Complex 3D biological models such as organoids and patient-derived spheroids are gaining popularity in many biomedical research areas because they more closely recapitulate in vivo tissues. These 3D models offer huge potential in disease modeling, drug screening, toxicity studies, host-microbe interactions, and precision medicine. In order to use organoids for large-scale screens, automation is vital to handle the massive amount of samples while maintaining consistent culture and reproducible iPSC lines and their derived organoids.
Access this app note to discover a solution that:- Gets robust image segmentation of label-free images with automated deep learning tools
- Customizes deep-learning segmentation models to detect complex objects of interest with minimal human intervention using SINAP
- Performs data classification easily with an intuitive machine learning phenoglyphs tool
