AIMC Topic: Microscopy, Fluorescence

Clear Filters Showing 161 to 170 of 205 articles

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...

Multiplex protein pattern unmixing using a non-linear variable-weighted support vector machine as optimized by a particle swarm optimization algorithm.

Talanta
Most of the proteins locate more than one organelle in a cell. Unmixing the localization patterns of proteins is critical for understanding the protein functions and other vital cellular processes. Herein, non-linear machine learning technique is pro...

Building cell models and simulations from microscope images.

Methods (San Diego, Calif.)
The use of fluorescence microscopy has undergone a major revolution over the past twenty years, both with the development of dramatic new technologies and with the widespread adoption of image analysis and machine learning methods. Many open source s...

Automated Classification of Circulating Tumor Cells and the Impact of Interobsever Variability on Classifier Training and Performance.

Journal of immunology research
Application of personalized medicine requires integration of different data to determine each patient's unique clinical constitution. The automated analysis of medical data is a growing field where different machine learning techniques are used to mi...

Single-image inference of clathrin-mediated endocytosis dynamics via deep learning.

The Journal of chemical physics
Clathrin-mediated endocytosis (CME) is a vital cellular process that exhibits spatial and temporal heterogeneity in its dynamics, traditionally studied through labor-intensive time-lapse microscopy and single particle tracking. To overcome the limita...