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Microscopy, Fluorescence

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Quantitative assessment of cancer cell morphology and motility using telecentric digital holographic microscopy and machine learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
The noninvasive, fast acquisition of quantitative phase maps using digital holographic microscopy (DHM) allows tracking of rapid cellular motility on transparent substrates. On two-dimensional surfaces in vitro, MDA-MB-231 cancer cells assume several...

Nano-topography Enhances Communication in Neural Cells Networks.

Scientific reports
Neural cells are the smallest building blocks of the central and peripheral nervous systems. Information in neural networks and cell-substrate interactions have been heretofore studied separately. Understanding whether surface nano-topography can dir...

Image based Machine Learning for identification of macrophage subsets.

Scientific reports
Macrophages play a crucial rule in orchestrating immune responses against pathogens and foreign materials. Macrophages have remarkable plasticity in response to environmental cues and are able to acquire a spectrum of activation status, best exemplif...

Accurate Classification of Protein Subcellular Localization from High-Throughput Microscopy Images Using Deep Learning.

G3 (Bethesda, Md.)
High-throughput microscopy of many single cells generates high-dimensional data that are far from straightforward to analyze. One important problem is automatically detecting the cellular compartment where a fluorescently-tagged protein resides, a ta...

A Hierarchical Convolutional Neural Network for vesicle fusion event classification.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Quantitative analysis of vesicle exocytosis and classification of different modes of vesicle fusion from the fluorescence microscopy are of primary importance for biomedical researches. In this paper, we propose a novel Hierarchical Convolutional Neu...

Automating cell detection and classification in human brain fluorescent microscopy images using dictionary learning and sparse coding.

Journal of neuroscience methods
BACKGROUND: Immunofluorescence (IF) plays a major role in quantifying protein expression in situ and understanding cell function. It is widely applied in assessing disease mechanisms and in drug discovery research. Automation of IF analysis can trans...

An Overview of data science uses in bioimage informatics.

Methods (San Diego, Calif.)
This review aims at providing a practical overview of the use of statistical features and associated data science methods in bioimage informatics. To achieve a quantitative link between images and biological concepts, one typically replaces an object...

Machine learning and computer vision approaches for phenotypic profiling.

The Journal of cell biology
With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segme...

Controlled surface morphology and hydrophilicity of polycaprolactone toward human retinal pigment epithelium cells.

Materials science & engineering. C, Materials for biological applications
Applying scaffolds as a bed to enhance cell proliferation and even differentiation is one of the treatment of retina diseases such as age-related macular degeneration (AMD) which deteriorating photoreceptors and finally happening blindness. In this s...

Single Molecule Fluorescence Microscopy and Machine Learning for Rhesus D Antigen Classification.

Scientific reports
In transfusion medicine, the identification of the Rhesus D type is important to prevent anti-D immunisation in Rhesus D negative recipients. In particular, the detection of the very low expressed DEL phenotype is crucial and hence constitutes the bo...