Details
Cell tracking and analysis in real time
HSA in-house developed deep learning
Tracking of cellular morphology changes and behavior in concert with
surrounding cells. Cells with increasing area are marked blue,
decreasing area red. Length of individual cell borders, circumference,
area and percentile change, compared to previous frame (Δ area, Δ
circum.), are tracked in real time.
Self developed AI networks:
Self developed AI networks:
- + Cell border gaps in the original image are closed intelligently
- + Automatic tracking of length of individual cell borders, cellular morphology changes and behavior in concert with surrounding cells
- + Visual representation of selected morphology changes (Area, circularity, neighbor cell behavior etc.)
- + Simple export of all statistical data into an Exel file
Standard Deep Learning U-Net
Simple intensity dependent annotation of cell borders vs original image
Old U-Net based AI network:
Old U-Net based AI network:
- – Gaps in the original image are not closed, therefore subsequent statistical analysis is impaired
- – Tracking of cellular parameters difficult or only possible by additional programs
- – No visual representation of selected changes in cellular morphology