Automatic deep learning
Our algorithms are the basis for our cell line analysis software. Trained with more than one million images and proofed using big datasets to ensure highest quality standards, our powerful convolutional neural networks allow you to automatically analyze multiple parameters of hundreds of cells at the same time.
Real-time cell segmentation
Our software is based on the translational power of Generative Adversarial Networks (GANs) to reliably determine the total area covered by cells. Combined with our exceptionally large fields of view, you can analyze a larger population of your cells in less time.
Single cell tracking
Our models, Region Based Convolutional Neural Networks (R-CNNs), detect a large number of individual cells in lensfree microscopy images and enable non-invasive single cell tracking over days. This lays the foundation for extensive analyses of single cell motility and migration. Left: Tracking of single cell paths. Right-top: square displacement for every cell, population average (mean square displacement MSD), and fit with anomalous diffusion equation () yielding the diffusion rate at different timepoints. Right-bottom: comparison with MSD calculated by taking the difference in position every hour.