A Review of Biological Image Analysis

Chen, Weiyang; Li, Weiwei; Xiang, Dong; Pei, Jialun

doi:10.2174/1574893612666170718153316

Cited by 24 publications

(15 citation statements)

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“…Then, the number of “runs” ( R ) is computed as the number of edges connecting different samples plus one. Finally, the FR-statistic W is calculated as: being µ and σ the mean and standard deviation of the R distribution ( Chen et al, 2018 ; Friedman and Rafsky, 1979 ) .…”

Section: Methodsmentioning

confidence: 99%

OSCAR: a framework to identify and quantify cells in densely packed three-dimensional biological samples

Ledesma-Terrón

2021

Preprint

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We have developed an Object Segmentation, Counter and Analysis Resource (OSCAR) that is designed specifically to quantify densely packed biological samples with reduced signal-to-background ratio. OSCAR uses as input three dimensional images reconstructed from confocal 2D sections stained with dies such as nuclear marker and immunofluorescence labeling against specific antibodies to distinguish the cell types of interest. Taking advantage of a combination of arithmetic, geometric and statistical algorithms, OSCAR is able to reconstruct the objects in the 3D space bypassing segmentation errors due to the typical reduced signal to noise ration of biological tissues imaged in toto. When applied to the zebrafish developing retina, OSCAR is able to locate and identify the fate of each nuclei as a cycling progenitor or a terminally differentiated cell, providing a quantitative characterization of the dynamics of the developing vertebrate retina in space and time with unprecedented accuracy.

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Section: Methodsmentioning

confidence: 99%

OSCAR: a framework to identify and quantify cells in densely packed three-dimensional biological samples

Ledesma-Terrón

2021

Preprint

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“…In addition to "just" visualizing cellular processes, live-cell imaging allows to extract quantitative information from the recorded data. Generally, quantitative image analysis is a complex topic whose proper discussion is far beyond the scope of this article, hence, the reader is referred to dedicated textbooks and articles 39,40,41 . Nevertheless, some basic guidelines associated to the following example data are provided.…”

Section: Quantitative Image Analysismentioning

confidence: 99%

Application of Membrane and Cell Wall Selective Fluorescent Dyes for Live-Cell Imaging of Filamentous Fungi

Lichius

Zeilinger

2019

JoVE

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The application of membrane and cell wall selective fluorescent dyes for live-cell imaging analyses of organelle dynamics in fungal cells started two decades ago and since then continues to contribute greatly to our understanding of the filamentous fungal lifestyle. This paper provides a practical guide for the utilization of the two membrane dyes FM 1-43 and FM 4-64 and the four cell wall stains Calcofluor White M2R, Solophenyl Flavine 7GFE 500, Pontamine Fast Scarlet 48 and Congo Red. The focus is on their low-dose application to ascertain artefact-free staining, their co-imaging properties, and their quantitative evaluation. The presented methods are applicable to all filamentous fungal samples that can be prepared in the described ways. The fundamental staining approaches can serve as starting points for adaptations to species that might require different cultivation conditions. First, biophysical and biochemical properties are reviewed as their understanding is essential for using these dyes as truly vital fluorescent stains. Secondly, step-by-step protocols are presented that detail the preparation of various fungal sample types for fluorescent live-cell imaging. Finally, example experiments illustrate different approaches to: (1) identify defects in the spatio-temporal organization of endocytosis in genetic mutants, (2) comparatively characterize shared and distinct co-localization of GFP-labeled target proteins in the endocytic pathway, (3) identify morphogenetic cell wall defects in a genetic mutant, and (4) monitor cell wall biogenesis in real time. Video Link The video component of this article can be found at https://www.jove.com/video/60613/ 10. They are virtually non-fluorescent in aqueous solution, but become intensely fluorescent upon plasma membrane integration, generating excellent signal-to-noise (S/N)-ratios 11. These properties make them ideally suited for visualizing plasma membrane and intracellular organelle dynamics, including tracking of endo-and exocytosis 12. The green-fluorescent FM 1-43 and the redfluorescent FM 4-64 are the two most widely used fluorescent membrane markers for these purposes. SynaptoGreen C4 and SynaptoRed C2 are generic molecules from alternative suppliers that can be interchangeably used instead of FM 1-43 and FM 4-64, respectively. Styryl dyes comprise three key structural regions: (1) the lipophilic tail that facilitates insertion of the dye into the lipid bilayer, (2) the fluorophore core that determines the spectral properties of the dye and is constituted by two aromatic rings connected by one to three double bonds, and (3) the positively charged hydrophilic head that prevents complete insertion and permeation of the dye through the membrane (Figure 1A). The longer the lipophilic tail, the higher is the dye's hydrophobicity and thus binding affinity to the membrane, but the lower is its water solubility and membrane de-staining rate. Consequently, different FM dye variants produce different staining dynamics and patterns. The higher

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“…Coupled with electrical characterization is image processing. This has become a vital tool in biological applications for quantifying the phenotypic differences between various cell populations [ 24 ]. Screening biological samples has given scientists a deeper insight into the biological systems and their diverse processes such as gene expression, protein modification or interaction, signal transduction, and irregular RNA interference and mutations.…”

Section: Introductionmentioning

confidence: 99%

Electrical Detection of Innate Immune Cells

Ahmad

Nasser

Olule

et al. 2021

Sensors

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Accurately classifying the innate immune players is essential to comprehensively and quantitatively evaluate the interactions between the innate and the adaptive immune systems. In addition, accurate classification enables the development of models to predict behavior and to improve prospects for therapeutic manipulation of inflammatory diseases and cancer. Rapid development in technologies that provide an accurate definition of the type of cell in action, allows the field of innate immunity to the lead in therapy developments. This article presents a novel immunophenotyping technique using electrical characterization to differentiate between the two most important cell types of the innate immune system: dendritic cells (DCs) and macrophages (MACs). The electrical characterization is based on capacitance measurements, which is a reliable marker for cell surface area and hence cell size. We differentiated THP-1 cells into DCs and MACs in vitro and conducted electrical measurements on the three cell types. The results showed average capacitance readings of 0.83 µF, 0.93 µF, and 1.01 µF for THP-1, DCs, and MACs, respectively. This corresponds to increasing cell size since capacitance is directly proportional to area. The results were verified with image processing. Image processing was used for verification because unlike conventional techniques, especially flow cytometry, it avoids cross referencing and by-passes the limitation of a lack of specificity of markers used to detect the different cell types.

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A Review of Biological Image Analysis

Cited by 24 publications

References 0 publications

OSCAR: a framework to identify and quantify cells in densely packed three-dimensional biological samples

OSCAR: a framework to identify and quantify cells in densely packed three-dimensional biological samples

Application of Membrane and Cell Wall Selective Fluorescent Dyes for Live-Cell Imaging of Filamentous Fungi

Electrical Detection of Innate Immune Cells

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