Mitochondria (TEM)
Mitochondria, the powerhouses of eukaryotic cells, are well-recognized in cell biology through textbooks and electron micrographs. However, segmenting mitochondria in electron micrographs has been a significant challenge due to their similar staining characteristics and the variability in their shapes and sizes.
The Image-Pro pre-trained Mitochondria TEM deep learning model addresses this challenge, either used on its own or in combination with the Mitochondria (EM) protocol. These tools simplify the analysis of mitochondria in large volumes of TEM data, allowing for efficient processing with little to no image analysis experience. By leveraging deep learning, the process is made more accessible, ensuring more accurate results for users at all experience levels.
Techniques: FIB-SEM, TEM
How it works
Select Image
Select your TEM image and open the Mitochondria (EM) protocol.
Set Object Diameter
Set the mitochondria diameter.
Find Mitochondria
Find mitochondria with a pre-trained deep learning model.
Quantitative results
Automatically generate tables, heat maps, charts and even complex bespoke reports.
Measurement parameters supported
- • Mitochondria Count
- • Mean Mitochondria Area
- • Sum Mitochondria Area
- • Mean Mitochondria Aspect Ratio
- • Mean Circularity
- • Mean Equivalent Circle Diameter
- • Mean Diameter
- • Percent Area (Sum)
Solution requirements
Required Modules
Base
2D Automated Analysis
Cell Biology EM Protocol Collection
Mitochondria (EM) Protocol
AI Deep Learning
Life Science Models
TEM Mitochondria Model
Recommended Package
