Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Label-free prediction of three-dimensional fluorescence images from transmitted-light microscopy.

ABSTRACT: Understanding cells as integrated systems is central to modern biology. Although fluorescence microscopy can resolve subcellular structure in living cells, it is expensive, is slow, and can damage cells. We present a label-free method for predicting three-dimensional fluorescence directly from transmitted-light images and demonstrate that it can be used to generate multi-structure, integrated images. The method can also predict immunofluorescence (IF) from electron micrograph (EM) inputs, extending the potential applications.

SUBMITTER: Ounkomol C

PROVIDER: S-EPMC6212323 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Label-free prediction of three-dimensional fluorescence images from transmitted-light microscopy.

Ounkomol Chawin C Seshamani Sharmishtaa S Maleckar Mary M MM Collman Forrest F Johnson Gregory R GR

Nature methods 20180917 11

Understanding cells as integrated systems is central to modern biology. Although fluorescence microscopy can resolve subcellular structure in living cells, it is expensive, is slow, and can damage cells. We present a label-free method for predicting three-dimensional fluorescence directly from transmitted-light images and demonstrate that it can be used to generate multi-structure, integrated images. The method can also predict immunofluorescence (IF) from electron micrograph (EM) inputs, extend ...[more]

PMID: 30224672

Similar Datasets

Photoimprint photoacoustic microscopy for three-dimensional label-free subdiffraction imaging.

Project description:Subdiffraction optical microscopy allows the imaging of cellular and subcellular structures with a resolution finer than the diffraction limit. Here, combining the absorption-based photoacoustic effect and intensity-dependent photobleaching effect, we demonstrate a simple method for subdiffraction photoacoustic imaging of both fluorescent and nonfluorescent samples. Our method is based on a double-excitation process, where the first excitation pulse partially and inhomogeneously bleaches the molecules in the diffraction-limited excitation volume, thus biasing the signal contributions from a second excitation pulse striking the same region. The differential signal between the two excitations preserves the signal contribution mostly from the center of the excitation volume, and dramatically sharpens the lateral resolution. Moreover, due to the nonlinear nature of the signal, our method offers an inherent optical sectioning capability, which is lacking in conventional photoacoustic microscopy. By scanning the excitation beam, we performed three-dimensional subdiffraction imaging of varied fluorescent and nonfluorescent species. As any molecules have absorption, this technique has the potential to enable label-free subdiffraction imaging, and can be transferred to other optical imaging modalities or combined with other subdiffraction methods.

| S-EPMC3957272 | biostudies-literature

NISNet3D: three-dimensional nuclear synthesis and instance segmentation for fluorescence microscopy images.

Project description:The primary step in tissue cytometry is the automated distinction of individual cells (segmentation). Since cell borders are seldom labeled, cells are generally segmented by their nuclei. While tools have been developed for segmenting nuclei in two dimensions, segmentation of nuclei in three-dimensional volumes remains a challenging task. The lack of effective methods for three-dimensional segmentation represents a bottleneck in the realization of the potential of tissue cytometry, particularly as methods of tissue clearing present the opportunity to characterize entire organs. Methods based on deep learning have shown enormous promise, but their implementation is hampered by the need for large amounts of manually annotated training data. In this paper, we describe 3D Nuclei Instance Segmentation Network (NISNet3D) that directly segments 3D volumes through the use of a modified 3D U-Net, 3D marker-controlled watershed transform, and a nuclei instance segmentation system for separating touching nuclei. NISNet3D is unique in that it provides accurate segmentation of even challenging image volumes using a network trained on large amounts of synthetic nuclei derived from relatively few annotated volumes, or on synthetic data obtained without annotated volumes. We present a quantitative comparison of results obtained from NISNet3D with results obtained from a variety of existing nuclei segmentation techniques. We also examine the performance of the methods when no ground truth is available and only synthetic volumes were used for training.

| S-EPMC10261124 | biostudies-literature

Lossless Three-Dimensional Parallelization in Digitally Scanned Light-Sheet Fluorescence Microscopy.

