AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Microscopy, Phase-Contrast

Showing 1 to 10 of 35 articles

Clear Filters

DeepSea is an efficient deep-learning model for single-cell segmentation and tracking in time-lapse microscopy.

Cell reports methods
Time-lapse microscopy is the only method that can directly capture the dynamics and heterogeneity of fundamental cellular processes at the single-cell level with high temporal resolution. Successful application of single-cell time-lapse microscopy re...

Label-free deep learning-based species classification of bacteria imaged by phase-contrast microscopy.

PLoS computational biology
Reliable detection and classification of bacteria and other pathogens in the human body, animals, food, and water is crucial for improving and safeguarding public health. For instance, identifying the species and its antibiotic susceptibility is vita...

AI-based Apoptosis Cell Classification Using Phase-contrast Images of K562 Cells.

Anticancer research
BACKGROUND/AIM: This study aimed to automate the classification of cells, particularly in identifying apoptosis, using artificial intelligence (AI) in conjunction with phase-contrast microscopy. The objective was to reduce reliance on manual observat...

Machine learning approach for recognition and morphological analysis of isolated astrocytes in phase contrast microscopy.

Scientific reports
Astrocytes are glycolytically active cells in the central nervous system playing a crucial role in various brain processes from homeostasis to neurotransmission. Astrocytes possess a complex branched morphology, frequently examined by fluorescent mic...

Quality Control in the Corneal Bank with Artificial Intelligence: Comparison of a New Deep Learning-based Approach with Conventional Endothelial Cell Counting by the "Rhine-Tec Endothelial Analysis System".

Klinische Monatsblatter fur Augenheilkunde
Endothelial cell density (ECD) is a crucial parameter for the release of corneal grafts for transplantation. The Lions Eye Bank of Baden-Württemberg uses the "Rhine-Tec Endothelial Analysis System" for ECD quantification, which is based on a fixed co...

Rapid fiber-detection technique by artificial intelligence in phase-contrast microscope images of simulated atmospheric samples.

Annals of work exposures and health
Since the manufacture, import, and use of asbestos products have been completely abolished in Japan, the main cause of asbestos emissions into the atmosphere is the demolition and removal of buildings built with asbestos-containing materials. To dete...

Towards Fluorescent-Tag-Less Viral Titration: Automated Estimation of Cell-Size Distribution and Infection Level from Phase-Contrast Microscopy Using Deep Learning and Transfer Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automated detection of infected insect cells is one of the crucial tasks in the field of recombinant protein production and vaccine development. The major challenge lies in manual segmentation of cells and quantifying cell size distribution is tediou...

Deep learning-based segmentation of subcellular organelles in high-resolution phase-contrast images.

Cell structure and function
Although quantitative analysis of biological images demands precise extraction of specific organelles or cells, it remains challenging in broad-field grayscale images, where traditional thresholding methods have been hampered due to complex image fea...

NeuroQuantify - An image analysis software for detection and quantification of neuron cells and neurite lengths using deep learning.

Journal of neuroscience methods
BACKGROUND: The segmentation of cells and neurites in microscopy images of neuronal networks provides valuable quantitative information about neuron growth and neuronal differentiation, including the number of cells, neurites, neurite length and neur...

Automatic visual detection of activated sludge microorganisms based on microscopic phase contrast image optimisation and deep learning.

Journal of microscopy
The types and quantities of microorganisms in activated sludge are directly related to the stability and efficiency of sewage treatment systems. This paper proposes a sludge microorganism detection method based on microscopic phase contrast image opt...