for confocal microscopy are usually poor. We demonstrate that the deconvolutions computed using our point spread function model are equivalent to those obtained using a measured point spread function for a 10x objective with NA 0.3 and for a 20x objective with NA 0.45.

| S-EPMC6879637 | biostudies-literature

Calibration of wide-field deconvolution microscopy for quantitative fluorescence imaging.

Project description:Deconvolution enhances contrast in fluorescence microscopy images, especially in low-contrast, high-background wide-field microscope images, improving characterization of features within the sample. Deconvolution can also be combined with other imaging modalities, such as confocal microscopy, and most software programs seek to improve resolution as well as contrast. Quantitative image analyses require instrument calibration and with deconvolution, necessitate that this process itself preserves the relative quantitative relationships between fluorescence intensities. To ensure that the quantitative nature of the data remains unaltered, deconvolution algorithms need to be tested thoroughly. This study investigated whether the deconvolution algorithms in AutoQuant X3 preserve relative quantitative intensity data. InSpeck Green calibration microspheres were prepared for imaging, z-stacks were collected using a wide-field microscope, and the images were deconvolved using the iterative deconvolution algorithms with default settings. Afterwards, the mean intensities and volumes of microspheres in the original and the deconvolved images were measured. Deconvolved data sets showed higher average microsphere intensities and smaller volumes than the original wide-field data sets. In original and deconvolved data sets, intensity means showed linear relationships with the relative microsphere intensities given by the manufacturer. Importantly, upon normalization, the trend lines were found to have similar slopes. In original and deconvolved images, the volumes of the microspheres were quite uniform for all relative microsphere intensities. We were able to show that AutoQuant X3 deconvolution software data are quantitative. In general, the protocol presented can be used to calibrate any fluorescence microscope or image processing and analysis procedure.

| S-EPMC3942261 | biostudies-literature

Deconvolution-free Subcellular Imaging with Axially Swept Light Sheet Microscopy.

Project description:The use of propagation invariant Bessel beams has enabled high-resolution subcellular light sheet fluorescence microscopy. However, the energy within the concentric side lobe structure of Bessel beams increases significantly with propagation length, generating unwanted out-of-focus fluorescence that enforces practical limits on the imaging field of view size. Here, we present a light sheet fluorescence microscope that achieves 390 nm isotropic resolution and high optical sectioning strength (i.e., out-of-focus blur is strongly suppressed) over large field of views, without the need for structured illumination or deconvolution-based postprocessing. We demonstrate simultaneous dual-color, high-contrast, and high-dynamic-range time-lapse imaging of migrating cells in complex three-dimensional microenvironments, three-dimensional tracking of clathrin-coated pits, and long-term imaging spanning >10 h and encompassing >2600 time points.

| S-EPMC4472079 | biostudies-literature

Blind Depth-variant Deconvolution of 3D Data in Wide-field Fluorescence Microscopy.

Project description:This paper proposes a new deconvolution method for 3D fluorescence wide-field microscopy. Most previous methods are insufficient in terms of restoring a 3D cell structure, since a point spread function (PSF) is simply assumed as depth-invariant, whereas a PSF of microscopy changes significantly along the optical axis. A few methods that consider a depth-variant PSF have been proposed; however, they are impractical, since they are non-blind approaches that use a known PSF in a pre-measuring condition, whereas an imaging condition of a target image is different from that of the pre-measuring. To solve these problems, this paper proposes a blind approach to estimate depth-variant specimen-dependent PSF and restore 3D cell structure. It is shown by experiments on that the proposed method outperforms the previous ones in terms of suppressing axial blur. The proposed method is composed of the following three steps: First, a non-parametric averaged PSF is estimated by the Richardson Lucy algorithm, whose initial parameter is given by the central depth prediction from intensity analysis. Second, the estimated PSF is fitted to Gibson's parametric PSF model via optimization, and depth-variant PSFs are generated. Third, a 3D cell structure is restored by using a depth-variant version of a generalized expectation-maximization.

| S-EPMC5155489 | biostudies-literature

Camera array based light field microscopy.