Project description:We introduce a concept that enables parallelized three-dimensional imaging throughout large volumes with isotropic 300-350 nm resolution. By staggering high aspect ratio illumination beams laterally and axially within the depth of focus of a digitally scanned light-sheet fluorescence microscope (LSFM), multiple image planes can be simultaneously imaged with minimal cross-talk and light loss. We present a first demonstration of this concept for parallelized imaging by synthesizing two light-sheets with nonlinear Bessel beams and perform volumetric imaging of fluorescent beads and invasive breast cancer cells. This work demonstrates that in principle any digitally scanned LSFM can be parallelized in a lossless manner, enabling drastically faster volumetric image acquisition rates for a given sample brightness and detector technology.

| S-EPMC5570909 | biostudies-literature

Automated three-dimensional detection and shape classification of dendritic spines from fluorescence microscopy images.

Project description:A fundamental challenge in understanding how dendritic spine morphology controls learning and memory has been quantifying three-dimensional (3D) spine shapes with sufficient precision to distinguish morphologic types, and sufficient throughput for robust statistical analysis. The necessity to analyze large volumetric data sets accurately, efficiently, and in true 3D has been a major bottleneck in deriving reliable relationships between altered neuronal function and changes in spine morphology. We introduce a novel system for automated detection, shape analysis and classification of dendritic spines from laser scanning microscopy (LSM) images that directly addresses these limitations. The system is more accurate, and at least an order of magnitude faster, than existing technologies. By operating fully in 3D the algorithm resolves spines that are undetectable with standard two-dimensional (2D) tools. Adaptive local thresholding, voxel clustering and Rayburst Sampling generate a profile of diameter estimates used to classify spines into morphologic types, while minimizing optical smear and quantization artifacts. The technique opens new horizons on the objective evaluation of spine changes with synaptic plasticity, normal development and aging, and with neurodegenerative disorders that impair cognitive function.

| S-EPMC2292261 | biostudies-literature

Three-dimensional label-free imaging throughout adipocyte differentiation by stimulated Raman microscopy.

Project description:Lipid droplets are lipid-storage organelles with a key role in lipid accumulation pathologies such as diabetes, obesity and atherosclerosis. Despite their important functions many aspects of lipid droplets biology are still unknown. This is partially due to the current use of exogenous labels to monitor their formation and remodelling by invasive imaging methods. Here, we apply stimulated Raman scattering microscopy to acquire images with high spatial resolution along with resolving capabilities of lipids and proteins and three-dimensional sectioning. Our images and data analysis demonstrate an increase in the number of large (>15μm2) lipid droplets in human adipocyte cells during differentiation process. In addition, spatially-resolved maps of lipids and proteins inside cells and three dimensional reconstructions of lipids at the initial and final steps of adipocyte differentiation are reported, too.

| S-EPMC6528968 | biostudies-literature

Label-free three-dimensional imaging of Caenorhabditis elegans with visible optical coherence microscopy.

Project description:Fast, label-free, high-resolution, three-dimensional imaging platforms are crucial for high-throughput in vivo time-lapse studies of the anatomy of Caenorhabditis elegans, one of the most commonly used model organisms in biomedical research. Despite the needs, methods combining all these characteristics have been lacking. Here, we present label-free imaging of live Caenorhabditis elegans with three-dimensional sub-micrometer resolution using visible optical coherence microscopy (visOCM). visOCM is a versatile optical imaging method which we introduced recently for tomography of cell cultures and tissue samples. Our method is based on Fourier domain optical coherence tomography, an interferometric technique that provides three-dimensional images with high sensitivity, high acquisition rate and micrometer-scale resolution. By operating in the visible wavelength range and using a high NA objective, visOCM attains lateral and axial resolutions below 1 ?m. Additionally, we use a Bessel illumination offering an extended depth of field of approximately 40 ?m. We demonstrate that visOCM's imaging properties allow rapid imaging of full sized living Caenorhabditis elegans down to the sub-cellular level. Our system opens the door to many applications such as the study of phenotypic changes related to developmental or ageing processes.

| S-EPMC5519216 | biostudies-literature

Label-free automated three-dimensional imaging of whole organs by microtomy-assisted photoacoustic microscopy.

