Cell Morphology
Cellular morphology is highly dynamic and plastic, serving as a critical and informative trait in various biological contexts, particularly in disease studies (Tegtmeyer, 2024). The Image-Pro Cell Morphology protocol simplifies such studies by providing a comprehensive array of morphological measurements at both the individual cell level and across entire populations.
This protocol integrates seamlessly with pre-trained deep learning models, enabling accurate and reliable measurement of cellular morphology. These models often outperform traditional machine learning methods in precision and efficiency (Molho et al., 2024). Designed for user-friendliness, the protocol supports the analysis of large datasets, including complex formats like multi-well plates, with minimal image analysis expertise.
Techniques: Brightfield, Fluorescence
How it works
Select Channel
Select the channel that contains labeled cells.
Set Object Diameter
Set the diameter of labeled cells.
Find Cells
Find cells with a pre-trained deep learning model, machine learning or threshold segmentation.
Quantitative results
Automatically generate tables, heat maps, charts and even complex bespoke reports.
Measurement parameters supported
- • Aspect Ratio
- • Axis Major
- • Axis Minor
- • Clumpiness
- • Diameter
- • Diameter (Equivalent Circle)
- • Fractal Dimension
- • Heterogeneity
Solution requirements
Required Modules
Base
2D Automated Analysis
Cell Biology Protocol Collection
Cell Morphology Protocol
AI Deep Learning
Life Science Models
Fluorescent Cells Model
Recommended Package