Project description:This paper proposes a novel approach for high-resolution light field microscopy imaging by using a camera array. In this approach, we apply a two-stage relay system for expanding the aperture plane of the microscope into the size of an imaging lens array, and utilize a sensor array for acquiring different sub-apertures images formed by corresponding imaging lenses. By combining the rectified and synchronized images from 5 × 5 viewpoints with our prototype system, we successfully recovered color light field videos for various fast-moving microscopic specimens with a spatial resolution of 0.79 megapixels at 30 frames per second, corresponding to an unprecedented data throughput of 562.5 MB/s for light field microscopy. We also demonstrated the use of the reported platform for different applications, including post-capture refocusing, phase reconstruction, 3D imaging, and optical metrology.

| S-EPMC4574646 | biostudies-other

Cell imaging beyond the diffraction limit using sparse deconvolution spatial light interference microscopy.

Project description:We present an imaging method, dSLIM, that combines a novel deconvolution algorithm with spatial light interference microscopy (SLIM), to achieve 2.3x resolution enhancement with respect to the diffraction limit. By exploiting the sparsity of the phase images, which is prominent in many biological imaging applications, and modeling of the image formation via complex fields, the very fine structures can be recovered which were blurred by the optics. With experiments on SLIM images, we demonstrate that significant improvements in spatial resolution can be obtained by the proposed approach. Moreover, the resolution improvement leads to higher accuracy in monitoring dynamic activity over time. Experiments with primary brain cells, i.e. neurons and glial cells, reveal new subdiffraction structures and motions. This new information can be used for studying vesicle transport in neurons, which may shed light on dynamic cell functioning. Finally, the method is flexible to incorporate a wide range of image models for different applications and can be utilized for all imaging modalities acquiring complex field images.

| S-EPMC3130569 | biostudies-other

Fluorescence microscopy image noise reduction using a stochastically-connected random field model.

Project description:Fluorescence microscopy is an essential part of a biologist's toolkit, allowing assaying of many parameters like subcellular localization of proteins, changes in cytoskeletal dynamics, protein-protein interactions, and the concentration of specific cellular ions. A fundamental challenge with using fluorescence microscopy is the presence of noise. This study introduces a novel approach to reducing noise in fluorescence microscopy images. The noise reduction problem is posed as a Maximum A Posteriori estimation problem, and solved using a novel random field model called stochastically-connected random field (SRF), which combines random graph and field theory. Experimental results using synthetic and real fluorescence microscopy data show the proposed approach achieving strong noise reduction performance when compared to several other noise reduction algorithms, using quantitative metrics. The proposed SRF approach was able to achieve strong performance in terms of signal-to-noise ratio in the synthetic results, high signal to noise ratio and contrast to noise ratio in the real fluorescence microscopy data results, and was able to maintain cell structure and subtle details while reducing background and intra-cellular noise.

| S-EPMC4756687 | biostudies-literature

Scattering-type scanning near-field optical microscopy with low-repetition-rate pulsed light source through phase-domain sampling.

Project description:Scattering-type scanning near-field optical microscopy (s-SNOM) allows spectroscopic imaging with spatial resolution below the diffraction limit. With suitable light sources, s-SNOM is instrumental in numerous discoveries at the nanoscale. So far, the light sources have been limited to continuous wave or high-repetition-rate pulsed lasers. Low-repetition-rate pulsed sources cannot be used, due to the limitation of the lock-in detection mechanism that is required for current s-SNOM techniques. Here, we report a near-field signal extraction method that enables low-repetition-rate pulsed light sources. The method correlates scattering signals from pulses with the mechanical phases of the oscillating s-SNOM probe to obtain near-field signal, by-passing the apparent restriction imposed by the Nyquist-Shannon sampling theorem on the repetition rate. The method shall enable s-SNOM with low-repetition-rate pulses with high-peak-powers, such as femtosecond laser amplifiers, to facilitate investigations of strong light-matter interactions and nonlinear processes at the nanoscale.

| S-EPMC5071641 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data