Project description:Three-dimensional (3D) optical imaging of whole biological organs with microscopic resolution has remained a challenge. Most versions of such imaging techniques require special preparation of the tissue specimen. Here we demonstrate microtomy-assisted photoacoustic microscopy (mPAM) of mouse brains and other organs, which automatically acquires serial distortion-free and registration-free images with endogenous absorption contrasts. Without tissue staining or clearing, mPAM generates micrometer-resolution 3D images of paraffin- or agarose-embedded whole organs with high fidelity, achieved by label-free simultaneous sensing of DNA/RNA, hemoglobins, and lipids. mPAM provides histology-like imaging of cell nuclei, blood vessels, axons, and other anatomical structures, enabling the application of histopathological interpretation at the organelle level to analyze a whole organ. Its deep tissue imaging capability leads to less sectioning, resulting in negligible sectioning artifact. mPAM offers a new way to better understand complex biological organs.

| S-EPMC5680318 | biostudies-literature

Condenser-free contrast methods for transmitted-light microscopy.

Project description:Phase contrast microscopy allows the study of highly transparent yet detail-rich specimens by producing intensity contrast from phase objects within the sample. Presented here is a generalized phase contrast illumination schema in which condenser optics are entirely abrogated, yielding a condenser-free yet highly effective method of obtaining phase contrast in transmitted-light microscopy. A ring of light emitting diodes (LEDs) is positioned within the light-path such that observation of the objective back focal plane places the illuminating ring in appropriate conjunction with the phase ring. It is demonstrated that true Zernike phase contrast is obtained, whose geometry can be flexibly manipulated to provide an arbitrary working distance between illuminator and sample. Condenser-free phase contrast is demonstrated across a range of magnifications (4-100×), numerical apertures (0.13-1.65NA) and conventional phase positions. Also demonstrated is condenser-free darkfield microscopy as well as combinatorial contrast including Rheinberg illumination and simultaneous, colour-contrasted, brightfield, darkfield and Zernike phase contrast. By providing enhanced and arbitrary working space above the preparation, a range of concurrent imaging and electrophysiological techniques will be technically facilitated. Condenser-free phase contrast is demonstrated in conjunction with scanning ion conductance microscopy (SICM), using a notched ring to admit the scanned probe. The compact, versatile LED illumination schema will further lend itself to novel next-generation transmitted-light microscopy designs. The condenser-free illumination method, using rings of independent or radially-scanned emitters, may be exploited in future in other electromagnetic wavebands, including X-rays or the infrared.

| S-EPMC4277858 | biostudies-other

Accurate and fiducial-marker-free correction for three-dimensional chromatic shift in biological fluorescence microscopy.

Project description:Correction of chromatic shift is necessary for precise registration of multicolor fluorescence images of biological specimens. New emerging technologies in fluorescence microscopy with increasing spatial resolution and penetration depth have prompted the need for more accurate methods to correct chromatic aberration. However, the amount of chromatic shift of the region of interest in biological samples often deviates from the theoretical prediction because of unknown dispersion in the biological samples. To measure and correct chromatic shift in biological samples, we developed a quadrisection phase correlation approach to computationally calculate translation, rotation, and magnification from reference images. Furthermore, to account for local chromatic shifts, images are split into smaller elements, for which the phase correlation between channels is measured individually and corrected accordingly. We implemented this method in an easy-to-use open-source software package, called Chromagnon, that is able to correct shifts with a 3D accuracy of approximately 15?nm. Applying this software, we quantified the level of uncertainty in chromatic shift correction, depending on the imaging modality used, and for different existing calibration methods, along with the proposed one. Finally, we provide guidelines to choose the optimal chromatic shift registration method for any given situation.

| S-EPMC5954143 | biostudies-literature

Chronic label-free volumetric photoacoustic microscopy of melanoma cells in three-dimensional porous scaffolds.

Project description:Visualizing cells in three-dimensional (3D) scaffolds has been one of the major challenges in tissue engineering. Most current imaging modalities either suffer from poor penetration depth or require exogenous contrast agents. Here, we demonstrate photoacoustic microscopy (PAM) of the spatial distribution and temporal proliferation of cells inside three-dimensional porous scaffolds with thicknesses over 1 mm. Specifically, we evaluated the effects of seeding and culture methods on the spatial distribution of melanoma cells. Spatial distribution of the cells in the scaffold was well-resolved in PAM images. Moreover, the number of cells in the scaffold was quantitatively measured from the as-obtained volumetric information. The cell proliferation profile obtained from PAM correlated well with what was obtained using the traditional 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay.

| S-EPMC2949455 | biostudies-other

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

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