AIMC Topic: Time-Lapse Imaging

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Time-Lapse Deep Learning for Single-Cell Subcellular Structural Phenotypic Antimicrobial Susceptibility Testing.

Analytical chemistry
Antimicrobial resistance (AMR) is a global health concern that complicates the effective treatment of infections, resulting in an increased severity of illness and elevated healthcare costs. Traditional phenotypic antimicrobial susceptibility testing...

High-resolution time-lapse imaging of droplet-cell dynamics optimal transport and contrastive learning.

Lab on a chip
Single-cell analysis is essential for uncovering heterogeneous biological functions that arise from intricate cellular responses. Here, microfluidic droplet arrays enable high-throughput data collection through cell encapsulation in picoliter volumes...

Rapid label-free identification of seven bacterial species using microfluidics, single-cell time-lapse phase-contrast microscopy, and deep learning-based image and video classification.

PloS one
For effective treatment of bacterial infections, it is essential to identify the species causing the infection as early as possible. Current methods typically require hours of overnight culturing of a bacterial sample and a larger quantity of cells t...

Deep learning methods to forecasting human embryo development in time-lapse videos.

PloS one
BACKGROUND: In assisted reproductive technology, evaluating the quality of the embryo is crucial when selecting the most viable embryo for transferring to a woman. Assessment also plays an important role in determining the optimal transfer time, eith...

Early embryo development: the current perspective in molecular evaluation and clinical status.

Systems biology in reproductive medicine
Early embryo development and competence mechanisms are paramount to ART's success but are still underexplored in human-relevant animal models. Clinical embryo evaluation remains largely based on subjectively evaluated morphological characteristics. I...

Dynamic mode decomposition for analysis and prediction of metabolic oscillations from time-lapse imaging of cellular autofluorescence.

Scientific reports
Oscillations are a common phenomenon in cell biology. They are based on non-linear coupling of biochemical reactions and can show rich dynamic behavior as found in, for example, glycolysis of yeast cells. Here, we show that dynamic mode decomposition...

Innovative AI models for clinical decision-making: predicting blastocyst formation and quality from time-lapse embryo images up to embryonic day 3.

Computers in biology and medicine
Accurate embryo assessment on embryonic day 3 of assisted reproductive technology (ART) is crucial for deciding whether to continue the culture until day 5 (blastocyst stage) or opt for earlier transfer or cryopreservation. Prolonged culture often im...

Automated phenotypic analysis and classification of drug-treated cardiomyocytes via synergized time-lapse holographic imaging and deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Predicting cardiovascular risk is critical for the therapy and control of cardiovascular illnesses. This work studies screening the toxicity of three drugs, (E-4031, isoprenaline, and sertindole) with various concentrations ...

CellPhePy: A python implementation of the CellPhe toolkit for automated cell phenotyping from microscopy time-lapse videos.

Journal of microscopy
We previously developed the CellPhe toolkit, an open-source R package for automated cell phenotyping from ptychography time-lapse videos. To align with the growing adoption of python-based image analysis tools and to enhance interoperability with wid...

Scale selection and machine learning based cell segmentation and tracking in time lapse microscopy.

Scientific reports
Monitoring and tracking of cell motion is a key component for understanding disease mechanisms and evaluating the effects of treatments. Time-lapse optical microscopy has been commonly employed for studying cell cycle phases. However, usual manual ce...